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2009
ACM

Sentiment analysis of blogs by combining lexical knowledge with text classification

9 years 10 months ago
Sentiment analysis of blogs by combining lexical knowledge with text classification
The explosion of user-generated content on the Web has led to new opportunities and significant challenges for companies, that are increasingly concerned about monitoring the discussion around their products. Tracking such discussion on weblogs, provides useful insight on how to improve products or market them more effectively. An important component of such analysis is to characterize the sentiment expressed in blogs about specific brands and products. Sentiment Analysis focuses on this task of automatically identifying whether a piece of text expresses a positive or negative opinion about the subject matter. Most previous work in this area uses prior lexical knowledge in terms of the sentiment-polarity of words. In contrast, some recent approaches treat the task as a text classification problem, where they learn to classify sentiment based only on labeled training data. In this paper, we present a unified framework in which one can use background lexical information in terms of word...
Prem Melville, Wojciech Gryc, Richard D. Lawrence
Added 25 Nov 2009
Updated 25 Nov 2009
Type Conference
Year 2009
Where KDD
Authors Prem Melville, Wojciech Gryc, Richard D. Lawrence
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