222 Matching Annotations
  1. Feb 2024
    1. Multiparametric characterization of scientometric performance profiles assisted by neural networks: a study of Mexican higher education institutions

      DOI: 10.1007/s11192-016-2166-0

      Caracterización multiparamétrica de perfiles de desempeño cienciométrico asistidos por redes neuronales: un estudio en instituciones de educación superior mexicanas

      Elio Atenógenes Villaseñor, Ricardo Arencibia-Jorge & Humberto Carrillo-Calvet

    1. Trends in the application of deep learning networks in medical image analysis: Evolution between 2012 and 2020

      Tendencias en la aplicación de redes de aprendizaje profundo en el análisis de imágenes médicas: Evolución entre 2012 y 2020

    1. Drug repurposing for COVID-19 via knowledge graph completion

      Reutilización de medicamentos para COVID-19 mediante la finalización del gráfico de conocimiento

    1. Network Science

      Albert-László Barabási

      Un libro de texto sobre ciencia de redes, está disponible gratuitamente bajo la licencia Creative Commons.

  2. Jan 2024
  3. Dec 2023
    1. chronic loneliness (evenif someone is not isolated) and isolation (even if someone is not lonely) representa significant health concern

      Useful to think about the matrix, even if it feels a little eat-your-vegetables.

    2. one ofthree vital components of social connection: structure, function, and quality.

      Structure: how many, what kind, how often. Function: how do (or could) other people meet your needs? Quality: positive-helpful-satisfying vs. reverse.

    3. Glossary

      Really interesting mix of things that are objectively observable and subjective interpretations of those things.

      • for: futures - neo-Venetian crypto-networks, Global Chinese Commons, GCC, cosmolocal, coordiNation, somewheres, everywheres, nowheres, Global System One, Global System Two, Global System Three, contributory accounting, fourth sector, protocol cooperative, mutual coordination economics

      • summary

      • learned something new
        • I learned a number of new ideas from reading Michel's article. He gives a brief meta-history of our political-socio-economic system, using Peter Pogany's framework of Global System One, Two and Three and within this argues for why a marriage of blockchain systems and cosmolocal production systems could create a "fourth sector" for the transition to Global System Three.
        • He cites evidence of existing trends already pointing in this direction, drawing from his research in P2P Foundation
    1. I used to be jealous of people who had “Internet friends.”

      Vgl imaginary friends that N's neighbours dubbed her online network.

  4. Sep 2023
    1. It is hard to maintain the I-you distinction, and cooperation is massively favored. This is not because the agents have become less selfish, but because the size of the self (to which they are committed) has grown. For properly coupled cells, it is impossible to hide information from each other (from yourself) and it is impossible to do anything injurious to your neighbor because the same effects (consequences) will affect you within seconds.
      • for: cellular collaboration, gap junction, bioelectrical networks, bioelectric network

      • interesting fact: multicellular mechanisms to create coherence in competent constituent subunit cells

      • more research
        • very interesting mechanisms that mediate benefits of collective behavior of competent subunits within the biological body.
  5. Aug 2023
    1. Extreme bad behaviour from governments and private companies – GAFAs [Google, Apple, Facebook, Amazon] and the like in China – will create a social and civic innovation to compensate and/or to contribute to an innovation jump. I hope for development of human cooperative brain networks.
      • for: quote, quote - Janet Salmons, quote - human cooperative brain networks, indyweb - support
      • quote
        • Extreme bad behaviour from governments and private companies – GAFAs [Google, Apple, Facebook, Amazon] and the like in China – will create a social and civic innovation to compensate and/or to contribute to an innovation jump. I hope for development of human cooperative brain networks.
      • author: Caroline Figueres
        • strategic consultant
    1. I should note that blitzscaling is not the only approach we’re seeing right now. The other (and I would argue wiser) approach to managing dense network formation is through invitation-based mechanisms. Heighten the desire, the FOMO, make participating feel special. Actively nurture the network. When done well, this can get people to go deeper in their participation, to form community.

      This seems a false dichotomy. There are more than two ways to do this, more than 'blitzscaling' and 'invitation-based' (which I have come to see as manipulative and a clear sign to stay away as it makes you the means not the goal right from the start of a platform, talking about norm setting). Federation is e.g. very different (and not even uniform in how it's different from both those options: from open to all to starting from a pre-existing small social graph offline). This like above seems to disregard, despite saying building tools is not the same as building community somewhere above, the body of knowledge about stewarding communities / network that exists outside of tech. Vgl [[Invisible hand of networks 20180616115141]]

  6. Jul 2023
    1. One feature took off immediately, for power users and casual readers alike: a simple sharing system that let users subscribe to see someone else’s starred items or share their collection of subscriptions with other people. The Reader team eventually built comments, a Share With Note feature, and more.

      Simple social sharing made the product take off

  7. Jun 2023
    1. Recent work in computer vision has shown that common im-age datasets contain a non-trivial amount of near-duplicateimages. For instance CIFAR-10 has 3.3% overlap betweentrain and test images (Barz & Denzler, 2019). This results inan over-reporting of the generalization performance of ma-chine learning systems.

      CIFAR-10 performance results are overestimates since some of the training data is essentially in the test set.

    1. AtPew Internet such things are measured as follows v :• writing material on a social networking site such as Facebook: 57% of internetusers do that• sharing photos: 37% of internet users do that• contributing rankings and reviews of products or services: 30% of internet usersdo that• creating tags of content: 28% of internet users do that• posting comments on third-party websites or blogs: 26% of internet users dothat• posting comments on other websites: 26% of internet users do that• using Twitter or other status update features: 19% of internet users do that• creating or working on a personal website: 15% of internet users do that• creating or working on a blog: 15% of internet users do that• taking online material and remixing it into a new creation: 15% of internet usersdo that with photos, video, audio or text

      Social Network activities measurement: Writing materials. Sharing Photos Contributing rankings and reviews of products or services Creating tags of content Posting comments on 3rd party websites or blogs Posting comments on other websites Using twitter or other status update features Creating or working on a personal website Creating or working on blog Taking online material and remixing into a new creation

    1. But we also need new generations of user-accountable institutions to realize the potential of new tech tools—which loops back to what I think Holgren was writing toward on Bluesky. I think it’s at the institutional and constitutional levels that healthier and more life-enhancing big-world tools and places for community and sociability will emerge—and are already emerging

      institutionalising as a way for socsoft to become sustainable, other than through for profit structures that have just one aim. Vgl [[2022 Public Spaces Conference]], I have doubts as institutions are slow by design which is what gives them their desirable stability. Vgl [[Invisible hand of networks 20180616115141]] vs markets.

      Also : generations are institutions too. It is needed to repeat these things to new gens, as they take what is currently there as given. Is currently true for things like open data too.

    2. I’ll be speaking with and writing about people working on some of the tools and communities that I think help point ways forward—and with people who’ve built fruitful, immediately useful theories and practices

      Sounds interesting. Add to feeds. Wrt [[Invisible hand of networks 20180616115141]] scaling comes from moving sideways, repetition and replication. And that takes gathering and sharing (through the network) of examples. Vgl [[OurData.eu Open Data Voorbeelden 20090720142847]] but for civic tech, socsoft? What would it look like?

  8. May 2023
    1. It turns out that backpropagation is a special case of a general techniquein numerical analysis called automatic differentiat

      Automatic differentiation is a technique in numerical analysis. That's why Real Analysis is an important Mathematics area that should be studied if one wants to go into AI research.

    1. Chatti notes that Connectivism misses some concepts, which are crucial for learning, such as reflection, learning from failures, error detection and correction, and inquiry. He introduces the Learning as a Network (LaaN) theory which builds upon connectivism, complexity theory, and double-loop learning. LaaN starts from the learner and views learning as the continuous creation of a personal knowledge network (PKN).[18]

      Learning as a Network LaaN and Personal Knowledge Network PKN , do these labels give me anything new?

