G. Murraya; E. Hoqueb; G. Careniniba University of the Fraser Valley, Abbotsford, BC, Canadab University of British Columbia, Vancouver, BC, Canada
Given a very large amount of social media text, being able to understand the variety of opinions contained in the text often depends on the generation of summaries and visualizations of the dataset so as to make it more manageable. This chapter first surveys approaches used for both extractive and abstractive summarization of opinion-filled social media text, including discussion of summarization evaluation. We then survey approaches for presenting these opinion summaries to users in the form of visualizations, including interactive ...
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