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Sentiment Analysis in Social Networks by Bing Liu, Enza Messina, Elisabetta Fersini, Federico Alberto Pozzi

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Chapter 6

Sentiment Analysis in Social Networks

A Machine Learning Perspective

E. Fersini    University of Milano-Bicocca, Milan, Italy

Abstract

Social networks represent an emerging challenging sector where the natural language expressions of people can be easily reported through short but meaningful text messages. Key information that can be grasped from social environments relates to the polarity of text messages (ie, positive, negative, or neutral). In this chapter we present a literature review regarding polarity classification in social networks, by distinguishing between supervised, unsupervised, and semisupervised machine learning models. In particular, the most recent advancements of the state of the art are presented, focusing on ...

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