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Formal Models & Network mechanisms

Emerging ideas. Formal Models & Network mechanisms. Formal network mechanisms. Agent-based models Experiments Diffusion mechanisms (Pipes) Network size Location of first movers Prism” mechanisms Power, rationality Centrality may also shape situations Not much explored.

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Formal Models & Network mechanisms

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  1. Emerging ideas Formal Models & Network mechanisms

  2. Formal network mechanisms • Agent-based models • Experiments • Diffusion mechanisms (Pipes) • Network size • Location of first movers • Prism” mechanisms • Power, rationality • Centrality may also shape situations • Not much explored

  3. Conditional Choice (from Rolfe 2009) Conditional Decision Rules

  4. Conditional Decision-making:Impact of Network Size on Diffusion Simulated turnout with 15% unconditional cooperation

  5. What to Measure? • Networks as Pipes • Location of positions, resources, mobilization, innovation, etc. • Rate/form of spread • Average degree • Clustering/density • Centralization • Redundant Ties • Social Cleavages • Network as Prisms • Relational style • Underinvestment • Overinvestment • Local strategy • structural holes • brokerage • Status

  6. Emerging ideas Measuring Network Size: Social Circles and scale UP

  7. Which Network to Measure? • Specific Transaction (i.e., discuss politics) • Social Circles (Dunbar) • 3-5 (core/family) • 12-20 (extended family/band) • 100-250 (lineage/Christmas Card List) • 1000s (Tribe)

  8. Extended Friendship Network Circle Please think for a moment about your extended network of friends and family. These are people whom you see on a fairly regular basis, or did see regularly in the past.  These may be people on your list for holiday or birthday cards, or people you would be likely to invite to a large party or wedding. Neighbours, co-workers, former schoolmates and people you met through social, political or religious activities may fall into this social circle. ...about how many people do you have in this social circle? Even if you are not sure, please take your best guess. • 1 to 25 or open-ended • 26 to 50 • 51 to 75 (and so on)

  9. Extended friendship Circle, cont. ...about how many have the following first or given names. Even if you are not at all sure, please take your best guess Katharina Anne Eva Martin Paul Marc/Mark Robert • Patrick • Gregory • Shaun • Rachael • Julia • Heather

  10. Network Structure Measure: Network Size • Self-estimated size • How many people do you know? • Scale-up estimates • Killworth, et al. 1988 • McCormick, Salganik and Zheng (2010) • Carefully pick names (.1% of population, equal across generations)

  11. Germany: Network Size

  12. Network Structure Measure: Personal Network Density • Is good friends with someone else on this list (Political Discussion) • Burt 1984 • What proportion are family members? • Sum of unique categories named from the “How many X do you know?” (may also proxy size)

  13. Network Structure Measure: Overdispersion and cleavages • How many people do you know…[in prison] Zheng, Salganik, Gelman (2006) examples from CCAP • Cleavages and network size Rolfe, 2012

  14. Network Structure Measure: Social Capital Access & Social Cleavages ...about how many fall into the following categories. Even if you are not at all sure, please take your best guess. Professional writer, artist Unemployed Retired Drives a company car 1 2-3 4-5 6-10 11 or more • None • Politicians • Leaders in neighborhood • Business owners or Self Employed • Corporate Executives • Managers • Professionals • Barkeeps • Schoolteachers

  15. Over-dispersion of Resources/Positions

  16. Proportion of Rs Knowing No Xs, by Social Circle (UK) A gender gap in ACCESS to power?

  17. CLEAVAGES: Network size isn’t an individual level mechanism…

  18. Network size varies across the social cleavage (1985 GSS)

  19. Voter turnout by social context(1985 GSS)

  20. Emerging ideas Measuring Networks as PRisms

  21. What to Measure? • Networks as Pipes • Location of positions, resources, mobilization, innovation, etc. • Rate/form of spread • Average degree • Clustering/density • Centralization • Redundant Ties • Social Cleavages • Network as Prisms • Relational style • Underinvestment • Overinvestment • Relational strategy • Structural holes • Brokerage • Status

  22. Relational Style/Strategy 1 Imagine your were hosting a party, and planned to invite friends from different parts of your life (e.g., work, school, social groups, neighborhood, etc.) • Would you find it appealing • Would they already know each other • Would they mix and mingle

  23. Relational Style/Strategy II Are you more comfortable interacting one-on-one or in a group? When there is a conflict between your friends, are you more likely to.. • pick sides • mediate • stay out of it

  24. Relational Style & Partisanship • Under-investors are more conservative; over-investors are more liberal (preliminary findings) • See Jackson on networks and beliefs about whether friendships are complements or substitutes • Under/Over Investment • Relational Style 1 & 2 • Number of activities/groups • Personal network size • Political Outcomes • Left-right • party choice • issue attitudes

  25. Self-Monitoring: 5 Qs (Berinsky)

  26. Emerging ideas Eliciting Network Attitudes: Issue or “Identity” Space Placements

  27. Issue Space: Gender Equality

  28. Germany & UKAverage Issue Placements

  29. Germany (Post Election)Perceptions of Disagreement

  30. Self vs. Family, Friends,Coworkers & Neighbors

  31. Emerging ideas Networks and Opinion Instability

  32. Predictions: Attitude Instability

  33. Issues and Opinion Stability

  34. Predictions: Attitude Instability

  35. Absolute value of change in opinion, by initial opinion

  36. Predicting Attitude Instability

  37. Predictions: Attitude change

  38. Directed change in opinion, by initial opinion

  39. Predicting Attitude Change

  40. Emerging ideas Political Belief Systems:Relational Class Analysis

  41. Measuring Political Belief SystemsGoldberg and Baldassarri “a configuration of ideas and attitudes in which the elements are bound together by some form of constraint or functional interdependence" (Converse 1964, 207) • Empirical analyses based on individual attitudes, summary indices, or dyadic interdependence. • Studies assume the existence of a singular system of • interconnected beliefs (i.e., liberal-conservative polarity). • Results: A large majority of citizens exhibit limited levels of constraint and coherence in the overall organization of their political beliefs (Converse 1964; Campell et al. 1960; Luskin 1987; DelliCarpini, Keeter1991; Popkin, Dimoch 1999).

  42. RCA – Relational Class Analysis • RCA Identifies political belief networks that are most common across the population. • RCA classifies individuals into groups according to their organization of beliefs. • RCA avoids a priori assumptions about how political beliefs are organized: • belief networks emerge from pattern of responses • it allows to identify multiple political belief systems along which sociodemographic and cognitive characteristics the population should be partitioned.

  43. Measuring Belief Similarity

  44. Spectral Partitioning into Belief “Blocks”

  45. Ideologues

  46. Alternatives

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