58 Matching Annotations
  1. Jan 2019
    1. computational models

      A computational model is a mathematical model in computational science that requires extensive computational resources to study the behavior of a complex system by computer simulation.

  2. Apr 2017
    1. ERGMs are the primary building blocks of statistically testing network structural effects. Increasingly, researchers are not only interested in describing an ego or complete network but rather in whether an observed network property is significant. ERGMs [Page 179]generate (random) networks derived from features of the observed network, which provide a way to compare the observed and simulated networks. Statistical analysis is then conducted to test whether the ties in the simulated network match those generated by the simulations.

      They provide a base for comparison similar to a control group?

    2. artifacts

      Maybe I missed something in our previous readings/videos, but can someone explain to me what is meant by the term "artifacts"?

  3. Mar 2017
    1. Brokerage

      This whole concept is a huge part of what I want to get out of my data set! This is exciting and also terrifying because I will have to figure out how to actually get these measurements....

    2. Ego actors can be individual persons, groups, or even some larger entity

      I had not thought of that until they spelled this out. that actually makes a lot of sense.

    3. “agent” in relations across groups

      I think this also applies in financial sectors, right? good explanantion linking centrality and structural holes; I also like the breakdown in the bottom paragraph with five specific roles shown in fig. 7.7

    4. constraint, extends the egocentric network density measure to include more information about the structural pattern of relations among ego's alters.

      density + pattern of relations among alters = constraints

    5. eigenvector centrality (Bonacich, 1972), entropy (Tutzauer, 2007), power (Bonacich, 1987), Katz centrality (1953), and random-walk centrality

      wow. entropy sounds awesome. I want to be able to use this in my analysis just because it sounds so cool and I think it was one of the few concepts that really made sense when I was introduced to entropy in physics and chemistry!

    6. (1) the topography of an ego's network and (2) the composition of that network, including the attributes of the alters to whom ego is connected.

      focus of questions that try to examine individual entities across different networks and/or patterns of interaction within groups.

    7. an individual's (ego) connections with others (alters) provides access to some instrumental (e.g., advice) or expressive (e.g., support) resource that may, in turn, be beneficia

      ego's social capital in the hood

    1. How centralized is the network?To what extent is there a small number of highly central nodes?

      It is easy to see why node level centrality and network-level centralization are mistakenly treated as the same. This is my third or fourth time through this and I'm still not completely clear.

    1. top-down” and “bottom-up

      These are two terms that are commonly used in literacy in regards to acquisition of emerging readers and two different theories as to which is the best way to help young readers become successful in reading. Spoiler - bottom-up won...

    2. cut-off value

      Although I already determined I needed to add a cut-off value to my data in order to make some of it meaningful it's reassuring to read about here.

    3. Equivalence, in general, refers to actors who occupy the same position.

      Nice definition

    4. equivalence

      I'm interested to learn more about this.

    5. top-down

      In ELT, "Top Down" refers to getting learners to make predictions about reading/listening activities before they actually do them. For example showing students a magazine article and asking to predict what they the article might be about, based on pictures or titles. This seems to be similar here, looking at readily available information without getting into the details first.

  4. Feb 2017
    1. “keep things together.”

      so is this directly correlated to structural cohesiveness?

    2. connected subgraph in which [Page 114]there is a path between all pairs of nodes

      component definition; the graphic from Bodong's video clip is helpful in getting a (mental) picture of this definition.

    1. Which structural properties of the complete network might be of interest to you?
      1. Would it be right to say that a decentralized network would mean that more actors have a say in the evaluation process?
      2. Could a measure like high transitivity indicate more equitable practices in evaluation?
      3. Would high reciprocity mean that there was healthier communication (not just directed "at" the new teachers, but feedback loops and supportive avenues of communication)?
      4. And finally, what would high density scores indicate -- that resources are more accessible and basically better connections overall - so a more well-connected network, with fewer actors in isolated or peripheral positions?
    2. relations are focused on one or a small set of actors

      centralization: power in the hands of a few

    3. “Small worlds” are those that paradoxically have a low average path length but high clustering.

      small world phenomenon

    4. “group together” into pockets of dense connectivity

      clustering: tendency towards shared interactions based on homophily

    5. hierarchy, equality, and exclusivity

      examples of forms of relationships (16 dif kinds according to Holland&Linehardt, 1979)

    6. reciprocity is reported as the proportion of reciprocated ties in the network. Therefore, values closer to 1.0 indicate higher reciprocity

      reciprocity: appears in many studies and seems highly relevant in educational fields

    7. conceptual level, it influences the structure of relations

      size: affects structure of relations, reflects network's boundary, and measure of number of nodes in network

    8. dichotomized

      How were the data changed from 1,2,3 to 1,0?

    9. structural holes (one actor connected to two others who, in turn, are not connected to each other)

      From my understanding of this, structural holes differ from triads since triads generally indicate that all three actors are connected in some way. Is this correct?

    10. effective density,

      I like the explanation of effective density. I think it will be useful for my own "potential" research

    11. network's topography
    1. snowball sampling

      Interesting. I am unfamiliar with this type of sampling. I have heard of it before, but I have not seen many studies that utilize this sampling approach.