      Mohamed Amine Chatti: The LaaN Theory. In: Personalization in Technology Enhanced Learning: A Social Software Perspective. Aachen, Germany: Shaker Verlag, 2010, pp. 19-42. http://mohamedaminechatti.blogspot.de/2013/01/the-laan-theory.html I've followed Chatti's blog in the past I think. Prof. Dr. Mohamed Amine Chatti is professor of computer science and head of the Social Computing Group in the Department of Computer Science and Applied Cognitive Science at the University of Duisburg-Essen. (did his PhD at RWTH in 2010, which is presumably how I came across him, through Ralf Klamma)

    1. Dave Troy is a US investigative journalist, looking at the US infosphere. Places resistance against disinformation not as a matter of factchecking and technology but one of reshaping social capital and cultural network topologies.

      Early work by Valdis Krebs comes to mind vgl [[Netwerkviz en people nav 20091112072001]] and how the Finnish 'method' seemed to be a mix of [[Crap detection is civic duty 2018010073052]] and social capital aspects. Also re taking an algogen text as is / stand alone artefact vs seeing its provenance and entanglement with real world events, people and things.

    1. Once two people, they can confirm the humanity of everyone else they've met IRL. Two people who know each of these people can confirm each other's humanity because of this trust network.

      ssl parties etc. Threema. mentioned above. Catfish! Scale is an issue in the sense that social distance will remain social distance, so it still leaves you with the question how to deal with something that is from a far away social distance (as is an issue on the web now: how we solve it is lurking / interacting and then when the felt distance is smaller go to IRL)

    2. As we start to doubt all “people” online, the only way to confirm humanity is to meet offline over coffee or a drink.

      this is already common for decades, not because of doubt, but because of being human. My blogging since 2002 has created many new connections to people ('you imaginary friends' the irl friends of a friend call them teasingly), and almost immediately there was a shared need felt to meet up in person. Online allowed me to cast a wider net for connections, but over time that was spun into something IRL. I visited conferences for this, organised conferences for it, traveled to people's homes, many meet-ups, our birthday unconferences are also a shape of this. Vgl [[Menselijk en digitaal netwerk zijn gelijksoortig 20200810142551]] Dopplr serviced this.

  9. Apr 2023
    1. Practical reasoning is a goal-directed sequence of linked practical inferencesthat seeks out a prudent line of conduct for an agent in a set of particular circumstances known by the agent. Where a is an agent, A is an action, and G a goal, thetwo basic types of practical inferences are respectively, the necessary conditionscheme and the sufficient condition scheme (Walton, Pract. Reas., 1 990; see alsoSchellens, 1 987).G is a goal for aDoing A is necessary for a to carry out GTherefore, a ought to do AG is a goal for aDoing A is sufficient for a to carry out GTherefore, a ought to do A
      • Goal Directed sequence
      • Agent Awareness
      • Act may be sufficient or necessary for Goal. *Therefore, Agent carries Act out
      • Required to Understand the Qualification Weight of Act is it necessary or sufficient?
    2. Clearly this type of reasoning has an argumentation scheme. One premisedefines or describes a goal. The other premise describes a means of achieving thegoal. The conclusion directs the agent towards action to carry out the means.6But this type of reasoning is so common and distinctive, having manyvariants and subspecies of argumentation, that it is misleading to call it anargumentation scheme. Better to call it a type of reasoning that can be used inargumentation in different types of dialogue (as in Walton, What Reas., 1990).
      • Agential Network
      • Case and Inferential Qualifications
      • Conclusions and Goal Relations
      • Normative Framework
  10. Mar 2023
  11. Feb 2023
    1. fz is less about the tree (though that is important) and more about the UX.

      I do like the framing of folgezettel as a benefit with respect to user experience.


      There is a lot of mention of the idea of trees within the note taking and zettelkasten space, but we really ought to be looking more closely at other living systems models like rhizomes and things which have a network-like structure.

  12. Jan 2023
    1. the concept of the network is merely a renewal of a certain positivist philosophy of Saint-Simon from the dawn of the industrial era, when the followers of Saint-Simon imagined that a vast network would unite all of humanity, abolishing archaic national and religious boundaries via the proliferation of new industrial interconnections in the forms of canals and railways.

      Saint-Simon, positivist utopian, saw world-changing networks in channels and railways (and he wasn't mistaken). A slow internet.

    2. For decades, the Zapatistas, usually via Subcomandante Marcos, sent out communique after communique to the world, poetically asking for solidarity. Surprisingly, the world responded, forming the alterglobalisation movement that called itself a ‘network of networks’ – a phrase also used at the time to describe the internet.

      Zapatistas and the internet, network of networks.

  13. Dec 2022
    1. the future I believe is communities where humans come together in groups and we start to cooperate. And the community itself takes on a life of its own. So this is the mentality I believe that we will evolve over time.

      !- future vision : locally cooperative hubs of trust - locally dense cooperation networks

  14. Nov 2022
    1. n recent years, the neural network based topic modelshave been proposed for many NLP tasks, such as infor-mation retrieval [11], aspect extraction [12] and sentimentclassification [13]. The basic idea is to construct a neuralnetwork which aims to approximate the topic-word distri-bution in probabilistic topic models. Additional constraints,such as incorporating prior distribution [14], enforcing di-versity among topics [15] or encouraging topic sparsity [16],have been explored for neural topic model learning andproved effective.

      Neural topic models are often trained to mimic the behaviours of probabilistic topic models - I should come back and look at some of the works:

      • R. Das, M. Zaheer, and C. Dyer, “Gaussian LDA for topic models with word embeddings,”
      • P. Xie, J. Zhu, and E. P. Xing, “Diversity-promoting bayesian learning of latent variable models,”
      • M. Peng, Q. Xie, H. Wang, Y. Zhang, X. Zhang, J. Huang, and G. Tian, “Neural sparse topical coding,”
  15. Oct 2022
    1. It may be that the more concrete boundaries that having multiple instances provide can dampen down the cascades caused by the small world network effect. It is an interesting model to coexist between the silos with global scope and the personal domains beloved by the indieweb. In indieweb we have been saying ‘build things that you want for yourself’, but building things that you want for your friends or organisation is a useful step between generations.

      I'd say not just interesting, but also crucial. Where T and FB operate at generic level (despite FB pages as subgroups), the statistical, and IndieWeb on the personal (my site, my self-built tool), M works at group level or just above (bigger instances). That middle ground between singular and the statistical is where complexity resides and where it needs to be addressed and embraced. The network metaphor favors that intermediate level.

    1. The essential truth of every social network is that the product is content moderation, and everyone hates the people who decide how content moderation works.
    2. the problems with Twitter are not engineering problems. They are political problems. Twitter, the company, makes very little interesting technology; the tech stack is not the valuable asset. The asset is the user base: hopelessly addicted politicians, reporters, celebrities, and other people who should know better but keep posting anyway.

      Twitter's primary asset is not their technology, but their addicted user base.

    1. It was only on these social networking sites, where people have a podium, that I noticed quite a change in discourse. All of a sudden, you could read family and friends' thoughts on all types of subjects that are never uttered in person.
  16. Sep 2022
    1. Multidiscpl teams are different from heterogenous ones when it comes to learning. Dense networks useful for incremental steps, but hinder innovative steps (Vgl [[Lurking Weak Strong Ties 20040204063311]]) Provide team design principles.

      Full paper in Zotero

    1. translate those notions into stuff that I can tackle in my own sphere of influence. And to me those then make up the stuff that matters.

