Abstract
Shifts in emotions towards given topics on social media are often related to momentous real world events, and for the researcher or journalist, such changes may be the first observable sign that something interesting is going on. Further research on why a topic t suddenly has become, say, more or less popular, may involve searching for topics \(t'\) whose co-occurrence with t have increased significantly together with the change in emotion. We hypothesize that \(t'\) and its increasing relationship to t may relate to a contributing cause why the attitude towards t is changing. A method and tool is presented that monitors a stream of messages, reporting topics with changing emotions and indicating explanations by means of related topics whose increasing occurrence are taken as possible clues of why the change did happen.
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Andreasen, T., Christiansen, H., Have, C.T. (2015). Tracing Shifts in Emotions in Streaming Social Network Data. In: Esposito, F., Pivert, O., Hacid, MS., Rás, Z., Ferilli, S. (eds) Foundations of Intelligent Systems. ISMIS 2015. Lecture Notes in Computer Science(), vol 9384. Springer, Cham. https://doi.org/10.1007/978-3-319-25252-0_31
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DOI: https://doi.org/10.1007/978-3-319-25252-0_31
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