Impact of Traumatic News on Social Media
Abstract
The spread of triggering and traumatic content on social media harms many social media users on a daily basis, as people cannot always control the content they view on social media. People who have been affected by past trauma may be triggered seeing social media posts that contain news of a similar nature. In this study, we collect tweets from two different news sources’ Twitter accounts. We use both regression and neural network models to classify these tweets as traumatic or non-traumatic based on a dataset of 600 events rated by trauma level. We then use various tweet metrics including retweets and replies to identify the reach and impact these potentially traumatic or triggering tweets have on Twitter users.
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Data Availability Statement
The datasets are available at the following google docs folder and can be shared upon request
https://drive.google.com/drive/folders/1xAkqiwioY_l0_xXaTE7aivq7k-CfysuQ?usp=drive_link
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