TY - CHAP A1 - Morgan, Jonathan Howard A1 - Zhao, Jun A1 - Zöller, Nikolas A1 - Sedlacek, Andrea A1 - Chen, Lena A1 - Piper, Hayley A1 - Beck, Yliana A1 - Rogers, Kimberly B. A1 - Hoey, Jesse A1 - Schröder, Tobias T1 - Modeling the Culture of Online Collaborative Groups with Affect Control Theory T2 - Advances in Social Simulation N2 - 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. KW - Culture KW - Affect KW - Gruppendynamik KW - Kollaboration Y1 - 2021 SN - 978-3-030-61503-1 U6 - https://doi.org/10.1007/978-3-030-61503-1_14 SP - 147 EP - 160 PB - Springer CY - Cham ER - TY - JOUR A1 - Lorenz, Jan A1 - Neumann, Martin A1 - Schröder, Tobias T1 - Individual attitude change and societal dynamics: Computational experiments with psychological theories JF - Psychological Review N2 - We present an agent-based model for studying the societal implications of attitude change theories. Various psychological theories of persuasive communication at the individual level are implemented as simulation experiments. The model allows us to investigate the effects of contagion and assimilation, motivated cognition, polarity, source credibility, and idiosyncratic attitude formation. Simulations show that different theories produce different characteristic macrolevel patterns. Contagion and assimilation are central mechanisms for generating consensus, however, contagion generates a radicalized consensus. Motivated cognition causes societal polarization or the fragmentation of attitudes. Polarity and source credibility have comparatively little effect on the societal distribution of attitudes. We discuss how the simulations provide a bridge between microlevel psychological theories and the aggregated macrolevel studied by sociology. This approach enables new types of evidence for evaluating psychological theory to complement experimental approaches, thus answering calls to enhance the role of coherent and formalized theory in psychological science. KW - Attitudes KW - Social Influence KW - Theoretical Integration KW - Computational Model KW - Einstellungsforschung KW - Einfluss Y1 - 2021 UR - https://psyarxiv.com/ebfvr/ U6 - https://doi.org/10.1037/rev0000291 SN - 1939-1471 VL - 128 IS - 4 SP - 623 EP - 642 PB - American Psychological Association CY - Washington ER - TY - RPRT A1 - Hoey, Jesse A1 - Nagappan, Meiyappan A1 - Rogers, Kimberly B. A1 - Schröder, Tobias A1 - Dametto, Diego A1 - De Zoysa, Nalin A1 - Iyer, Rahul A1 - Morgan, Jonathan H. A1 - Rishi, Deepak A1 - Sirianni, Antonio D. A1 - Yun, Seonghu A1 - Zhao, Jun A1 - Zöller, Nikolas T1 - Theoretical and Empirical Modeling of Identity and Sentiments in Collaborative Groups N2 - 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. KW - Computational social science KW - GitHub KW - Gruppendynamik KW - Sozialpsychologie Y1 - 2021 U6 - https://doi.org/10.31235/osf.io/4hukx SP - 1 EP - 36 ER - TY - JOUR A1 - Hoey, Jesse A1 - MacKinnon, Neil J. A1 - Schröder, Tobias T1 - Denotative and connotative management of uncertainty BT - A computational dual-process model JF - Judgment and Decision Making N2 - 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. KW - Zwei-Prozess-Modell KW - Gefühl KW - Affekt KW - Kognitive Dissonanz Y1 - 2021 UR - http://journal.sjdm.org/20/200104/jdm200104.pdf U6 - https://doi.org/10.1017/S1930297500008652 SN - 1930-2975 VL - 16 IS - 2 SP - 505 EP - 550 PB - Society for Judgment and Decision Making ER -