      Things that matter are a combination of things of interest plus sphere of influence/action radius. This can bring macro issues into a place where they can be addressed by micro actions that have meaning locally and contribute to the issue at scale. Contributes to the invisible hand of networks. Vgl [[Invisible hand of networks 20180616115141]]

  17. Aug 2022
    1. If you decentralize, the system will recentralize, but one layer up. Something new will be enabled by decentralization. That sounds like evolution through layering, like upward-spiraling complexity. That sounds like progress to me.

      Systems will centralise one step up from where it's decentralised. Interesting. My intuition is a bit 'softer' it's a rule of thumb for coalescence. Things might coalesce out of different needs/circumstances. The type of centralisation intended here, if it's about the silo's there's a external driver, that the easiest business models are found in centralisation as it creates asymmetric power for the centraliser. It's not a necessary outcome of the underlying distributedness, but something that others might need using that distributedness. If centrliasation isn't possible or allowed at some layer, it may well force external drivers for centralisation one layer up. Organisations as well as CoPs are mushrooms on the mycelium of human networks. Now that capital, location and finding colleagues can be done distributedly those mushrooms aren't always needed, and we see other types of mushrooms coalesce alongside classic organisations. Something like that?

    1. Mobile Network Hacking, IP Edition. by Karsten Nohl, Luca Melette & Sina Yazdanmehr. Black Hat. London. December 2-5, 2019. 47 minute video. https://www.blackhat.com/eu-19/briefings/schedule/index.html#mobile-network-hacking-ip-edition-17617

      Mobile networks have gone through a decade of security improvements ranging from better GSM encryption to stronger SIM card and SS7 configurations. These improvements were driven by research at this and other hacking conferences.

      Meanwhile, the networks have also mushroomed in complexity by integrating an ever-growing number of IT technologies from SIP to WiFi, IPSec, and most notably web technologies.

      This talk illustrates the security shortcomings when merging IT protocols into mobile networks. We bring back hacking gadgets long thought to be mitigated, including intercepting IMSI catchers, remote SMS intercept, and universal caller ID spoofing.

      We explore which protection measures are missing from the mobile network and discuss how to best bring them over from the IT security domain into mobile networks.

    1. On the Internet there are many collective projects where users interact only by modifying local parts of their shared virtual environment. Wikipedia is an example of this.[17][18] The massive structure of information available in a wiki,[19] or an open source software project such as the FreeBSD kernel[19] could be compared to a termite nest; one initial user leaves a seed of an idea (a mudball) which attracts other users who then build upon and modify this initial concept, eventually constructing an elaborate structure of connected thoughts.[20][21]

      Just as eusocial creatures like termites create pheromone infused mudballs which evolve into pillars, arches, chambers, etc., a single individual can maintain a collection of notes (a commonplace book, a zettelkasten) which contains memetic seeds of ideas (highly interesting to at least themselves). Working with this collection over time and continuing to add to it, modify it, link to it, and expand it will create a complex living community of thoughts and ideas.

      Over time this complexity involves to create new ideas, new structures, new insights.

      Allowing this pattern to move from a single person and note collection to multiple people and multiple collections will tend to compound this effect and accelerate it, particularly with digital tools and modern high speed communication methods.

      (Naturally the key is to prevent outside selfish interests from co-opting this behavior, eg. corporate social media.)

  18. Jul 2022
  19. Jun 2022
    1. few other large platforms unwittingly dissolved the mortar of trust, belief in institutions, and shared stories that had held a large and diverse secular democracy together.
    1. What's become clear is that our relationships are experiencing a profound reset. Across generations, having faced a stark new reality, a decades-long trend1 reversed as people are now shifting their energy away from maintaining a wide array of casual connections to cultivating a smaller circle of the people who matter most.

      ‘how the demand for deeper human connection has sparked a profound reset in our relationships’.

      The Meta Foresight (formerly Facebook IQ) team conducted a survey of 36,000 adults across 12 markets.

      Among their key findings:

      72% of respondents said that the pandemic caused them to reprioritize their closest friends
      Young people are most open to using more immersive tech to foster connections (including augmented and virtual reality), though all users indicated that tech will play a bigger role in enhancing personal connections moving forward
      37% of people surveyed globally reported reassessing their life priorities as a result of the pandemic
      
    1. algorithmic radicalization is presumably a simpler problem to solve than the fact that there are people who deliberately seek out vile content. “These are the three stories—echo chambers, foreign influence campaigns, and radicalizing recommendation algorithms—but, when you look at the literature, they’ve all been overstated.”

      algorithmic radicalization

    2. “A lot of the stories out there are just wrong,” he told me. “The political echo chamber has been massively overstated. Maybe it’s three to five per cent of people who are properly in an echo chamber.” Echo chambers, as hotboxes of confirmation bias, are counterproductive for democracy. But research indicates that most of us are actually exposed to a wider range of views on social media than we are in real life, where our social networks—in the original use of the term—are rarely heterogeneous.
  20. May 2022
    1. Indeed, as David Haskell, a biologist and writer, notes, a tree is “a community of cells” from many species: “fungus, bacteria, protist, alga, nematode and plant.” And often “the smallest viable genetic unit [is] … the networked community.”

      Explore this idea....

      What does it look like quantitatively?

    1. the death of Gerri Santoro, a woman who died seeking an illegal abortion in Connecticut, ignited a renewed fervor among those seeking to legalize abortion. Santoro’s death, along with many other reported deaths and injuries also sparked the founding of underground networks such as The Jane Collective to offer abortion services to those seeking to end pregnancies.
  21. Apr 2022
    1. Social networks may thus be “sticky” because social integration provides both benefits that encourage staying and social deterrents to leaving, increasing the chances of persistence.

      Important point - persistence can be because of negative reasons.

    2. persistence is the product of not only individual processes but also relational ones
    3. Students in a gateway biology course were randomly assigned to complete a control or values affirmation exercise, a psychological intervention hypothesized to have positive social effects. By the end of the term, affirmed students had an estimated 29% more friends in the course on average than controls. Affirmation also prompted structural changes in students’ network positions such that affirmed students were more central in the overall course friendship network.
  22. Feb 2022
    1. When I hear people in a variety of contexts talking about “building community” for students or colleagues (or, customers), I worry about that, too.  Is the motivation an additive one?  “Let’s give them more people to connect with and rely on?”  Or is it intended to be a kind of capture?

      What an enormous challenge for those of us in faculty development and other "community-building" businesses. Are we actually serving when we help people acculturate? We might be. We also might be trying to capture peoples' time and attention and loyalty.

  23. Jan 2022
    1. https://vimeo.com/232545219

      from: Eyeo Conference 2017

      Description

      Robin Sloan at Eyeo 2017 | Writing with the Machine | Language models built with recurrent neural networks are advancing the state of the art on what feels like a weekly basis; off-the-shelf code is capable of astonishing mimicry and composition. What happens, though, when we take those models off the command line and put them into an interactive writing environment? In this talk Robin presents demos of several tools, including one presented here for the first time. He discusses motivations and process, shares some technical tips, proposes a course for the future — and along the way, write at least one short story together with the audience: all of us, and the machine.

      Notes

      Robin created a corpus using If Magazine and Galaxy Magazine from the Internet Archive and used it as a writing tool. He talks about using a few other models for generating text.

      Some of the idea here is reminiscent of the way John McPhee used the 1913 Webster Dictionary for finding words (or le mot juste) for his work, as tangentially suggested in Draft #4 in The New Yorker (2013-04-22)

      Cross reference: https://hypothes.is/a/t2a9_pTQEeuNSDf16lq3qw and https://hypothes.is/a/vUG82pTOEeu6Z99lBsrRrg from https://jsomers.net/blog/dictionary


      Croatian acapella singing: klapa https://www.youtube.com/watch?v=sciwtWcfdH4


      Writing using the adjacent possible.


      Corpus building as an art [~37:00]

      Forgetting what one trained their model on and then seeing the unexpected come out of it. This is similar to Luhmann's use of the zettelkasten as a serendipitous writing partner.

