Text and network analysis for sentiment mining

A session at Sentiment Analysis in Finance Conference, Singapore, 10 – 11 March, 2016

Enza Messina, University of Milano-Bicocca

In this talk we show how social relationships can be managed to improve user-level sentiment analysis of microblogs, overcoming the limitation of the state-of-the-art methods that generally consider posts as independent data. We show how combining post contents and network structure information may lead to significant improvements in the polarity classification of the sentiment both at post and at user level.

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Date Thu 10th March 2016

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