- Jul 2024
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en.wikipedia.org en.wikipedia.org
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https://en.wikipedia.org/wiki/Matthew_effect
The Matthew effect of accumulated advantage, sometimes called the Matthew principle, is the tendency of individuals to accrue social or economic success in proportion to their initial level of popularity, friends, and wealth. It is sometimes summarized by the adage or platitude "the rich get richer and the poor get poorer". The term was coined by sociologists Robert K. Merton and Harriet Zuckerman in 1968 and takes its name from the Parable of the Talents in the biblical Gospel of Matthew.
related somehow to the [[Lindy effect]]?
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- May 2024
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www.theguardian.com www.theguardian.com
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Der Bezos Earth Fund wird bis zum Ende des Jahrzehnts 10 Milliarden Dollar für den Kampf gegen die Klima und die Biodiversitätskrise zur Verfügung stellen. Die Mittel des Fonds geben ihm enormen Einfluss. Viele in der NGOs Szene sehen die Politik des Fonds als Gefährdung für die Unabhängigkeit der von ihm geförderten Organisationen. Der Guardian berichtet anlässlich einer Preisverleihung kritisch vor allem über das Engagement des Fonds für CO2 Kompensationen. https://www.theguardian.com/environment/article/2024/may/20/jeff-bezos-earth-fund-carbon-offsets-climate-sector-uneasy-aoe
Tags
- Science Based Targets Initiative
- Luiz Fernando do Amaral
- John Kerry
- Zac Goldsmith
- Bezos Earth fund
- Wanjira Mathai
- Carbon Market Watch
- Paul Bodnar
- Go for Impact
- Conservation International
- Carbon offsets
- Auszeichnung des Bezos Earth Fund durch Conservation International
- Climate Action Network International
- Stephan Singer
- Andrew Steer
- Sam Van den Plas
- by: Patrick Greenfield
- Iván Duque
- Holger Hoffmann-Riem
Annotators
URL
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- Jun 2023
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www.sciencedirect.com www.sciencedirect.com
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Issues of Upgrading Study Courses and Use of Semantic Networks as a Means for Their Evaluation
Penggunaan Jejaring Semantik sebagai metode evaluasi Mata Kuliah.
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- May 2023
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- Dec 2022
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agupubs.onlinelibrary.wiley.com agupubs.onlinelibrary.wiley.com
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the Earth Commission's report will be used to underpin the development of science-based targets for business and cities by SBTN.
!- relationship between : Earth Commission and Science-Based Targets Network (SBTN) - Earth Commission results will be used to develop Science-Based targets - for businesses and cities
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earthcommission.org earthcommission.org
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nto the work of the Science-Based Targets Network
!- relationship with : Science-Based Targets Network
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link.springer.com link.springer.com
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In this work, we develop the “Multi-Agent, Multi-Attitude” (MAMA) model which incorporates several key factors of attitude diffusion: (1) multiple, interacting attitudes; (2) social influence between individuals; and (3) media influence. All three components have strong support from the social science community.
several key factors of attitude diffusion: 1. multiple, interacting attitudes 2. social influence between individuals 3. media influence
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- May 2022
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www.noemamag.com www.noemamag.com
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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?
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- Feb 2022
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psyarxiv.com psyarxiv.com
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Horita, Y., & Yamazaki, M. (2022). Generalized and behavioral trust: Correlation with nominating close friends in a social network. PsyArXiv. https://doi.org/10.31234/osf.io/xu8k3
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- Jan 2022
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arxiv.org arxiv.org
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Vega-Oliveros, D. A., Grande, H. L. C., Iannelli, F., & Vazquez, F. (2021). Bi-layer voter model: Modeling intolerant/tolerant positions and bots in opinion dynamics. The European Physical Journal Special Topics, 230(14–15), 2875–2886. https://doi.org/10.1140/epjs/s11734-021-00151-8
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- Nov 2021
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link.aps.org link.aps.org
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Kumar, A., Chowdhary, S., Capraro, V., & Perc, M. (2021). Evolution of honesty in higher-order social networks. Physical Review E, 104(5), 054308. https://doi.org/10.1103/PhysRevE.104.054308
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Kwiek, M. (2021). The Globalization of Science: The Increasing Power of Individual Scientists. MetaArXiv. https://doi.org/10.31222/osf.io/gj4aq