      Open questions

      How might we use information theory to do this more easily?

      What does a person or machine's "hand" look like in the long term with these tools?

      Can we use corpus linguistics in reverse for this?

      What sources would you use to train your model?

      References:

      • Andrej Karpathy. 2015. "The Unreasonable Effectiveness of Recurrent Neural Networks"
      • Samuel R. Bowman, Luke Vilnis, Oriol Vinyals, et al. "Generating sentences from a continuous space." 2015. arXiv: 1511.06349
      • Stanislau Semeniuta, Aliaksei Severyn, and Erhardt Barth. 2017. "A Hybrid Convolutional Variational Autoencoder for Text generation." arXiv:1702.02390
      • Soroush Mehri, et al. 2017. "SampleRNN: An Unconditional End-to-End Neural Audio Generation Model." arXiv:1612.07837 applies neural networks to sound and sound production
    1. https://www.youtube.com/watch?v=z3Tvjf0buc8

      graph thinking

      • intuitive
      • speed, agility
      • adaptability

      ; graph thinking : focuses on relationships to turn data into information and uses patterns to find meaning

      property graph data model

      • relationships (connectors with verbs which can have properties)
      • nodes (have names and can have properties)

      Examples:

      • Purchase recommendations for products in real time
      • Fraud detection

      Use for dependency analysis

  24. Dec 2021
    1. What is P2P (peer-to-peer) and what can you do with it? https://www.itpedia.nl/wp-content/uploads/2018/12/fingerworld.jpg.webp In a sense, Peer to Peer (P2P) networks are the social networks of the Internet. Every peer is equal to the others, and every peer has the same rights and duties as the others. Peers are clients and servers at the same time.

    1. It is impossible to think without writing; at least it is impossible in any sophisticated or networked (anschlußfähig) fashion.

      The sentiment that it is impossible to think without writing is patently wrong. While it's an excellent tool, it takes an overly textual perspective and completely ignores the value of orality an memory in prehistory.

      Modern culture has lost so many of our valuable cultural resources that we have completely forgotten that they even existed.

      Oral cultures certainly had networked thought, Luhmann and others simply can't imagine how it may have worked. We're also blinded by the imagined size of societies in pre-agricultural contexts. The size and scope of cities and city networks makes the history of writing have an outsized appearance.

      Further, we don't have solid records of these older netowrks, a major drawback of oral cultures which aren't properly maintained, but this doesn't mean that they didn not exist.

  25. Nov 2021
    1. people reading the same book at the same time, exploring the same ideas…Norms around signalling you're interested in something, and the extent of your interest, would go far

      How do we find the connections we don't know we're looking for?

  26. Sep 2021
    1. "Human nature is not a machine to be built after a model, and set to do exactly the work prescribed for it, but a tree which requires to grow and develop itself on all sides, according to the tendency of the inward forces which make it a living thing. Such are the differences among human beings in their sources of pleasure, their susceptibilities of pain, and the operation on them of different physical and moral agencies, that unless there is a corresponding diversity in their modes of life, they neither obtain their fair share of happiness, nor grow up to the mental, moral, and aesthetic stature of which their nature is capable." John Stuart Mill, On Liberty (1859)
  27. Aug 2021
  28. Jul 2021
    1. Supply chains—starting with the factories upstream, running through the ports and rail yards and warehouses, and ending with retail—are large and complex systems. These systems need to be adaptive, and yet the news shows us they are not. 

      We need supply chains to route around problems in the same way that packets on the internet route around bottlenecks and broken connections.

  29. Jun 2021
  30. May 2021
  31. Apr 2021
    1. This looks fascinating. I'm not so much interested in the coding/programming part as I am the actual "working in public" portions as they relate to writing, thinking, blogging in the open and sharing that as part of my own learning and growth as well as for sharing that with a broader personal learning network. I'm curious what lessons might be learned within this frame or how educators and journalists might benefit from it.

    1. Others are asking questions about the politics of weblogs – if it’s a democratic medium, they ask, why are there so many inequalities in traffic and linkage?

      This still exists in the social media space, but has gotten even worse with the rise of algorithmic feeds.

  32. Mar 2021
    1. he Cyborg Manifesto, Donna Haraway talks about the possibility of networks. While the Facebook of 2021 strings us out along a spectrum and pushes us to either end, Haraway’s conception of a network in 1985 is “the profusion of space and identities and the permeability of boundaries in the personal body and the body politic.” I

      An interesting data point in the evolution of networks

    1. Particularly striking in 1971 was his call for advanced technology to support "learning webs": The operation of a peer-matching network would be simple. The user would identify himself by name and address and describe the activity for which he sought a peer. A computer would send him back the names and addresses of all those who had inserted the same description. It is amazing that such a simple utility has never been used on a broad scale for publicly valued activity.
  33. Feb 2021
    1. Cytoscape is an open source software platform for visualizing complex networks and integrating these with any type of attribute data. A lot of Apps are available for various kinds of problem domains, including bioinformatics, social network analysis, and semantic web.
  34. Jan 2021
  35. Dec 2020
    1. If you look at the same graph with distance 2, the layer of additionally visible nodes show how my new Notion might be connected to things like online identity, using the environment to store memory and layered access to information. This triggers additional thoughts during the writing process.

      Lovely. This is such a great insight that I can already see is going to help me a lot.

  36. Oct 2020
    1. In at least one instance, a foreign adversary was able to take advantage of a back door invented by U.S. intelligence, according to Juniper Networks Inc, which said in 2015 its equipment had been compromised. In a previously unreported statement to members of Congress in July seen by Reuters, Juniper said an unnamed national government had converted the mechanism first created by the NSA.

      NSA gets Juniper to put a backdoor in one of their products. The product gets compromised by a foreign government in 2015.

    1. Workplace Learning in Informal Networks

      Milligan, C., Littlejohn, A., & Margaryan, A. (2014). Workplace Learning in Informal Networks. Journal of Interactive Media in Education.

      Learning does not stop when an individual leaves formal education, but becomes increasingly informal, and deeply embedded within other activities such as work. This article describes the challenges of informal learning in knowledge intensive industries, highlighting the important role of personal learning networks. The article argues that knowledge workers must be able to self-regulate their learning and outlines a range of behaviours that are essential to effective learning in informal networks. The article identifies tools that can support these behaviours in the workplace and how they might form a personal work and learning environment.

      https://search.ebscohost.com/login.aspx?direct=true&AuthType=shib&db=eric&AN=EJ1034717&site=eds-live&scope=site&custid=uphoenix

      7/10

    1. Newport is an academic — he makes his primary living teaching computer science at a university, so he already has a built-in network and a self-contained world with clear moves towards achievement.

      This is one of the key reasons people look to social media--for the connections and the network they don't have via non-digital means. Most of the people I've seen with large blogs or well-traveled websites have simply done a much better job of connecting and interacting with their audience and personal networks. To a great extent this is because they've built up a large email list to send people content directly. Those people then read their material and comment on their blogs.

      This is something the IndieWeb can help people work toward in a better fashion, particularly with better independent functioning feed readers.

    1. That is to say: if the problem has not been the centralized, corporatized control of the individual voice, the individual’s data, but rather a deeper failure of sociality that precedes that control, then merely reclaiming ownership of our voices and our data isn’t enough. If the goal is creating more authentic, more productive forms of online sociality, we need to rethink our platforms, the ways they function, and our relationships to them from the ground up. It’s not just a matter of functionality, or privacy controls, or even of business models. It’s a matter of governance.
    1. Thought leader and tech executive, John Ryan, provided valuable historical context both onstage and in his recent blog. He compared today’s social media platforms to telephone services in 1900. Back then, a Bell Telephone user couldn’t talk to an AT&T customer; businesses had to have multiple phone lines just to converse with their clients. It’s not that different today, Ryan asserts, when Facebook members can’t share their photos with Renren’s 150 million account holders. All of these walled gardens, he said, need a “trusted intermediary” layer to become fully interconnected.

