Decision Making in Online Social Networks

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    Understanding Morality behind Human opinion and reasoning
    ( 2022-01-04) Kumar, Akit ; Xiao, Lu
    Moral values influence people’s opinions and reasoning. While people increasingly share and shape each other’s opinions in social media, we have limited understanding of how people’s moral values play a role in these processes. As a first step to close this literature gap, we conducted two studies to examine the relationships between one’s morality and how one’s opinions are expressed and changed in social media. Specifically, we explored the potential of using the moral values reflected from an online comment to classify its stance. We also examined how these moral values contribute to the change of one’s opinions in online persuasion processes. Our results show that one’s morality and viewpoint are connected, and the more similar between the two users’ moral values the more persuasion power one carries over the other. In addition, the stronger a user’s moral value the more resistant the user is to change their opinion.
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    Separating privacy and security in online decision-making process: The case of Venmo
    ( 2022-01-04) Zanella, Gianluca ; Jozani, Mohsen ; Safaei Pour, Morteza
    The rise of peer-to-peer online financial services that attract users with social media features warrants a sharper distinction between security and privacy. While past research on online financial services focuses on the security of the transactions, the literature on online social media emphasizes the risks for the individual’s privacy. Unfortunately, the two concepts are often considered as overlapping or, in some cases, as two dimensions of the same concept, thus making complex the study of the distinct roles of security and privacy in the decision-making process. We analyze the activity of 13; 338 accounts on Venmo to explore the different roles of the two concepts in the decision to disclose financial transactions on online platforms. The results show that security concerns cause the users to opt-out of any public feeds, while users address their privacy concerns by limiting the amount of information disclosed. The findings and their impact are discussed.
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    Frequent Truth: Impact of Frequency of Misinformation Correction in Extended Extreme Events
    ( 2022-01-04) Nandakumar, Archana ; Rajivan, Prashanth
    Misinformation management is a growing area of concern in Online Social Network (OSN) organizations. There are several behavioral interventions employed to address misinformation in OSN's. One example is offering users correction when they have engaged with fake news. However, there is little research quantifying the effectiveness of such interventions. We conducted a laboratory experiment to test whether experiencing corrective feedback improved peoples' ability to discriminate true and false news claims during extended extreme events like the COVID-19 pandemic. Participants in the experiment were randomly assigned to four different experiment conditions. Depending on the condition assigned, participants received varying amount of corrective feedback. Results from this experiment suggests that increasing frequency of corrective feedback may not affect peoples' ability to correctly assess information (or misinformation). Political ideology and mistrust in fact-checking organization were found to be the most significant contributing factors. We discuss implications of the findings from this experiment.
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    Behavioral changes associated with interacting with bots on Twitter
    ( 2022-01-04) Babutsitdze, Zakaria ; Vincileoni, Dorian
    We study changes in Twitter users' behavior associated with interacting with automated bots on the platform. Based on the list of malicious bots identified and shut down by Twitter in the wake of 2016 US presidential election, we are able to identify about 54 thousand human Twitter users who have interacted with automated accounts. We first establish the baseline pattern of user behavior in the period before interaction and then measure behavioral changes observed around the period of interaction. Using a quasi-experimental research design, we document economically and statistically significant quantitative and qualitative changes in users' behavior and discuss their implications.
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    Introduction to the Minitrack on Decision Making in Online Social Networks
    ( 2022-01-04) Sadovykh , Valeria ; Sundaram, David ; Peko, Gabrielle