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- Oct 2021
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www.mdpi.com www.mdpi.com
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Mazumdar, S., & Thakker, D. (2020). Citizen Science on Twitter: Using Data Analytics to Understand Conversations and Networks. Future Internet, 12(12), 210. https://doi.org/10.3390/fi12120210
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- Sep 2021
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psyarxiv.com psyarxiv.com
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Marley, J., Blanche, M., Bulut, A., Bamber, L., McVay, S., Adeyanju, A., & Worsfold, S. (2021). The Digital Resilience Network [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/m8dbc
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- Aug 2021
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thebulletin.org thebulletin.org
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We’ve analyzed thousands of COVID-19 misinformation narratives. Here are six regional takeaways—Bulletin of the Atomic Scientists. (n.d.). Retrieved August 1, 2021, from https://thebulletin.org/2021/06/weve-analyzed-thousands-of-covid-19-misinformation-narratives-here-are-six-regional-takeaways/
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- Jul 2021
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twitter.com twitter.comTwitter1
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Leah Keating on Twitter: “This work with @DavidJPOS and @gleesonj is now on arXiv (https://t.co/hxjZnCmKcM): ‘A multi-type branching process method for modelling complex contagion on clustered networks’ Here is a quick overview of our paper: (1/6) https://t.co/3jQ2flhk71” / Twitter. (n.d.). Retrieved July 23, 2021, from https://twitter.com/leahakeating/status/1418150117106978816
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- Jun 2021
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arxiv.org arxiv.org
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Persoon, P. G. J. (2021). Cumulative structure and path length in networks of knowledge. ArXiv:2106.10480 [Physics]. http://arxiv.org/abs/2106.10480
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arxiv.org arxiv.org
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Qian, Z.-Y., Yuan, C., Zhou, J., Chen, S.-M., & Nie, S. (2021). Optimal control of complex networks with conformity behavior. ArXiv:2106.10607 [Physics]. http://arxiv.org/abs/2106.10607
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- May 2021
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psyarxiv.com psyarxiv.com
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Agarwal, A. (2021). Ripple Effect of a Pandemic: Analysis of the Psychological Stress Landscape during COVID19. PsyArXiv. https://doi.org/10.31234/osf.io/dm5x2
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psyarxiv.com psyarxiv.com
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Agarwal, A. (2021). The Accidental Checkmate: Understanding the Intent behind sharing Misinformation on Social Media. PsyArXiv. https://doi.org/10.31234/osf.io/kwu58
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www.nature.com www.nature.comNetworks1
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Network science is now a mature research field, whose growth was catalysed by the introduction of the ‘small world’ network model in 1998. Networks give mathematical descriptions of systems containing containing many interacting components, including power grids, neuronal networks and ecosystems. This collection brings together selected research, comments and review articles on how networks are structured (Layers & structure); how networks can describe healthy and disordered systems (Brain & disorders); how dynamics unfold on networks (Dynamics & spread); and community structures and resilience in networks (Community & resilience).
This is a great looking collection of articles on network science.
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- Mar 2021
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Karimi, Fariba, and Petter Holme. ‘A Temporal Network Version of Watts’s Cascade Model’. ArXiv:2103.13604 [Physics], 25 March 2021. http://arxiv.org/abs/2103.13604.
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Devriendt, K., Martin-Gutierrez, S., & Lambiotte, R. (2020). Variance and covariance of distributions on graphs. ArXiv:2008.09155 [Physics, Stat]. http://arxiv.org/abs/2008.09155
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arxiv.org arxiv.org
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Di Lauro, F., Berthouze, L., Dorey, M. D., Miller, J. C., & Kiss, I. Z. (2020). The impact of network properties and mixing on control measures and disease-induced herd immunity in epidemic models: A mean-field model perspective. ArXiv:2007.06975 [Physics, q-Bio]. http://arxiv.org/abs/2007.06975
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Wang, Xiangrong, Alejandro Tejedor, Yi Wang, and Yamir Moreno. ‘Unique Superdiffusion Induced by Directionality in Multiplex Networks’. ArXiv:2011.00991 [Physics], 2 November 2020. http://arxiv.org/abs/2011.00991.
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arxiv.org arxiv.org
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Hota, Ashish R., Tanya Sneh, and Kavish Gupta. ‘Impacts of Game-Theoretic Activation on Epidemic Spread over Dynamical Networks’. ArXiv:2011.00445 [Physics], 1 November 2020. http://arxiv.org/abs/2011.00445.
