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• W2251081168 abstract "In this work, we propose a method for automatic analysis of attitude (affect, judgment, and appreciation) in sentiment words. The first stage of the proposed method is an automatic separation of unambiguous affective and judgmental adjectives from miscellaneous that express appreciation or different attitudes depending on context. In our experiments with machine learning algorithms we employed three feature sets based on Pointwise Mutual Information, word-pattern co-occurrence, and minimal path length. The next stage of the proposed method is to estimate the potentials of miscellaneous adjectives to convey affect, judgment, and appreciation. Based on the sentences automatically collected for each adjective, the algorithm analyses the context of phrases that contain sentiment word by considering morphological tags, high-level concepts, and named entities, and then makes decision about contextual attitude labels. Finally, the appraisal potentials of a word are calculated based on the number of sentences related to each type of attitude." @default.
• W2251081168 created "2016-06-24" @default.
• W2251081168 creator A5004281431 @default.
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• W2251081168 date "2012-12-01" @default.
• W2251081168 modified "2023-09-27" @default.
• W2251081168 title "Analyzing Sentiment Word Relations with Affect, Judgment, and Appreciation" @default.
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