Abstract
The user generated content, available in massive amounts in social media, is receiving increased attention due to its many potential applications. One of such applications is the representation of events with multimedia data. This paper addresses the problem of retrieving and summarizing events on a given topic, and propose a novel and original framework for leveraging social media data to extract and illustrate social events automatically on any given query. The problem is tackled in three steps. First, the input query is parsed semantically to identify the topic, location, and time information related to the event of interest. Then, we use the parsed information to mine the latest and hottest related events from social news web services. In the end, for each event, we retrieve both relevant tweets on Twitter and compelling images from Google image search. The resulting documents are shown within a vivid interface featuring both event description, tag cloud and photo collage.
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Liu, X., Huet, B. (2013). Event Representation and Visualization from Social Media. In: Huet, B., Ngo, CW., Tang, J., Zhou, ZH., Hauptmann, A.G., Yan, S. (eds) Advances in Multimedia Information Processing – PCM 2013. PCM 2013. Lecture Notes in Computer Science, vol 8294. Springer, Cham. https://doi.org/10.1007/978-3-319-03731-8_69
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DOI: https://doi.org/10.1007/978-3-319-03731-8_69
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-03730-1
Online ISBN: 978-3-319-03731-8
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