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This paper presents a new method for sentiment analysis in Facebook that, starting from messages written by users, supports: (i) to extract information about the users’ sentiment polarity (positive, neutral or negative), as transmitted in the messages they write; and (ii) to model the users’ usual sentiment polarity and to detect significant emotional changes. We have implemented this method in SentBuk,...
This paper presents SentBuk, a Facebook application that extracts information about the user sentiment automatically, in a non-intrusive way. It performs sentiment analysis of user writings in Facebook walls, classifying each sentence as positive, neutral or negative. Finally, the overall user sentiment is calculated. On one hand, this information is useful to enrich user models for adaptive e-learning...
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