Silence or Outbreak – a Real-Time Emergent Topic Identification System (RealTIS) for Social Media
Keywords:Outbreak Detection, Real-time Emergent Topic Identification, Motifs Analysis, Social Media
AbstractThis paper presents RealTIS, a Real-time emergent Topic Identification System for user-generated content on the web via social networking services such as Twitter, Weibo, and Facebook. Without user intervention, our proposed RealTIS system can efficiently collect necessary social media posts, construct a quality topic summarization from the vast sea of data, and then automatically identify whether the emerging topics will be out-breaking or just fading into silence. RealTIS uses a time-sliding window to compute the statistics about the basic structure (motifs) variation of the propagation network for a specific topic. These statistics are then used to predict unusual shifts in correlations, make early warning and detect outbreak. Besides, this work also illustrates the mechanism by which our proposed system makes early warning happen.
How to Cite
Lu, N., Yang, Z., Huang, J., Wu, Y., & Wang, H. (2022). Silence or Outbreak – a Real-Time Emergent Topic Identification System (RealTIS) for Social Media. Proceedings of the AAAI Conference on Artificial Intelligence, 36(11), 13194-13196. https://doi.org/10.1609/aaai.v36i11.21725
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