      An apt analogy which I've used multiple times in the past.

    1. Micro.blog is not an alternative silo: instead, it’s what you build when you believe that the web itself is the great social network.

      So true!!!

    1. cyberinfrastructure is something more specific thanthe network itself, but it is something more general than a tool or a resource developed for a particular proj-ect, a range of projects, or, even more broadly, for a particular discipline.

      Mentioned in the video https://youtu.be/lelmXaSibrc?t=17m35s

    1. Mutual aid societies were built on the razed foundations of the old  guilds, and cooperatives and mass political parties then drew on the  experience of the mutual aid societies."

      This reminds me of the beginning of the Civil Rights movement that grew out of the civic glue that arose out of prior work relating to rape cases several years prior.

      I recall Zeynep Tufekci writing a bit about some of these tangential ideas in some of her social network writing. (Where's the link to that?)

  37. Aug 2020
  38. Jul 2020
  39. Jun 2020
  40. May 2020
  41. Apr 2020
    1. import all the necessary libraries into our notebook. LibROSA and SciPy are the Python libraries used for processing audio signals. import os import librosa #for audio processing import IPython.display as ipd import matplotlib.pyplot as plt import numpy as np from scipy.io import wavfile #for audio processing import warnings warnings.filterwarnings("ignore") view raw modules.py hosted with ❤ by GitHub View the code on <a href="https://gist.github.com/aravindpai/eb40aeca0266e95c128e49823dacaab9">Gist</a>. Data Exploration and Visualization Data Exploration and Visualization helps us to understand the data as well as pre-processing steps in a better way. 
    2. TensorFlow recently released the Speech Commands Datasets. It includes 65,000 one-second long utterances of 30 short words, by thousands of different people. We’ll build a speech recognition system that understands simple spoken commands. You can download the dataset from here.
    3. In the 1980s, the Hidden Markov Model (HMM) was applied to the speech recognition system. HMM is a statistical model which is used to model the problems that involve sequential information. It has a pretty good track record in many real-world applications including speech recognition.  In 2001, Google introduced the Voice Search application that allowed users to search for queries by speaking to the machine.  This was the first voice-enabled application which was very popular among the people. It made the conversation between the people and machines a lot easier.  By 2011, Apple launched Siri that offered a real-time, faster, and easier way to interact with the Apple devices by just using your voice. As of now, Amazon’s Alexa and Google’s Home are the most popular voice command based virtual assistants that are being widely used by consumers across the globe. 
    4. Learn how to Build your own Speech-to-Text Model (using Python) Aravind Pai, July 15, 2019 Login to Bookmark this article (adsbygoogle = window.adsbygoogle || []).push({}); Overview Learn how to build your very own speech-to-text model using Python in this article The ability to weave deep learning skills with NLP is a coveted one in the industry; add this to your skillset today We will use a real-world dataset and build this speech-to-text model so get ready to use your Python skills!
    1. Keras is a high-level neural networks API, written in Python and capable of running on top of TensorFlow, CNTK, or Theano. It was developed with a focus on enabling fast experimentation. Being able to go from idea to result with the least possible delay is key to doing good research. Use Keras if you need a deep learning library that: Allows for easy and fast prototyping (through user friendliness, modularity, and extensibility). Supports both convolutional networks and recurrent networks, as well as combinations of the two. Runs seamlessly on CPU and GPU. Read the documentation at Keras.io. Keras is compatible with: Python 2.7-3.6.
    1. Networks  of civic engagement increase the potential cost to defectors who risk  benefits from future transactiaction. The same networks foster norms of  reciprocity that are reinforced by the networks of relationships in  which reputation is both balued and discussed. The same social networks  facilitate the flow of reputational information.

      How can we build some of this into social media networks to increase the level of trust and facts?

    1. there’s nothing exceptional about human brains.

      But is there something exceptional about the societies we have built? And the culture (including everything: chairs, tables, houses, streets, etc, etc) that surrounds us? I mean: is consciousness something that we have as individuals? Or is is something collective that we feel individually? Like a node in a vast network that gets a feeling of the local consciousness that the whole network has, and feels as if it is his/her own consciousness...

  42. Feb 2020
    1. The wiki can be used as a semantic networking tool, a way to construct meaningful connections between topics, ideas or concepts. A semantic network is composed of nodes (such as wiki pages ) with meaningful links (hyperlinks) connecting them. A semantic network of wikis can help learners to organize their ideas and to convey that organisation of ideas to others (Jonassen et al, 1999, p.165)

      semantic networking tool: a way to construct meaningful connections between topics, ideas or concepts. A semantic network is composed of nodes (such as wiki pages) with meaningful links (hyperlinks) connecting them. The pages are nodes the hyperlinks are the meaningful links. You can also see how important a concept is by the times it appears in other pages.s

  43. Jan 2020
  44. Dec 2019
    1. "Most of the structuring forms I'll show you stem from the simple capability of being able to establish arbitrary linkages between different substructures, and of directing the computer subsequently to display a set of linked substructures with any relative positioning we might designate among the different substructures. You can designate as many different kinds of links as you wish, so that you can specify different display or manipulative treatment for the different types."
    2. "You usually think of an argument as a serial sequence of steps of reason, beginning with known facts, assumptions, etc., and progressing toward a conclusion. Well, we do have to think through these steps serially, and we usually do list the steps serially when we write them out because that is pretty much the way our papers and books have to present them—they are pretty limiting in the symbol structuring they enable us to use. Have you even seen a 'scrambled-text' programmed instruction book? That is an interesting example of a deviation from straight serial presentation of steps.3b6b "Conceptually speaking, however, an argument is not a serial affair. It is sequential, I grant you, because some statements have to follow others, but this doesn't imply that its nature is necessarily serial. We usually string Statement B after Statement A, with Statements C, D, E, F, and so on following in that order—this is a serial structuring of our symbols. Perhaps each statement logically followed from all those which preceded it on the serial list, and if so, then the conceptual structuring would also be serial in nature, and it would be nicely matched for us by the symbol structuring.3b6c "But a more typical case might find A to be an independent statement, B dependent upon A, C and D independent, E depending upon D and B, E dependent upon C, and F dependent upon A, D, and E. See, sequential but not serial? A conceptual network but not a conceptual chain. The old paper and pencil methods of manipulating symbols just weren't very adaptable to making and using symbol structures to match the ways we make and use conceptual structures. With the new symbol-manipulating methods here, we have terrific flexibility for matching the two, and boy, it really pays off in the way you can tie into your work.3b6d This makes you recall dimly the generalizations you had heard previously about process structuring limiting symbol structuring, symbol structuring limiting concept structuring, and concept structuring limiting mental structuring.
  45. Nov 2019
    1. HGT typically adds new catabolic routes to microbial metabolic networks. This increases the chance of new metabolic interactions between bacteria
  46. Jul 2019
    1. Compared with neural networks configured by a pure grid search,we find that random search over the same domain is able to find models that are as good or betterwithin a small fraction of the computation time.
  47. Jun 2019
    1. Throughout the past two decades, he has been conducting research in the fields of psychology of learning and hybrid neural network (in particular, applying these models to research on human skill acquisition). Specifically, he has worked on the integrated effect of "top-down" and "bottom-up" learning in human skill acquisition,[1][2] in a variety of task domains, for example, navigation tasks,[3] reasoning tasks, and implicit learning tasks.[4] This inclusion of bottom-up learning processes has been revolutionary in cognitive psychology, because most previous models of learning had focused exclusively on top-down learning (whereas human learning clearly happens in both directions). This research has culminated with the development of an integrated cognitive architecture that can be used to provide a qualitative and quantitative explanation of empirical psychological learning data. The model, CLARION, is a hybrid neural network that can be used to simulate problem solving and social interactions as well. More importantly, CLARION was the first psychological model that proposed an explanation for the "bottom-up learning" mechanisms present in human skill acquisition: His numerous papers on the subject have brought attention to this neglected area in cognitive psychology.
    1. However, this doesn’t mean that Min-Max scaling is not useful at all! A popular application is image processing, where pixel intensities have to be normalized to fit within a certain range (i.e., 0 to 255 for the RGB color range). Also, typical neural network algorithm require data that on a 0-1 scale.

