Discovering Emerging Topics in Social Streams via Link Anomaly Detection

Provided by: Institute of Electrical and Electronics Engineers
Topic: Networking
Format: PDF
Detection of emerging topics is now receiving renewed interest motivated by the rapid growth of social networks. Conventional term-frequency-based approaches may not be appropriate in this context, because the information exchanged are not only texts but also images, URLs and videos. The authors focus on the social aspects of these networks. That is the links between users that are generated dynamically intentionally or unintentionally through replies, mentions and retweets. The authors propose a probability model of the mentioning behavior of a social network user and propose to detect the emergence of a new topic from the anomaly measured through the model.

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