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Building a Concept-Level Sentiment Dictionary Based on Commonsense Knowledge
March-April 2013 (vol. 28 no. 2)
pp. 22-30
Angela Charng-Rurng Tsai, National Taiwan University
Chi-En Wu, Yuan Ze University
Richard Tzong-Han Tsai, Yuan Ze University
Jane Yung-jen Hsu, National Taiwan University
Sentiment dictionaries are essential for research in the sentiment analysis field. A two-step method integrates iterative regression and random walk with in-link normalization to build a concept-level sentiment dictionary. The approach uses ConceptNet as a framework to propagate sentiment values, based on the assumption that semantically related concepts share a common sentiment.
Index Terms:
Knowledge discovery,Data mining,Emotion recognition,Information analysis,Knowledge discovery,Iterative methods,Data collection,Dictionaries,Context awareness,Natural language processing,commonsense knowledge,Knowledge discovery,Data mining,Emotion recognition,Information analysis,Knowledge discovery,Iterative methods,Data collection,Dictionaries,Context awareness,Natural language processing,ConceptNet,sentiment analysis,sentiment dictionary
Citation:
Angela Charng-Rurng Tsai, Chi-En Wu, Richard Tzong-Han Tsai, Jane Yung-jen Hsu, "Building a Concept-Level Sentiment Dictionary Based on Commonsense Knowledge," IEEE Intelligent Systems, vol. 28, no. 2, pp. 22-30, March-April 2013, doi:10.1109/MIS.2013.25
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