Diletta Goglia,
Alessio Gandelli,
Davide Vega
diletta.goglia@it.uu.se (D.G.), davide.vega@it.uu.se (D.V.)
UU-InfoLab, Department of Information Technology, Uppsala University, Uppsala, Sweden
Individuals' opinions and judgments are shaped by interactions with others and by the social context in which they occur, especially on social media platforms where users encounter an overload of different actors, communities, and information. Such exposure significantly influences users' beliefs and behaviors and deeply impacts their opinion expression as demonstrated by diverse social psychology theories, such as the spiral of silence. While the impact of groups on individual opinions has been extensively studied in offline contexts, its online equivalent lacks comprehensive understanding. In particular, estimating the opinion of a group in online discussions is a complex task, as is assessing users' exposure to it and measuring its influence on them. Nonetheless, the existing literature studied online opinion dynamics primarily (i) collecting evidence from controlled and regulated environments (e.g., surveys and lab settings), and (ii) focusing on digital conversations about a narrow set of topics (such as political debates).
In this work, we measure how users' judgments about morally ambiguous social dilemmas are influenced by the opinion of the majority group on online platforms. We utilize digital footprints (i.e., more than 6 million comments gathered from spontaneous online discussions) collected from the Reddit community \textit{r/AmItheAsshole}, where users participate to judge each other based on stories narrating everyday moral dilemmas and morally ambiguous behaviors. %Our dataset consists of more than 6 million Reddit comments from \textit{r/AmItheAsshole}, an online community where people participate to express judgments about other users based on morally ambiguous behaviors. In the community, the most popular opinion is publicly revealed after some time: we leverage this information to examine if and how users' judgments change after such majority opinion is unveiled. We use a Bayesian multivariate regression %analysis approach to assess such impact.
Our analysis reveals that users' judgment behavior changes in quantity but not in quality (i.e., the amount of expressed judgments decreases, but, at the same time, the type of expressed judgment does not). Users are not adapting their individual judgments to the majority opinion while not collectively diverging from it, indicating that the majority is not influencing their own judgments. We interpret our findings using social psychology theories, emphasizing the different social norms that regulate online and offline interactions. This research contributes to a deeper understanding of opinion dynamics in online environments, highlighting the unique mechanisms that govern social influence in digital communities.
TBD
This work has been partly funded by eSSENCE, an e-Science collaboration funded as a strategic research area of Sweden. The computations were enabled by resources provided by the National Academic Infrastructure for Supercomputing in Sweden (NAISS), partially funded by the Swedish Research Council through grant agreement no. 2022-06725. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
This work is licensed under the MIT License.
This repository is actively maintained. For any questions or further information, please feel free to contact the corresponding author:
Diletta Goglia 
Ph.D. Candidate at Uppsala University Information Laboratory (UU-InfoLab) research group.
Information Technology department, Uppsala University, Sweden.
diletta.goglia@it.uu.se
@dilettagoglia
Last update: April 2025