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psyarxiv.com psyarxiv.com
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Heeren, A., HANSEEUW, B., Cougnon, L., & Lits, G. (2021, March 11). Excessive Worrying as the Driving Force of Anxiety During the First COVID-19 Lockdown-Phase in Belgium. https://doi.org/10.31234/osf.io/b34aj
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- Feb 2021
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link.aps.org link.aps.org
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Wang, X., Sirianni, A. D., Tang, S., Zheng, Z., & Fu, F. (2020). Public Discourse and Social Network Echo Chambers Driven by Socio-Cognitive Biases. Physical Review X, 10(4), 041042. https://doi.org/10.1103/PhysRevX.10.041042
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www.wired.com www.wired.com
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Ogbunu, B. C. (2020, October 27). The Science That Spans #MeToo, Memes, and Covid-19. Wired. https://www.wired.com/story/the-science-that-spans-metoo-memes-and-covid-19/
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- Oct 2020
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appliednetsci.springeropen.com appliednetsci.springeropen.com
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First, I will focus in these larger groups because reviews that transcend the boundary between the social and natural sciences are rare, but I believe them to be valuable. One such review is Borgatti et al. (2009), which compares the network science of natural and social sciences arriving at a similar conclusion to the one I arrived.
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For instance, in the study of mobile phone networks, the frequency and length of interactions has often been used as measures of link weight (Onnela et al. 2007), (Hidalgo and Rodriguez-Sickert 1008), (Miritello et al. 2011).
And they probably shouldn't because typically different levels of people are making these decisions. Studio brass and producers typically have more to say about the lead roles and don't care as much about the smaller ones which are overseen by casting directors or sometimes the producers. The only person who has oversight of all of them is the director, and even then they may quit caring at some point.
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heterogeneous networks have been found to be effective promoters of the evolution of cooperation, since there are advantages to being a cooperator when you are a hub, and hubs tend to stabilize networks in equilibriums where levels of cooperation are high (Ohtsuki et al. 2006), (Pacheco et al. 2006), (Lieberman et al. 2005), (Santos and Pacheco 2005).
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inst-fs-iad-prod.inscloudgate.net inst-fs-iad-prod.inscloudgate.net
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His weak-tie networks had been politically activated
This makes me wonder if she's cited Mark Granovetter or any of similar sociologists yet?
Apparently she did in footnote 32 in chapter 1. Ha!
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Only a segment of the population needs to be connected digitally to affect the entire environment. In Egypt in 2011, only 25 percent of the population of the country was on-line, with a smaller portion of those on Facebook, but these people still managed to change the wholesale public discussion, including conversa-tions among people who had never been on the site.
There's some definite connection to this to network theory of those like Stuart Kaufmann. You don't need every node to be directly connected to create a robust network, particularly when there are other layers--here interpersonal connections, cellular, etc.
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scripting.com scripting.com
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Anyone who's dealt with networks knows that the network knows more than the individual."
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- Sep 2020
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psyarxiv.com psyarxiv.com
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Lee, Hyeon-seung, Derek Dean, Tatiana Baxter, Taylor Griffith, and Sohee Park. ‘Deterioration of Mental Health despite Successful Control of the COVID-19 Pandemic in South Korea’. Preprint. PsyArXiv, 30 August 2020. https://doi.org/10.31234/osf.io/s7qj8.
Tags
- South Korea
- psychosis-risk
- is:preprint
- anxiety
- nationwide lockdown
- behavioural science
- loneliness
- lang:en
- psychological outcome
- crisis
- social factors
- physical health
- social distancing
- demographic
- females
- COVID-19
- public health
- general population
- social network
- depression
- mental health
- stress
Annotators
URL
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r/BehSciAsk—Integrating Behavioural Science into Epidimiology. (n.d.). Reddit. Retrieved June 27, 2020, from https://www.reddit.com/r/BehSciAsk/comments/hg501h/integrating_behavioural_science_into_epidimiology/
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- Aug 2020
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link.aps.org link.aps.org
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Velásquez-Rojas, F., Ventura, P. C., Connaughton, C., Moreno, Y., Rodrigues, F. A., & Vazquez, F. (2020). Disease and information spreading at different speeds in multiplex networks. Physical Review E, 102(2), 022312. https://doi.org/10.1103/PhysRevE.102.022312
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Khanam, K. Z., Srivastava, G., & Mago, V. (2020). The Homophily Principle in Social Network Analysis. ArXiv:2008.10383 [Physics]. http://arxiv.org/abs/2008.10383
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www.nature.com www.nature.com
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Shahal, S., Wurzberg, A., Sibony, I., Duadi, H., Shniderman, E., Weymouth, D., Davidson, N., & Fridman, M. (2020). Synchronization of complex human networks. Nature Communications, 11(1), 3854. https://doi.org/10.1038/s41467-020-17540-7
