A Sentimental Education: Sentiment Analysis Using Subjectivity Summarization Based on Minimum Cuts

@misc{citeulike:113216, abstract = {Sentiment analysis seeks to identify the viewpoint(s) underlying a text span; an example application is classifying a movie review as "thumbs up" or "thumbs down". To determine this sentiment polarity, we propose a novel machine-learning method that applies text-categorization techniques to just the subjective portions of the document. Extracting these portions can be implemented using efficient techniques for finding minimum cuts in graphs; this greatly facilitates incorporation of cross-sentence contextual constraints.}, author = {Pang, Bo and Lee, Lillian }, citeulike-article-id = {113216}, eprint = {cs/0409058}, keywords = {classification, graph, natural-language-processing, nlp, subjectivity, summarization}, month = {September}, posted-at = {2005-03-03 14:44:37}, priority = {4}, title = {A Sentimental Education: Sentiment Analysis Using Subjectivity Summarization Based on Minimum Cuts}, url = {http://arxiv.org/abs/cs/0409058}, year = {2004} }

TY - ELEC ID - citeulike:113216 L3 - citeulike-article-id:113216 TI - A Sentimental Education: Sentiment Analysis Using Subjectivity Summarization Based on Minimum Cuts N2 - Sentiment analysis seeks to identify the viewpoint(s) underlying a text span; an example application is classifying a movie review as "thumbs up" or "thumbs down". To determine this sentiment polarity, we propose a novel machine-learning method that applies text-categorization techniques to just the subjective portions of the document. Extracting these portions can be implemented using efficient techniques for finding minimum cuts in graphs; this greatly facilitates incorporation of cross-sentence contextual constraints. KW - classification KW - graph KW - natural-language-processing KW - nlp KW - subjectivity KW - summarization AU - Pang, Bo AU - Lee, Lillian PY - 2004/09/29/ UR - http://arxiv.org/abs/cs/0409058 ER -