Mutual influence in support seeking and provision behaviors during comforting conversations: a turn-level analysis

Human Communication Research · 2022 · 12 citations

• Psychology
• Social psychology

Abstract Mutual influence is central to prominent supportive communication theories but remains understudied. We conduct a turn-level analysis to investigate mutual influence in the unfolding nature of conversations among 334 stranger dyads discussing a personal problem. We examine how the types of messages produced by support seekers influence the immediate response from providers, and how that provider response impacts the next message produced by support seekers. Seeker use of approach behaviors and exonerating justifications were associated with higher levels of person centeredness in provider responses, and avoidance behaviors were associated with lower levels of provider person centeredness. Higher levels of provider person centeredness were associated with a greater likelihood of approach behaviors, exonerating justifications, and incriminating justifications and lower likelihood of avoidance behaviors from seekers. The results collectively suggest virtuous and vicious cycles in the messages produced by seekers and providers during supportive conversations.

When Machine and Bandwagon Heuristics Compete: Understanding Users’ Response to Conflicting AI and Crowdsourced Fact-Checking

Human Communication Research · 2022 · 41 citations

• Computer Science
• Artificial Intelligence
• Machine Learning

Abstract Three experiments tested if the machine and bandwagon heuristics moderate beliefs in fact-checked claims under different conditions of human/machine (dis)agreement and of transparency of the fact-checking system. Across experiments, people were more likely to align their belief in the claim when artificial intelligence (AI) and crowdsourcing agents’ fact-checks were congruent rather than incongruent. The heuristics provided further nuance to the processes, especially as a particular agent suggested truth verdicts. That is, people with stronger belief in the machine heuristic were more likely to judge the claim as true when an AI agent’s fact-check suggested the claim was likely true but not false; likewise, people with stronger belief in the bandwagon heuristic were more likely to judge the claim as true when the crowdsource agent fact-checked the claim to be true but not false. Making the system more transparent to users does not appear to change results.

Social Norms and the Dynamics of Online Incivility

Social Science Computer Review · 2021 · 76 citations

• Political Science
• Social psychology
• Psychology

Online discussions are performed in the gaze of fellow users. To increase engagement, platforms typically let these users evaluate the comments made by others through rating systems (e.g., via Likes or Down/Up votes). Understanding how such ratings shape, and are shaped by, features of the underlying discussion is important for our understanding of online behavior. In this study, we focus on an increasingly concerning aspect of online discussions: incivility. We draw on the theory of normative social behavior to analyze a data set of over 6,000 online newspaper comments. We find that repeated incivility by the same person is more likely when their initial incivility was affirmed by both descriptive norms (incivility in nearby comments) and injunctive norms (Up votes). Repeated incivility receives more Up votes if nearby comments also include incivility but fewer Up votes if they do not, suggesting that injunctive norms are contextual and shaped by descriptive norms. We conclude that online incivility is a dynamic, normative process that is responsive to both positive feedback and proximate incivility.