Investigating the Effects of Nudges for Facilitating the Use of Trigger Warnings and Content Warnings

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Virginia Tech


Social media can trigger past traumatic memories in viewers when posters post sensitive content. Strict content moderation and blocking/reporting features do not work when triggers are nuanced and the posts may not violate site guidelines. Viewer-side interventions exist to help filter and hide certain content but these put all the responsibility on the viewer and typically act as 'aftermath interventions'. Trigger and content warnings offer a unique solution giving viewers the agency to scroll past content they may want to avoid. However, there is a lack of education and awareness for posters for how to add a warning and what topics may require one. We conducted this study to determine if poster-side interventions such as a nudge algorithm to add warnings to sensitive posts would increase social media users' knowledge and understanding of how and when to add trigger and content warnings. To investigate the effectiveness of a nudge algorithm, we designed the TWIST (Trigger Warning Includer for Sensitive Topics) app. The TWIST app scans tweet content to determine whether a TW/CW is needed and if so, nudges the social media poster to add one with an example of what it may look like. We then conducted a 4-part mixed methods study with 88 participants. Our key findings from this study include (1) Nudging social media users to add TW/CW educates them on triggering topics and raises their awareness when posting in the future, (2) Social media users can learn how to add a trigger/content warning through using a nudge app, (3) Researchers grew in understanding of how a nudge algorithm like TWIST can change people's behavior and perceptions, and (4) We provide empirical evidence of the effectiveness of such interventions (even in short-time use).



Social Media, Twitter, X, Trigger Warnings, Content Warnings, Sensitive Content, Nudging Algorithm, OpenAI