      Use min-max scaling for image processing & neural networks.

  48. Apr 2019
    1. Most of these near clones have and will fail. The reason that matching the basic proof of work hurdle of an Status as a Service incumbent fails is that it generally duplicates the status game that already exists. By definition, if the proof of work is the same, you're not really creating a new status ladder game, and so there isn't a real compelling reason to switch when the new network really has no one in it.

      This presumes that status is the only reason why people would join such a network. It also underlines the fact that the platform needs to be easy and simple to use, otherwise no one enters it and uses it as the tool first before the network exists.

  49. Mar 2019
  50. Feb 2019
    1. y, these occurrences –which 38arguablycan be considered the norm rather than the exception in related taxa –may 39provide useful evidence of relatednes

      This is very true.

      And one reason more why especially palaeontologists should stop ignoring distance-based networks (following the Farris'ian Dogma that "distance = phenetic", but see Felsenstein, 2004, Inferring Phylogenies) as a tool to explore the non-trivial signal in their data sets — some application examples posted at the Genealogical World of Phylogenetic Networks; see also Denk & Grimm, Rev. Pal. Pal. 2009, Bomfleur et al., BMC Evol. Biol. 2015, —, PeerJ, 2017. Even in the absence of reticulation, evolving morphologies do not provide tree-like signal, because synapomorphies, characters fully compatible with the true tree, are rare, homoiologies common, and convergences, characters incompatible with the true tree, inevitable.

      The less tree-like the signal and the more different the individual probabilities for change, the more misleading or ambiguous will be the parsimony tree reconstruction. Neighbour-nets may appear to be crude tools, but are quick-to-infer, designed to handle data incompatibility. Consensus networks are, in any possible aspect, more informative than a strict or majority rule consensus tree.

      Instead of trying to decide between equally and inevitable biased trees, we can just explore our data, using networks. See pic, depicting all potential synapomorphies, bold, symplesiomorphies, italics, and homoiologies that can be inferred directly from the crocodilian morphomatrix. Naturally including pseudo-synapomorphies (red) when compared to the provided molecular tree.

      PS That the way out of the dilemma is to embrace networks has been realised very early in evolutionary sciences (long before Hennig and Farris).

      Pic3

    1. “the true benefit of the academy is the interaction, the accessto the debate, to the negotiation of knowledge—not to the stale cataloging of content

      Once this particular light goes on in one's head, it may be impossible to turn it off. Yet we still need the so-called "stale" cataloging of content. We need foundational knowledge. Perhaps the academy has just made its function (again) more visible under connectivism? And we are in a creative tension of sorts with knowledge cataloging as an end in itself?

  51. Jan 2019
    1. Finally, a maincontribution of this research lies in the examination of the solicitation of expertise in a digitally-connected world, where widely distributed and diverse expertise must nevertheless be realized under highly localized conditions.

      Evokes crowdsourcing/peer production literature on expertise (Majchrzak et al, Faraj et al, Benkler et al, Kittur,et al.)

  52. Dec 2018
    1. It is based on reciprocity and a level of trust that each party is actively seeking value-added information for the other.

      Seems like this is a critical assumption to examine for current media literacy/misinformation discussions. As networks become very large and very flat, does this assumption of reciprocity and good faith hold? (I'm thinking, here, of people whose expertise I trust in one domain but perhaps not in another, or the fact that sometimes I'm talking to one part of my network and not really "actively seeking information" for other parts.)

    1. feed-forward network (also known as a multilayer perceptron)

      In the network, each layer has variety of cells, which connect to next layers cells.

  53. Nov 2018
    1. At Clark, we established networked communities to help professors from different disciplines share innovative pedagogies and ideas for leading student work on group projects.

      Specifically how is "networked communities" being used in this context? "Networked" how (technically, practically, and organizationally)?

  54. Oct 2018
    1. Do neural networks dream of semantics?

      Neural networks in visual analysis, linguistics Knowledge graph applications

      1. Data integration,
      2. Visualization
      3. Exploratory search
      4. Question answering

      Future goals: neuro-symbolic integration (symbolic reasoning and machine learning)

  55. Aug 2018
    1. To start you thinking, here’s a quote from lead educator Jean Burgess. Jean considers how Twitter has changed since 2006 and reflects on her own use of the platform in the context of changing patterns of use. In response to the suggestion that Twitter is a dying social media platform, Jean states that: the narratives of decline around the place at the moment […] have to do with a certain loss of sociability. And to those of us for whom Twitter’s pleasures were as much to do with ambient intimacy, personal connections and play as they were to do with professional success theatre, celebrity and breaking news, this is a real, felt loss: sociability matters.
    1. Historically,researchers in diverse fields such as communication, sociology, law, and eco-nomics have argued that effective human systems organize people through acombination of hierarchical structures (e.g., bureaucracies), completely dis-tributed coordination mechanisms (e.g., markets), and social institutions ofvarious kinds (e.g., cultural norms). However, the rise of networked systemsand online platforms for collective intelligence has upended many of the as-sumptions and findings from this earlier research.

      Benkler argues that the process, motives, and cultural norms of online network-driven knowledge work are different than systems previously studied and should be re-evaluated.

    1. the internet may not be the most effective means of bringing work to an audience, particularly if you don’t already have some sort of access to an audience that will allow your work to be discovered

      Traditional scholarly publishing has a huge benefit of momentum - everyone is already there.

  56. Jul 2018
    1. Then I used Gephi, another free data analysis tool, to visualize the data as an entity-relationship graph. The coloured circles—called Nodes—represent Twitter accounts, and the intersecting lines—known as Edges—refer to Follow/Follower connections between accounts. The accounts are grouped into colour-coded community clusters based on the Modularity algorithm, which detects tightly interconnected groups. The size of each node is based on the number of connections that account has with others in the network.
    2. Using the open-source NodeXL tool, I collected and imported a complete list of accounts tweeting that exact phrase into a spreadsheet. From that list, I also gathered and imported an extended community of Twitter users, comprised of the friends and followers of each account. It was going to be an interesting test: if the slurs against Nemtsov were just a minor case of rumour-spreading, they probably wouldn't be coming from more than a few dozen users.
    1. The New Yorker’s Sasha Frere-Jones called Twitter a “self-cleaning oven,” suggesting that false information could be flagged and self-corrected almost immediately. We no longer had to wait 24 hours for a newspaper to issue a correction.
    1. Dissemination MechanismsFinally, we need to think about how this content is being disseminated. Some of it is being shared unwittingly by people on social media, clicking retweet without checking. Some of it is being amplified by journalists who are now under more pressure than ever to try and make sense and accurately report information emerging on the social web in real time. Some of it is being pushed out by loosely connected groups who are deliberately attempting to influence public opinion, and some of it is being disseminated as part of sophisticated disinformation campaigns, through bot networks and troll factories.
    1. The team found that the number of friends that pairs of individual have in common is strongly correlated with the strength of the tie between them, as measured in other ways. That’s regardless of whether people are linked by mobile-phone records or by social ties in rural Indian villages.
  57. Nov 2017
    1. Rather than framing everything at the course level, we should be deploying these technologies for the individual.26

      Obvious question: what about groups, communities, networks, and other supra-individual entities apart from the course/cohort model?

    1. As they stand, and especially with algorithmic reinforcement, “reactions” and “likes” are like megaphones for echo chambers and news outrage.

