Mining WordNet for fuzzy sentiment: Sentiment tag extraction from WordNet glosses

@misc{citeulike:2804615, abstract = {Many of the tasks required for semantic tagging of phrases and texts rely on a list of words annotated with some semantic features. We present a method for extracting sentiment-bearing adjectives from WordNet using the Sentiment Tag Extraction Program (STEP). We did 58 STEP runs on unique non-intersecting seed lists drawn from manually annotated list of positive and negative adjectives and evaluated the results against other manually annotated lists. The 58 runs were then collapsed...}, author = {Andreevskaia, A. and Bergler, S. }, citeulike-article-id = {2804615}, keywords = {lexical-analysis, opinion-mining, sentiment}, posted-at = {2008-05-16 08:41:38}, priority = {3}, title = {Mining WordNet for fuzzy sentiment: Sentiment tag extraction from WordNet glosses}, url = {http://citeseer.ist.psu.edu/747034.html}, year = {2006} }

TY - GEN ID - citeulike:2804615 L3 - citeulike-article-id:2804615 TI - Mining WordNet for fuzzy sentiment: Sentiment tag extraction from WordNet glosses N2 - Many of the tasks required for semantic tagging of phrases and texts rely on a list of words annotated with some semantic features. We present a method for extracting sentiment-bearing adjectives from WordNet using the Sentiment Tag Extraction Program (STEP). We did 58 STEP runs on unique non-intersecting seed lists drawn from manually annotated list of positive and negative adjectives and evaluated the results against other manually annotated lists. The 58 runs were then collapsed... KW - lexical-analysis KW - opinion-mining KW - sentiment AU - Andreevskaia, A AU - Bergler, S PY - 2006/// UR - http://citeseer.ist.psu.edu/747034.html ER -