Language-model-based pro/con classification of political text

SIGIR 2010 Proceedings - 33rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval

Volumn , Issue , 2010, Pages 747-748

  Awadallah, Rawia ^a   Ramanath, Maya ^a   Weikum, Gerhard ^a  

^a MAX PLANCK INSTITUTE FOR INFORMATICS   (Germany)

Author keywords

Language models; Sentiment analysis; Text classification

Indexed keywords

LANGUAGE MODEL; MODEL-BASED; SENTIMENT ANALYSIS; TEXT CLASSIFICATION;

COMPUTATIONAL LINGUISTICS; INFORMATION RETRIEVAL; QUERY PROCESSING;

TEXT PROCESSING;

EID: 77956048676     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1835449.1835596     Document Type: Conference Paper

References (4)

1. K. Eguchi and V. Lavrenko. Sentiment retrieval using generative models. In EMNLP, 2006.
2. B. Pang and L. Lee. Opinion mining and sentiment analysis. Found. and Trends in IR, 2(1-2):1-135, 2008.
3. M. Thomas, B. Pang, and L. Lee. Get out the vote: Determining support or opposition from congressional floor-debate transcripts. In EMNLP, 2006.
4. C. Zhai. Statistical language models for information retrieval. Found. and Trends in IR, 2(3):137-215, 2008.