首页|Cross event detection and topic evolution analysis in cross events for man-made disasters in social media streams
Cross event detection and topic evolution analysis in cross events for man-made disasters in social media streams
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NSTL
Terrorist attacks, chemical attacks, rapes and other socially sensitive incidents are shared on social media to gain attention from the world. Microblogging sites like Twitter become flooded with these root events and their sub events as they evolve over time, such events are referred to as cross events. Cross event detection is critical in determining the nature of events. The event detection is based on tweet segmentation using the Wikipedia title database. Segment clustering is done based on a similarity measure by encoding the tweets in the form of vectors using the BERT Model. We proposed the Cross Event Evolution Detection framework, which detects cross events that are similar in their temporal nature and result from main events. The experimental results on a real Twitter data collection shows the effectiveness of our proposed framework for both cross event detection and topic evolution algorithm during the evolution of topics and cross events.
NSTL
