This project, run through ARLIS, investigates how emotion impacts information propagation and sharing in Polish and Lithuanian social media. Teams of in-country annotators independently assess each post, including all multimedia content, for over 22 distinct emotions inclusively on 0 to 100 scales--meaning that the same post will have different scores for different emotions. We will conduct multi-level statistical analyses of the impact of emotions, specific topics, and account and message features on social media sharing and engagement.
Developing novel techniques - through the application of state-of-the-art machine learning - to detect various forms of clickbait, especially video-based clickbait, and study user behavior on social media to design effective warning systems.
Online communities, from question and answer sites to general-purpose discussion forums, are increasingly working to solve hard problems together, often through a process of open sharing and discussion of ideas and information.