    2. K-core, discussed in more detail in the next chapter, is a subset of actors that has ties with at least K other actors

      useful in "empirically locating network boundaries" but not used widely

    3. positional approach generates a set of actors that occupy a similar position in some social structure. Each actor, however, need not be directly connected to every other actor

      positional different from relational because there could be structural holes

    1. mapping and measuring of relationships and flows between people, groups, organizations, computers, Web sites, and other information/knowledge processing entities

      I like this definition of SNA

    1. Cultural capital theory

      This is my first time learning about cultural capital. It makes sense so I am surprised that I have not come across it before.

    2. human capital theory

      Human Capital is a big deal in the field of Human Resource Development. Supporters of the human capital theory argue that humans are the best asset of any organization. It's nice to see the theory mentioned in literature outside of business and HR fields.

    3. social closure vs. structural holes

      While I can make an educated guess as to what these terms mean, I am not very familiar with them.

    4. “Social capital [Page 218]is defined by its function. It is not a single entity, but a variety of different entities having two characteristics in common: They all consist of some aspect of social structure, and they facilitate certain actions of the individuals who are within the structure” (Coleman, 1990, p. 302).

      This is the easiest definition to work with, in my opinion!

    5. this classical theory of capital consists of two distinct elements: value that is generated and pocketed by the capitalists and investment on the part of capitalists with expected returns in the marketplace. Therefore, capital is a surplus value and represents an investment in expected returns (Lin, 2001a).

      I find this interesting because it is being described as "classical theory of capital"... even though it is still used to this day as the dominant definition of capital, and fits well within contemporary applications of capital theory, including social capital theory.

    1. These structural relations—unlike “fixed” attributes such as gender, race, and age that do not vary in different contexts—exist only at a specific time–place and either disappear or recede when actors are elsewhere.

      Patterned social relations are structural relations that exist only at a specific time-place and either disappear or recede when actors are elsewhere. Relations vary significantly across contexts and condition the social actors apart from their attributes.

  5. Jan 2017
    1. directed graph. Conversely, an undirected graph

      These graphs are powerful tools, very similar to concept maps.

    2. Multiplex data, discussed later in this chapter, are those network data that measure more than one kind of relation, which most contemporary network studies incorporate.
    3. core-periphery structure:


    4. arcs or edges

      Here is a better explanation of the SNA terms Arcs and Edges. Arcs represent those relations that are directed from one student to another, meaning that the friendship nomination has not necessarily been reciprocated. Edges, on the other hand, are those lines that do not have arrowheads (since friendships are directed, there are no edges in Figure 3.1), which are appropriate when the relation is by definition reciprocated (e.g., “studies with”).

    5. arcs.

      I am unfamiliar with the term "arc" in this context since I am unsure what is meant by "directed lines".

    6. sociometry

      This has come up a couple times now with no definition (that I've seen), so I looked it up on dictionary.com: the measurement of attitudes of social acceptance or rejection through expressed preferences among members of a social grouping

    1. relational thinking

      I think this will occur a lot in SNA

    2. nductive modeling strategies

      This is a really great SNA term/phrase. Generating big ideas from small observations is a nice description of SNA. It reminds me of the grounded theory approach in qualitative research.

    3. Diffusion

      I really appreciate how the term diffusion is used in SNA to describe the natural spread of knowledge through a network.

    4. CONCOR (for CONvergence of iterated CORrelations)

      I'm curious about this concept, as I suspect it's been the basis for other technologies we use today.

    5. therapeutic techniques

      I think the idea of research as therapy is really interesting. Beyond that, though, a major concept within LT is the idea of bringing theory into practice; this seems like a different application of that process.

    6. phenomenological individualism

      Is this ontology inherently incompatible with relational realism? If different educational researchers operate under each ontological paradigm and describe the same scenario in unique ways, what value would each bring to our understanding of the world? Is one inherently more valuable than the other?

    7. It is a comprehensive paradigmatic way of taking social structure seriously by studying directly how patterns of ties allocate resources in a social system”

      SNA is not just a methodology, rather an informed perspective that should affect every area of research.

    8. Fourth, relational realism is the doctrine that interactions and social ties constitute the central existence of social life

      This seems to somewhat reflect a similar evolution in education theory (not directly, but somewhat), tying into the newer theory of connectivism, as I see it. Though this doesn't necessary indicate a progression (maybe though?)

    1. Groups

      A collection of actors on which ties are to be measured.

    2. Relation

      The collection of the ties between actors, taken as a whole.

    3. Ties

      Ties are connections between actors

    4. Finally, also consider that the chance of any given teacher enforcing the policy increases with the number of others who enforce it. Under what conditions will [Page 15]enforcement of the policy spread to a nontrivial portion of the network? What percentage of teachers will ultimately enforce this policy? How does this depend on the network's structure and the individual's position in that structure as well as one's own individual attributes?

      Diffusion--as I understand it--is tracking how a particular phenomenon moves through a social network. This reminds me of a TEDTalk on how to start a movement: https://www.youtube.com/watch?v=RXMnDG3QzxE

    1. understanding the antecedents and consequences of network phenomena

      I am curious about a few things packed in this sentence: network phenomena, and their antecedents and consequences.