Sentiment Analysis: Retrieving Positive Or Negative Polarities in News Articles Using Information Agents
In this research, a sentiment analysis approach is proposed to extract sentiments associated with positive or negative polarities in news articles. Information retrieval agents were implemented to capture important keywords from the unstructured data such as news, distinguished the keywords into positive or negative lexicons, rank those keywords based on the frequency of occurrences, and recommend the news articles as positive or negative to the users. The proposed approach is illustrated with experimental results and their main implications are discussed.
Yu, V. W., Lea, B., & Guruswamy, B. (2006). Sentiment Analysis: Retrieving Positive Or Negative Polarities in News Articles Using Information Agents. Proceedings of the 37th Annual Conference of Decision Sciences Institute.
37th Annual Conference of Decision Sciences Institute
Business and Information Technology
Keywords and Phrases
Information Agent; Sentiment Analysis; Text Mining
Article - Conference proceedings
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