FB1 Sozial- und Bildungswissenschaften
Filtern
Erscheinungsjahr
- 2021 (3) (entfernen)
Dokumenttyp
Sprache
- Englisch (3)
Volltext vorhanden
- nein (3)
Gehört zur Bibliographie
- ja (3)
Schlagworte
- Gruppendynamik (2)
- Affect (1)
- Affekt (1)
- Computational social science (1)
- Culture (1)
- Gefühl (1)
- GitHub (1)
- Kognitive Dissonanz (1)
- Kollaboration (1)
- Sozialpsychologie (1)
Institut
- FB1 Sozial- und Bildungswissenschaften (3) (entfernen)
Theoretical and Empirical Modeling of Identity and Sentiments in Collaborative Groups (THEMIS.COG) was an interdisciplinary research collaboration of computer scientists and social scientists from the University of Waterloo (Canada), Potsdam University of Applied Sciences (Germany), and Dartmouth College (USA). This white paper summarizes the results of our research at the end of the grant term. Funded by the Trans-Atlantic Platform’s Digging Into Data initiative, the project aimed at theoretical and empirical modeling of identity and sentiments in collaborative groups. Understanding the social forces behind self-organized collaboration is important because technological and social innovations are increasingly generated through informal, distributed processes of collaboration, rather than in formal organizational hierarchies or through market forces. Our work used a data-driven approach to explore the social psychological mechanisms that motivate such collaborations and determine their success or failure. We focused on the example of GitHub, the world’s current largest digital platform for open, collaborative software development. In contrast to most, purely inductive contemporary approaches leveraging computational techniques for social science, THEMIS.COG followed a deductive, theory-driven approach. We capitalized on affect control theory, a mathematically formalized theory of symbolic interaction originated by sociologist David R. Heise and further advanced in previous work by some of the THEMIS.COG collaborators, among others. Affect control theory states that people control their social behaviours by intuitively attempting to verify culturally shared feelings about identities, social roles, and behaviour settings. From this principle, implemented in computational simulation models, precise predictions about group dynamics can be derived. It was the goal of THEMIS.COG to adapt and apply this approach to study the GitHub collaboration ecosystem through a symbolic interactionist lens. The project contributed substantially to the novel endeavor of theory development in social science based on large amounts of naturally occurring digital data.
The interplay between intuitive and deliberative processing is known to be important for human decision making. As independent modes, intuitive processes can take on many forms from associative to constructive, while deliberative processes often rely on some notion of decision theoretic rationality or pattern matching. Dual process models attempt to unify these two modes based on parallel constraint networks or on socially or emotionally oriented adjustments to utility functions. This paper presents a new kind of dual process model that unifies decision theoretic deliberative reasoning with intuitive reasoning based on shared cultural affective meanings in a single Bayesian sequential model. Agents constructed according to this unified model are motivated by a combination of affective alignment (intuitive) and decision theoretic reasoning (deliberative), trading the two off as a function of the uncertainty or unpredictability of the situation. The model also provides a theoretical bridge between decision-making research and sociological symbolic interactionism. Starting with a high-level view of existing models, we advance Bayesian Affect Control Theory (BayesACT) as a promising new type of dual process model that explicitly and optimally (in the Bayesian sense) trades off motivation, action, beliefs and utility. We demonstrate a key component of the model as being sufficient to account for some aspects of classic cognitive biases about fairness and dissonance, and outline how this new theory relates to parallel constraint satisfaction models.
We review Affect Control Theory (ACT) as a promising basis for equipping computational agents in social simulations with a sense of sociality. ACT is a computational theory that integrates sociological insights about the symbolic construction of the social order with psychological knowledge about cognitive-affective mechanisms. After explaining the theoretical foundations of ACT and applications of the theory at the dyadic and group level, we describe a case study applying the theory from an ongoing research project examining self-organized online collaboration in software development.