Modeling what makes us human:
Individual beliefs and identities within sociocultural structures

Summary

• People associate with many different identities

  • Identities help us organize (countries, directions of road driving)

  • They also drive us to fight each other

• Where do beliefs and identities come from?

• Theory:

  • We develop identities from our interactions with others

  • Learn social structures: in/out group, stereotypes

  • We internalize our social structure, place in world, norms of private/public action

    • Norms control private behavior because we have an idea of a “generalized other” that represents the world

  • We have choice about which identities we participate in

• Norms allow us to interact with people we don’t personally know

  • Mediated via social networks: receiving and transmitting belief/identity

  • Feedback look: cognition, belief/identify, larger social context

• Challenge: modeling the interaction between culture and identity

• Belief change

  • How do people combine information from personal beliefs and social network information to change/create new beliefs?

  • For any given issue people have many related beliefs

    • E.g. for COVID vaccine there are beliefs related to religion, value of nature-based healing, danger

  • How do people combine prior beliefs to inform a given issue

  • Belief dissonance: 

    • If different beliefs disagree it is painful

    • As such, you’ll change your mind to make them agree

      • Modify beliefs

      • Modify whether a belief is relevant to an issue

      • Modify social network to change your influences

    • Model process as H = weighted sum of difference between different beliefs

    • The probability that a person holds a given belief is P(1/(1+ebeta*H) 

      • (beta is free parameter)

  • Topics:

    • Childhood vaccines

    • Genetically modified foods

  • Survey asked people about how other beliefs relate to the topics

    • Social beliefs

    • Moral beliefs

  • Used survey to build a network of beliefs (nodes: beliefs, edges: number of people who hold both beliefs)

  • Showed that to some extent beliefs do become more homogenized over time but its a noisy process

• Identity signaling

  • In/out-group signaling across social networks

  • Signaling

    • Overt: actively displaying identity

    • Covert: only noticeable to the in-group

  • Overt signaling more advantageous when more of your network is in-group and vice versa

  • Data: Tweets from accounts with very heterogeneous networks

    • Identity of tweets are classified by users to identify signaling

      • Determined overt vs covert by asking raters about what the tweet actually means politically

      • If people in a region of political space are confused, then the signal is covert

    • Data shows that accounts with more diverse social networks

• Formation of identity via cultural/group boundaries and stereotypes (in-progress)

  • How do political elites identify groups as “Us” (Americans) vs “Them” (Immigrants)

    • E.g. Italians shifted from Them to Us but Mexicans are still Them to a large extent

    • Criteria has changed (less religion and more ethnicity, legality of entry)

    • Looked at boundary rhetoric and how it evolves over time

      • Word embeddings in documents,

      • Applied to ethnic groups

      • Related to external world events

    • Goal: how group boundaries can be used to coordinate different groups for social change