      This is something that's been nagging at me for the last couple of weeks.

      Does it all matter? Does that tweet, share, thumbs up, like really matter at all? If you/we/I share out of tweet of support, outrage, or indifference, does it really matter on the grand scale.

      Yes, I might have some likeminded individuals value it, read it, use it, share it. But, ultimately aren't we really just shouting into the echo chambers that have been built up for us thanks to these algorithms and networks? We're preaching to the choir.

      I'd like to think that open can/will combat this...but unsure.

      I think this is a post for Hybrid Ped or elsewhere. Lemme know if this resonates with anyone and you want to write it out.

  58. Oct 2017
    1. Another significant finding is that efforts of the membersof religious networks—in spite of their relatively closedcharacteristics—in terms of being at the center of a net-work and taking the brokerage role are, contrary to theliterature, highly developed

      This is an important finding that can help researchers better understand how this and similar religious networks operate.

    1. health-minded individuals discuss health problems with their peers and seek support fromexperts

      Absolutely. There are hardly any topics that are not discussed on the Twitter. The networks are created when the like-minded twitter users retweet each other’s tweets, creating a unique social network.

    1. addictive behavior

      I think this week's readings by Yang et al were really helpful in understanding how addictive behavior can spread through the network. A study by Cohen and Lemay (2007) suggested that there is a link between having less diverse social networks and getting influenced into drinking and smoking. It will be really interesting to see the results of this study. Especially, how the network dynamics might change since this is a egocentric network.

  59. Sep 2017
    1. mphasize its normative, shared,inter-generationally transmitted characteristics rather than itsheterogeneity, emergence, and practical application.

      I wonder about weak vs strong ties. This strikes me as a difference, i.e. heterogeneity. I also wonder about knowledge network analysis...maybe this is about how knowledge travels.

    1. ccording to this blog,

      When I read this blog, I thought about how knowledge comes to mature academics. When we are junior, we spend a great deal of time reading the specifics of articles and texts. Do we do the same as senior academics? Or does knowledge come to us via our networks? We talk to people at conferences or exchange ideas via email or other digital means? Just wondering if knowledge networks change over the life course of an academic?

    1. how they influence our lives, and how individual behavior is shaped by these networks.

      Networks are what sociologists talk about all the time but our methods don't fully 'see' them. We find relationships between variables--i.e. race and class--and then discuss how this relationship is due to social forces. Networks are the way in which social forces exert power!

    1. t is possible to identify a wide variety of actors who have contributed to ashift towards, and/or reproduced, academic capitalism:

      Each of these could be a network. You could compare the networks to see if they are structured differently as a way of trying to understand who is most responsible for the push towards Academic Capitalism.

    1. networks are everywhere,

      I think this is why they are hard to analyze...it is like trying to see and understand air. It is everywhere so it feels so normal and invisible. Networks, particularly human networks are the same. Humans have always been embedded in networks; we live, thrive and die in networks. They are another form of 'air'. The difference is that today, social media has made them more visible. We can now see them and analyze them in new ways. Hence, why this class is online :-)

    1. new framework for understanding issues ranging from democracy on the web to the vulnerability of the internet and the spread of deadly viruses

      Sometimes this new framework feels a bit overwhelming to me because it asks me to 'see' the world differently. I am use to seeing through discreet categories containing individuals; i.e. race, class and gender. SNA is asking me to see it through interconnections and links--the stuff behind the categories. Sometimes it feels like I am being asked to see 'air'; I know it is there, but it is all around me--ubiquitous--which makes it harder, and more intellectually challenging, to see.

  60. Aug 2017
    1. This is a very easy paper to follow, but it looks like their methodology is a simple way to improve performance on limited data. I'm curious how well this is reproduced elsewhere.

  61. May 2017
    1. Rather than selecting a single organization to lead the network, consider a spoke-and-hub or constellation model that empowers teams of organizations to act as “network hubs” for different sectors of the network. The best candidates for these hubs are intermediary organizations that act in the best interests of the network, allowing other network members to focus on their core mission and programmatic activities. Hub organizations play several roles. As conveners, they bring people together and build the field. As catalysts, they invest money and resources to get new ideas off the ground or help exciting projects to develop. As communicators, hub organizations enhance networks members’ ability to tell their story effectively and efficiently, internally and externally. As champions, hubs lift up the accomplishments of network actors, regionally, nationally, and internationally. And, as coordinators, hub organizations connect the dots, recommend priorities for the network, and connect those priorities to national resources.

      This could describe BCcampus - a hub organization that connects networks

  62. Apr 2017
    1. connects

      The description of iLife seems to echo the point made by Charles Taylor (as qtd. by Rickert): "Webs and networks can no more exist without me than can I without them."

    1. networkculture.Everythingusesandisused,andthereisnoclearboundarybetweentheoneandtheother.

      Re: my microresponse from 3/11 regarding Perelman, Burke, networks, community, and social fabric

    1. If we write that out as equations, we get:

      It would be easier to understand what are x and y and W here if the actual numbers were used, like 784, 10, 55000, etc. In this simple example there are 3 x and 3 y, which is misleading. In reality there are 784 x elements (for each pixel) and 55,000 such x arrays and only 10 y elements (for each digit) and then 55,000 of them.

  63. Mar 2017
    1. I have a lot of questions about whether any of the web-based tools we are using actually fit the mold of System A. I don’t often feel those spaces as convivial and natural. Behind the artifice of interface lay the reality of code. Is that structure humane? Is it open, sustainable, and regenerative? Does it feel good? Does the whole idea behind code generate System A or System B? I really don’t know.

      This is a really good key question..

    1. Then it was Maha's Birthday, why don't we sing 'Happy Birthday' I thought, - well why not?

      Distant Presence Friends

    2. during the week we had students reading my blog, seeing their snow hat from last winter being commented on by people all around the world and retweeted by Rihanna (a robot - I kept that quiet not to spoil the effect) on Twitter.

      Modeling reflective practice.

      Narrative connected

    3. First day in class, we had students chatting with a friend of mine working on a Ski Resort in Australia,

      Porous walls. Hybridization. Change narrative

    1. I met with my friend Marcin Kleban. After a twenty minute discussion we started a project of 40 language teachers and learners, he trusted me.. I met with my friend Blaise Ngandeu, I was able to learn about Nexus Analysis from my friend Maritta Riekki.

      connections attachment identification

    2. I wrote about this experience here in Swings and Roundabouts.

      Learning the power of open.

    1. So with social networking graphs, we will be able to get a better view on connections and their movement in the #rhizo14 constellation.

      Different methodology for research.

  64. Jan 2017
  65. Nov 2016
    1. Softmax分类器所做的就是最小化在估计分类概率(就是 Li=efyi/∑jefjLi=efyi/∑jefjL_i =e^{f_{y_i}}/\sum_je^{f_j})和“真实”分布之间的交叉熵.

      而这样的好处,就是如果样本误分的话,就会有一个非常大的梯度。而如果使用逻辑回归误分的越严重,算法收敛越慢。比如,\(t_i=1\) 而 \(y_i=0.0000001\),cost function 为 \(E=\frac{1}{2}(t-y)^2\) 那么,\(\frac{dE}{dw_i}=-(t-y)y(1-y)x_i\).

  66. Sep 2016
    1. A network perspective not only lays bare the various stakeholders with a vested social, economic, and political interest in what happens within schools and colleges, but also the ways agency for what happens within classrooms at my institution extends beyond the students and educators charged with constructing learning.

      Useful approach (reminiscent of ANT), especially if paired with a community-based approach.

