Bwbaugh: Hierarchical sentiment analysis with partial self-training

*SEM 2013 - 2nd Joint Conference on Lexical and Computational Semantics

Volumn 2, Issue , 2013, Pages 539-542

  Baugh, Wesley ^a  

^a UNIVERSITY OF NORTH TEXAS   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFIERS; SEMANTICS;

HIERARCHICAL CLASSIFIERS; NAIVE BAYES CLASSIFIERS; OVERALL ACCURACIES; SELF TRAINING; SENTIMENT ANALYSIS; TRAINING DATA; UNLABELED DATA;

CLASSIFICATION (OF INFORMATION);

EID: 84978148013     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (5)

1. Alec Go, Richa Bhayani, and Lei Huang. Twitter sentiment classification using distant supervision. CS224N Project Report, Stanford, pages 1–12, 2009.
2. Anthony K Jose. Twitter sentiment analysis.
3. Moshe Koppel and Jonathan Schler. The importance of neutral examples for learning sentiment. Computational Intelligence, 22(2):100–109, 2006.
4. Alexander Pak and Patrick Paroubek. Twitter as a corpus for sentiment analysis and opinion mining. In Proceedings of LREC, volume 2010, 2010.
5. Theresa Wilson, Zornitsa Kozareva, Preslav Nakov, Alan Ritter, Sara Rosenthal, and Veselin Stoy-anov. Semeval-2013 task 2: Sentiment analysis in twitter. In Proceedings of the 7th International Workshop on Semantic Evaluation, 2013.