Event Detection in Social Media Data

نویسندگان

  • Wenwen Dou
  • Xiaoyu Wang
  • William Ribarsky
  • Michelle Zhou
چکیده

Recent research has shown that a considerable fraction of social media streams are about “events”. Collectively, events serve as a succinct summary of social media streams. Individually, event and its sub-events, reveal the evolution of certain social phenomena over time. In addition, analyzing relationships between events and people’s responses to the events provides rich information on the masses’ opinions towards an event; this may further shed light on the impact of public policies dealing with the events. Event detection, therefore, is an important and practical task to identify and make sense of the overwhelming amounts of social media data. In this paper, we explore and summarize popular tasks in the domain of event detection. More specifically, we present four tasks: New Event Detection, Event Tracking, Event Summarization, and Event Association. We use these four tasks to illustrate main purposes for performing event detection in social media space, and further present their application domains. Keywords: event detection, social media, visualization. Index Terms: H.5.m. Information interfaces and presentation (e.g., HCI): Miscellaneous.

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تاریخ انتشار 2012