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journals.plos.org journals.plos.org
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Aleta, A., Arruda, G. F. de, & Moreno, Y. (2020). Data-driven contact structures: From homogeneous mixing to multilayer networks. PLOS Computational Biology, 16(7), e1008035. https://doi.org/10.1371/journal.pcbi.1008035
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- Jul 2020
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www.youtube.com www.youtube.comYouTube1
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Supporting Open Science Data Curation, Preservation, and Access by Libraries. (2020, June 25). https://www.youtube.com/watch?v=SbmGWHpzAHs&feature=youtu.be
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www.sciencedirect.com www.sciencedirect.com
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Fontana, M., Iori, M., Montobbio, F., & Sinatra, R. (2020). New and atypical combinations: An assessment of novelty and interdisciplinarity. Research Policy, 49(7), 104063. https://doi.org/10.1016/j.respol.2020.104063
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- Jun 2020
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zoom.us zoom.us
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Welcome! You are invited to join a webinar: Supporting Open Science Data Curation, Preservation, and Access by Libraries. After registering, you will receive a confirmation email about joining the webinar. (n.d.). Zoom Video. Retrieved June 28, 2020, from https://zoom.us/webinar/register/2615905946283/WN_W6dYUXQFTqGQjGAZPRB74w
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psyarxiv.com psyarxiv.com
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Borsboom, D., Blanken, T., Dablander, F., Tanis, C., van Harreveld, F., & van Mieghem, P. (2020). BECON methodology [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/53ey9
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www.bristol.ac.uk www.bristol.ac.uk
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UKRN position on covid 19 research. (2020 May 01). School of Psychological Science | University of Bristol. http://www.bristol.ac.uk/psychology/research/ukrn/news/2020/ukrn-position-on-covid-19-research.html
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scisight.apps.allenai.org scisight.apps.allenai.orgAbout1
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Jazayeri, A., & Yang, C. C. (2020). Motif Discovery Algorithms in Static and Temporal Networks: A Survey. ArXiv:2005.09721 [Physics]. http://arxiv.org/abs/2005.09721
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- May 2020
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psyarxiv.com psyarxiv.com
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Blanchard, M. A., & Heeren, A. (2020). Why We Should Move from Reductionism and Embrace a Network Approach to Parental Burnout? [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/y34cq
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arxiv.org arxiv.org
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Katz, D. M., Coupette, C., Beckedorf, J., & Hartung, D. (2020). Complex Societies and the Growth of the Law. ArXiv:2005.07646 [Physics]. http://arxiv.org/abs/2005.07646
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www.nature.com www.nature.com
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Zdeborová, L. (2020). Understanding deep learning is also a job for physicists. Nature Physics, 1–3. https://doi.org/10.1038/s41567-020-0929-2
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Johnson, N.F., Velásquez, N., Restrepo, N.J. et al. The online competition between pro- and anti-vaccination views. Nature (2020). https://doi.org/10.1038/s41586-020-2281-1
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Almaatouq, A., Noriega-Campero, A., Alotaibi, A., Krafft, P. M., Moussaid, M., & Pentland, A. (2020). Adaptive social networks promote the wisdom of crowds. Proceedings of the National Academy of Sciences, 201917687. https://doi.org/10.1073/pnas.1917687117
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Hope, T., Borchardt, J., Portenoy, J., Vasan, K., & West, J. (2020, May 6). Exploring the COVID-19 network of scientific research with SciSight. Medium. https://medium.com/ai2-blog/exploring-the-covid-19-network-of-scientific-research-with-scisight-f75373320a8c
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Pinto, S. F., & Ferreira, R. S. (2020). Analyzing course programmes using complex networks. ArXiv:2005.00906 [Physics]. http://arxiv.org/abs/2005.00906
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coviz.apps.allenai.org coviz.apps.allenai.orgAbout1
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About. (n.d.). Retrieved May 6, 2020, from https://coviz.apps.allenai.org/
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Vasiliauskaite, V., & Rosas, F. E. (2020). Understanding complexity via network theory: A gentle introduction. ArXiv:2004.14845 [Physics]. http://arxiv.org/abs/2004.14845
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psyarxiv.com psyarxiv.com
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Segovia-Martín, J., & Tamariz, M. (2020, May 5). Testing early and late connectivity dynamics in the lab: an experiment using 4-agent micro-societies. https://doi.org/10.31234/osf.io/nuf78
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- Apr 2020
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Chaves, M. S., Mattos, T. G., & Atman, A. P. F. (2020). Characterizing network topology using first-passage analysis. Physical Review E, 101(4), 042123. https://doi.org/10.1103/PhysRevE.101.042123
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trello.com trello.com
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Collective Intelligence and COVID-19 | Trello. (n.d.). Retrieved April 20, 2020, from https://trello.com/b/STdgEhvX/collective-intelligence-and-covid-19
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