Rumors, Fake News and Social Bots in Conflicts and Emergencies: Towards a Model for Believability in Social Media

The use of social media is gaining more and more in importance in ordinary life but also in conflicts and emergencies. The social big data, generated by users, is partially also used as a source for situation assessment, e.g. to receive pictures or to assess the general mood. However, the information's believability is hard to control and can deceive. Rumors, fake news and social bots are phenomenons that challenge the easy consumption of social media. To address this, our paper explores the believability of content in social media. Based on foundations of information quality we conducted a literature study to derive a three-level model for assessing believability. It summarizes existing assessment approaches, assessment criteria and related measures. On this basis, we describe several steps towards the development of an assessment approach that works across different types of social media.

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