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- W53089922 abstract "Online discussions, user reviews and comments on the Social Web are valuable sources of information about products, services, or shared contents. The rapidly growing popularity and activity of Web communities raises novel questions of appropriate aggregation and diversification of such social contents. In many cases, users are interested in gaining an extensive overview over pros and contras of a particular track of contributions. Consequently, we address the problem of social content diversification by combining latent semantic analysis with feature-centric sentiment analysis. Our FREuD approach provides a representative overview over sub-topics and aspects of discussions, characteristic user sentiments under different aspects, and reasons expressed by different opponents. Our preliminary experiments with live data of CNET reviews shows promising results and indicate that FREuD is able to extract aspects from the reviews and generate a sentiment-diversified ranked list of user reviews for a given product." @default.
- W53089922 created "2016-06-24" @default.
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- W53089922 date "2012-01-01" @default.
- W53089922 modified "2023-09-27" @default.
- W53089922 title "FREuD: Feature-Centric Sentiment Diversification of Online Discussions" @default.
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