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1. Stickiness- the message must make an impact- the disease must be powerful- syphilis occurred in more latent form earlier in century but didnt become epidemic 2. Law of Few- power laws- few very sexually active people get disease cause it to become epidemic 3. Power of Context- how alter behavior based on context- people are very sensitive to the environment- stabbing of Kitty Genovese with 30 wittnesses -mid 1990s Baltimore houses razed and cutback on medical spending lead to syphilisepidemic |
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when nodes with friends take on the same attributes/join the same organizations |
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The model for the internet. The strongly connected component in the middle has sites that have out-links (link to it) but not in-links (are not linked to) and also a "out" part that is the opposite. There are tubes that can reach in and out pages but are not connected to the SCC. Also there are tendrils that can reach either the in or the out pages
-also many employees depend on a small subset but not eachother |
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Simplest model of Contagion First wave(=k)- carrier meets k people, some infected Second wave(=k*k people)- 1st wave meets k new people and pass disease with prob=p Has basic reproductive number- expected number of people infected by an individual (R=pk)>1 necessary for disease to not die out |
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Where individuals do not offer help in an emergency when other are present. From the power of context and Kitty Genovese where thirty wittnesses observed her getting mugged and stabbed but expected the other people to call the cops then no one did |
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The probability of a tie between two nodes being formed increases as the number of common friends (groups) increases. Focal closure is where 2 people in an organization become friends Membership closure is where a friend of some one become involved in an organization that the other is involved in Triadic Closure |
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internet based computing whereby shared resources, software and information are provided to computers and other devices on-demand -Salesforce.com= Matt O'Connor pay as you go, multi-tennant, Auto upgrades, faster, cheaper, real-time collaboration, no software |
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The spread of a new behavior can stall when it reaches a cluster (tightly-knit group) -homophily as a barrier to diffusion -cluster of density p is such that each node has p fraction of neighbors in set Set of all nodes is cluster density=1 Union of 2 clusters with Density p has density p Running into dense cluster is only thing that causes a cascade to stop Complete cascade only if no cluster with a critical density, q |
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Why attributes change based on links and why links change based on attributes -ex Substance abuse, sports, and friendship When friends have similar (alterable) characteristics because they develop them together |
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Cognitive Social Structure |
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Everyone in a network's perceptions of what links exist in a network-1987 Krackhardt- CSS have more info than normal social structure, no "objective relations |
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Captures which inlinks each actor reports to have (who trusts them). -This shows whether people feel needed/involved in a network (bc ppl come to them to talk/get advice) |
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aggregated over the outlinks each actor claims to have (to whom they go for advice) |
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people within a network (employees) who talk about (work) issues regularly -what is regularly? |
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Connected subset of network nodes and links |
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Connected subset of network nodes and links |
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As more people do something there is more implicit social pressure to conform. -eg Milgram's Sky starers -in contrast to Rational Contagion (crowded bar vs empty bar) where something is contageous due to its info effects or direct-benefit effects |
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The extent to which two variables are related/codetermined -indicates a predictive relationship |
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Where copying others' actions has direct payoffs - network effects= where the value of something is proportional to the number of people that use it (Fax, Facebook) |
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Surveys- collect perception of interaction list of names v free recall Ratings v complete rankings -Observations- face-face, listserv... -Interviews- face-face, telephone, Snowball Sampling -Indirect data- archival records- more reliable -Experiments |
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Existing ties drive creation and destruction of attributes
Depends on relative advantages, observability, compatibility with social system, Trialability (decrease risk by adopting gradually) - homophily can be barrier |
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Disciplinary Science Model |
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where Journals in one disclipline cite journals in another- shows how disciplines are linked |
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Edge, stars, and triangle |
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star is an actor highly central to network |
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Maximum Liklihood estimation |
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Choose theta such that the observed network configuration is the most likely given L=e^(g(y)*theta^T)/k(theta) |
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xsub(n+1)=xsub(n)-f'(xsub(n))/f"(xsub(n)) |
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Markov Chain Monte Carlo MLE |
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1.Start with guess for theta 2.Create Network using ERGM simulations 3.calculate log-ratio of liklihoog function 4. Use Newton-Rhapson to find better theta 5.Update theta, repeat 2-4 |
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A retrieves info on X from B if others in A's comm network also do so |
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Theory of Transactive Memory |
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Good things happen to teams where 1.members know (who knows)who knows what - reduces workload and redundancy 2.high knowledge differentiation- expertise in different areas |
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ties are more likely to form to create a balanced network |
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Theory of social exchange |
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If A gets info X from B, then B is more likely to get info Y from A |
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A retrieves X from B if A is physically close to B, despite technology |
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A is more likely to retrieve X from B if A and B share attributes (position, gender, etc.) - if % cross gender edges>> 2*%male in network*%female in network |
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Knowledge Persuasion decision implementation Confirmation |
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no Homophily vs heterophily |
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Random ties vs ties more likely between boys and girls (different attributes) |
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Unchangeable characterists determine how links formed -vs. existing ties change alterable characteristice |
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feedback effects in the complex process of Influence including diffusion and coevolution |
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minority of the population is responsible for the majority of the activity - eg., sexual partners, friends, Heidi Roizen (silicon valley entrepreneur and CEO/board member) and Lois Weisberg(chicago connector- parties) |
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BKS performed a study in which they observed who people on the beach were talking to and then asked them to report who they were talking to- different |
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text to knowledge is automatic data mining system |
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herding/when beneficial to follow crowd despite own private info |
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Quadratic Assignment Procedure- sometimes used as goodness of fit test for graph-level statistics using Monte Carlo MLE |
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Theory of Collective Action vs mutual interest |
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Collective action is where actors work together to create something that they all enjoy -MI- Actors work together to each get something (eg., GroupOn) |
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nodes are concepts and edges are relationships btw them -eg word association studies - Vannevar Bush show that humans have associative memory |
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Multitheoretical Multilevel analysis refers to the approach that explains the creation, maintenance, and dissolution of network links through different theories and at different analytical levels |
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Strongly Connected Component |
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A subset of nodes for each of which there exists a directed path to every other node in the SCC |
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Setting Network Boundaries |
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1. Positional (eg employment) 2. Event Based (who attended) 3. Relational (social interconnectedness) |
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When survey respondents have different thresholds for a continuous variable with a non-continuous choice |
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informants place themselves as more central in overall networks |
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Expanding selection/snowball sampling |
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Start with initial list of people then add based on their responses - could then select k-core (know all except k members in set) |
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- identify an ego's alters -typically ego-centric studies that set boundaries during study |
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obtain info on the alters and their relationships |
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single v multiple name generators |
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Single elicits small network of close ties - can use social exchange criteria (advice), some use affective criteria (closeness, role (neighbor), frequency of interaction -multiple ask many questions (eg., who socialize with, advice...) |
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Reverse small world method |
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to determine network size- out of 500 people given their jobs, an individual has to say one person they know who would have the highest probability of knowing that person |
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give info about distribution of complex social interactions 2.see if network structures are observed more than expected by chance 3.Allow for quantitative modeling 4.break micro-macro gap - each tie is random variable -Propose dependence hypothesis, implies particular model form -Markov random graphs are a class of ERGM with Conditional Dependence assumption |
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homophily and assimilation |
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Homophily prevails among tobacco and alcohol users while assimilation prevails among canabis and alcohol users |
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Markov Chain Monte Carlo Maximum Liklihood Estimation -Simulation of graph distribution for given parameter values, refine values by comparison with observed graph -simple Markov inadequate when transitivity effects are strong |
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