We have a strong tendency to reduce Cognitive dissonance. If multiple beliefs conflict with each other, some of the beliefs are likely to change to resolve the dissonance. In other words, beliefs interact. How should we conceptualize and model this interaction or the belief network?
A way to model the interactions between beliefs (or Belief system is by using the theory of Social balance (see Rodriguez2016collective). If we model a belief network as a network of concepts connected by signed edges (beliefs), then it is reasonable to assume that they will satisfy the social balance condition. For instance, three concepts have strong “positive” valence. If the beliefs between them are all positive, then they are in a stable status. But if one of the beliefs is negative, then this triad is not congruent anymore. We can also think of this with the valence of concepts. If two concepts have the same valence, then the connection between the two concepts would be positive.
Other theoretical attempts: - Cognitive association network - Galesic2021integrating - Brandt2021evaluating
Research groups and projects
Can we infer the belief network structure from data?
The strength of an edge between two concepts may be reflected by the co-occurrence of those concepts. Maybe Aspect based sentiment analysis can be used.
Hase2021language proposes methods to detect, update, and visualize the beliefs of language models.
Tomasevic2021measuring proposes a method to measure the influence of political beliefs.
Joseph2021misalignment surveyed people and compared their answers to what could be inferred (by humans), showing that there is considerable misalignment. This is a fundamental challenge for any effort to infer beliefs from public social media data.
Bhattacharya2012belief and Bhattacharya2012discovering propose methods to discover beliefs from social media data.
See also Dalege2021changing, Galesic2021integrating, Houghton2020interdependent, Brandt2021evaluating.
Schmelz2022opposition uses surveys to study the belief regarding the COVID 19 vaccine and related attitudes.