A Framework for Mining Thai Public Opinions
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Publication Details
Author list: Deerosejanadej C., Prom-on S., Achalakul T.
Publisher: Hindawi
Publication year: 2016
Start page: 339
End page: 355
Number of pages: 17
ISBN: 9780128093467; 9780128053942
ISSN: 0146-9428
eISSN: 1745-4557
Languages: English-Great Britain (EN-GB)
Abstract
User-generated textual opinions strongly influence humans' beliefs and decisions. Due to the rapid growth of social data, readers cannot capture major opinions on particular topics by reading through all texts. To provide informative supporting evidence for sentiment analysis results, we integrate an opinion summarization framework into a Data and Opinion Mining (DOM) engine, which is an extension of a mobile Big Data analytics engine for mining Thai public opinions (XDOM). This opinion summarization framework is based on a modified genetic sentence clustering and sentence selection. This chapter presents the development of XDOM, which takes in data from multiple well-known social network sources, and then processes them using MapReduce, a keyword-based sentiment analysis technique, a clustering-based text summarization, and an influencer analysis algorithm. The XDOM engine is capable of identifying overall sentiments, representative text summaries, and influential authors of certain topics. The system's sentiment prediction accuracy was evaluated by matching the predicted result with human sentiment and tested in various case studies. The effectiveness of both approaches demonstrates the practical applications of the engine. ฉ 2016 Elsevier Inc. All rights reserved.
Keywords
MapReduce, opinion mining, opinion summarization, public sentiment, sentence clustering
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