SIG Social Computing
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Paper Type
Complete
Paper Number
1678
Description
While the effect of established social media on stock markets has been thoroughly investigated, the recent surge in retail investing and the emergence of different finance-related Reddit communities with unique new traits have led to new research questions. In this work, we aim to understand the linguistic and thematic characteristics and differences of the largest financial Reddit communities, r/WallStreetBets, r/stocks, and r/investing. Using different techniques for the analysis of linguistic features and topic modeling, we identify keywords and phrases that are most prominent in each community and determine each community’s thematic focus and risk affinity. An analysis of users that post on all of these communities confirm these findings, as they appear to adapt to the respective target audience when posting. The stock returns for each community prove consistent with their respective risk profile. Overall, we conclude that understanding these communities can help investors in making more informed investment decisions.
Recommended Citation
Agrawal, Pratik; Buz, Tolga; and de Melo, Gerard, "WallStreetBets Beyond GameStop, YOLOs, and the Moon: The Unique Traits of Reddit’s Finance Communities" (2022). AMCIS 2022 Proceedings. 8.
https://aisel.aisnet.org/amcis2022/sig_sc/sig_sc/8
WallStreetBets Beyond GameStop, YOLOs, and the Moon: The Unique Traits of Reddit’s Finance Communities
While the effect of established social media on stock markets has been thoroughly investigated, the recent surge in retail investing and the emergence of different finance-related Reddit communities with unique new traits have led to new research questions. In this work, we aim to understand the linguistic and thematic characteristics and differences of the largest financial Reddit communities, r/WallStreetBets, r/stocks, and r/investing. Using different techniques for the analysis of linguistic features and topic modeling, we identify keywords and phrases that are most prominent in each community and determine each community’s thematic focus and risk affinity. An analysis of users that post on all of these communities confirm these findings, as they appear to adapt to the respective target audience when posting. The stock returns for each community prove consistent with their respective risk profile. Overall, we conclude that understanding these communities can help investors in making more informed investment decisions.
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