Predicting the Political Sentiment of Web Log Posts Using Supervised Machine Learning Techniques Coupled with Feature Selection-Reference-Cited by-同舟云学术

Predicting the Political Sentiment of Web Log Posts Using Supervised Machine Learning Techniques Coupled with Feature Selection

Published: Issue: Volume: Page:187-206
ISSN:
Container-title:Advances in Web Mining and Web Usage Analysis
language:
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Author:

Durant Kathleen T.,Smith Michael D.

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/978-3-540-77485-3_11.pdf

Reference23 articles.

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2. Carroll, J.: Local TV and Newspapers Remain Most Popular News Sources, Increased use of Internet news this year. The Gallup Poll. poll.gallup.comcontent/default.aspx?CI=14389 (December 2004)

3. Das, S., Chen, M.: Yahoo! for Amazon: Extracting Marketing Sentiment from Stock Message Boards. In: APFA 2001. Proceedings of the 8th Asia Pacific Finance Association Annual Conference (2001)

4. Dube, J.: Blog Readership up 58% in 2004. CyberJournalist.net (January 2005), www.cyberjournalist.net/news/001819.php

5. Engström, C.: Topic Dependence in sentiment classification. Master’s thesis, St Edmunds’s College, University of Cambridge (2004)

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