  67. Jul 2016
    1. Page 158

      George Barnett, Edward think, and Mary Beth debus constructed a mathematical model of citation age to test this ordering using large data sets from each of the science citation index, social sciences citation index, and arts and humanities citation index published by the isi. In each of these three sets, the citation age of an average article reaches its peak in less than two years, with the Arts and Humanities peeking soonest parentheses 1.164 years close parentheses comma and the social sciences speaking latest parentheses 1.752 years close parentheses, contrary to expectations. The maximum proportion of citations did have the predicted ordering, with science the highest, and the Arts and Humanities the lowest. While the models presume that citation rates were stable over time a close examination of the data revealed that citation for article increase substantially over the time period of the study parentheses in science, from 12.14 per article in 1961 to 16 in 1986 God semi colon in the social sciences, from 7.07 in 1970 to 15.6 in 1986 semi colon no Citation for article data were given for the Arts and Humanities close parentheses.

    2. Page 158

      Half-Life studies are used to identify temporal variations in the use of literature by discipline most such studies indicate that the humanities have the longest citation half life and the Sciences the shortest with the social sciences in between. In other words, scientific articles reference the most recent Publications and Humanities articles the least recent ones.

    3. Pages 36 and 37

      Boardman discusses Merton. Lots of references here to series of citation and networks of relationships among Scholars the other references they make to each other's work

  68. May 2016
    1. When students see adults actually listening to them with respect, that is when they begin to realize they have a voice and can make a difference in their world.

      I hope this is true. And I love the idea that adults are that important to students. Still I wonder how this fits with the connected-learning notion that youth want to be heard and recognized by their peers. I suppose it isn't an either/or: some youth seek peer approval, others want to be heard by adults. When you post on an open social network, you never know who will respond.

  69. Apr 2016
    1. If, at the dawn of the web, I was to take a list of things the web would bring about and show them to a researcher, they might disagree on the level of interest people would have in things (what’s with the cat pictures, spaceman?) but there’d be little there to surprise them except for one item: the most used reference work in the world will be collaboratively maintained by a group of anonymous and pseudonymous volunteers as part of a self-organizing network.

      It would be nice if on this day, as we marvel about the rise of Wikipedia, we could turn some of our attention to the Wikipedias of the future. Where are opportunities for this mode of collaboration that we’ve missed? Why are we not confronted by more impossible things? How can we move from the electronic dreams of the 1970s to visions informed by the lessons of wiki and Wikipedia? Some people might think we’ve already done that. But I’m pretty sure we’re barely getting started.

  70. Jan 2016
    1. In this regard, it’s interesting to note that the viewing of TV programs at the time of their broadcast went up 20% with the advent of Twitter, indicating a desire to consume collaboratively. My ten year experience with social reading suggests that we might see a similar increase if long-form texts began appearing in platforms enabling people to gather in the margins with trusted friends and colleagues.
    1. Meanwhile, in almost exactly the same decades that the Internet arose and eventually evolved social computing, literary scholarship followed similar principles of decentralization to evolve cultural criticism.7

      Wow. This is the most interesting statement that I've read in a while. Wish I could pin an annotation...

      Really helps me justify my career arc, turning from literary criticism as a career to software "development."

  71. Nov 2015
    1. Finally children do as we do, not as we say. That gives us incentive to bring play back into our adult lives. We can shut off the TVs and take our children with us on outdoor adventures. We should get less exercise in the gym and more on hiking trails and basketball courts. We can also make work more playful: Businesses that do this are among the most successful. Seattle’s Pike Fish Market is a case in point. Workers throw fish to one another, engage the customers in repartee, and appear to have a grand time. Some companies, such as Google, have made play an important part of their corporate culture. Study after study has shown that when workers enjoy what they do and are well-rewarded and recognized for their contributions, they like and respect their employers and produce higher quality work. For example, when the Rohm and Hass Chemical company in Kentucky reorganized its workplace into self- regulating and self-rewarding teams, one study found that worker grievances and turnover declined, while plant safety and productivity improved.
    1. Emmons proposes a series of questions to help people recover from difficult experiences, which I’ve adapted for the workplace: What lessons did the experience teach us? Can we find ways to be thankful for what happened to us now, even though we were not at the time it happened? What ability did the experience draw out of us that surprised us? Are there ways we have become a better workplace because of it? Has the experience removed an obstacle that previously prevented us from feeling grateful?
    2. Research points to the notion that gratitude might have positive effects on transforming conflicts, which can benefit the organization and working relationships. How do you do that? It starts with the one charged with mediating the conflict: For example, a supervisor with two bickering employees might open a meeting by expressing sincere appreciation of both parties. Throughout the process, that person should never miss an opportunity to say “thank you.” The research says this attitude of gratitude will have a positive feedback effect, even if results aren’t obvious right away.
    3. Giving creates gratitude, but giving can also be a good way to express gratitude, especially if the person in question is shy. You can say “thanks” by taking on scut work, lending a parking space, or giving a day off. These kinds of non-monetary gifts can lead to more trust in working relationships, if it’s reciprocal, sincere, and altruistically motivated.
    4. Employees need to hear “thank you” from the boss first. That’s because expressing gratitude can make some people feel unsafe, particularly in a workplace with a history of ingratitude.
    5. The benefits of gratitude go beyond a sense of self-worth, self-efficacy, and trust between employees. When Greater Good Science Center Science Director Emiliana Simon-Thomas analyzed data from our interactive gratitude journal Thnx4.org, she found the greater the number of gratitude experiences people had on a given day, the better they felt. People who kept at it for at least two weeks showed significantly increased happiness, greater satisfaction with life, and higher resilience to stress; this group even reported fewer headaches and illnesses.
    6. Gratitude is a non-monetary way to support those non-monetary motivations. “Thank you” doesn’t cost a dime, and it has measurably beneficial effects. In a series of four experiments, psychologists Adam Grant and Francesca Gino found that “thank you” from a supervisor gave people a strong sense of both self-worth and self-efficacy. The Grant and Gino study also reveals that the expression of gratitude has a spillover effect: Individuals become more trusting with each other, and more likely to help each other out.
    1. Mbembe points out that often thefunction of awarding infrastructural projects has far more to do with gaining access to governmentcontracts and rewarding patron-client networks than it has to do with their technical function.This is why roads disappear, factories are built but never operated, and bridges go to nowhere.

      Sounds like scheming for political gains.. This is easy to see in the work place or society when one befriends another or joins a certain group for political/hierarchal benefits rather than for the pure purpose of the action. African societies cannot be the only ones who follow these functional implementations of these infrastructural projects.

  72. Oct 2015
    1. when we set goals that are reallynon-zero that have to do with not only honoring our own interests, but also advancing thewelfare and interests of others, friends, family members, and social groups, that kindof a goal, that non-zero goal that really incorporates others interests with the greatergood is associated with greater success, career, and happiness.
    1. hospitable network means that information can flow relatively easily between nodes

      I like this definition. I am really interested in riffing on a Derridian notion of hospitality, this kind of networked hospitality, food networks, and the hospitality industry. There are a couple of things that I'm wondering at this point: what constitutes "information" and what constitutes "ease." I'm thinking about environments that are hospitable to certain microorganisms, but not others. So one kind of bacteria might move through with ease, while another might be killed off.

    1. a web so conceptually consistent, socially relevant and technically expandable

      We've done relatively well with the first two. "Technically expandable" is the one in danger.

      If we continue to build "social networks" as singular dead end cul-de-sacs, we leave no exit available to those who follow.

      The Web we want is expandable beyond the reaches of what we currently know, the economies we operate within, and the future we can currently conceive.

  73. Sep 2015
    1. A study by James Fowler of the University of California, San Diego, and Nicholas Christakis of Harvard, published in the Proceedings of the National Academy of Science, shows that when one person behaves generously, it inspires observers to behave generously later, toward different people. In fact, the researchers found that altruism could spread by three degrees—from person to person to person to person. “As a result,” they write, “each person in a network can influence dozens or even hundreds of people, some of whom he or she does not know and has not met.”