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http://hdl.handle.net/20.500.12358/25198
TitleLanguage-model-based pro/con classification of political text
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Abstract

Given a controversial political topic, our aim is to classify documents debating the topic into pro or con. Our approach extracts topic related terms, pro/con related terms, and pairs of topic related and pro/con related terms and uses them as the basis for constructing a pro query and a con query. Following standard LM techniques, a document is classified as pro or con depending on which of the query likelihoods is higher for the document. Our experiments show that our approach is promising.

Authors
Awadallah, Rawia
Ramanath, Maya
Weikum, Gerhard
TypeJournal Article
Date2010
Subjects
experimentation language models
text classification
h31 [information storage and retrieval]: content analysis and indexing-linguistic processing general terms algorithms
sentiment analysis
Published inProceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
PublisherACM
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The institutional repository of the Islamic University of Gaza was established as part of the ROMOR project that has been co-funded with support from the European Commission under the ERASMUS + European programme. This publication reflects the views only of the author, and the Commission cannot be held responsible for any use which may be made of the information contained therein.

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The institutional repository of the Islamic University of Gaza was established as part of the ROMOR project that has been co-funded with support from the European Commission under the ERASMUS + European programme. This publication reflects the views only of the author, and the Commission cannot be held responsible for any use which may be made of the information contained therein.

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