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Title:
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VISUAL TREND ANALYSIS METHOD FOR ONTOLOGY BASED OPINION MINING ON MOVIE REVIEWS |
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Author(s):
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Seongmin Mun, Ginam Kim, Gyeongcheol Choi, Kyungwon Lee |
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ISBN:
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978-989-8533-54-8 |
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Editors:
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Piet Kommers and Guo Chao Peng |
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Year:
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2016 |
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Edition:
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Single |
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Keywords:
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Clustering, Data Visualization, Network, Ontology, Opinion, Polarity |
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Type:
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Poster/Demonstration |
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First Page:
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287 |
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Last Page:
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290 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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The rapid development of the Web 2.0 era has generated a huge amount of online word-of-mouth information, which has influenced the society in various fields. Effects of Word of Mouth on movies, in particular, has become the new standards to evaluate a movie that affects potential audiences decision. Therefore, this research proposes a methodology to analyze the responses of movie audiences in two ways; overall regardless of time flow and trending which reflects the changes of audience opinions over time. Review analysis was conducted through ontology followed by opinion mining, further visualized via polar chart network, clustering and timeline. Visualization designed in this process is presented in http://54.255.190.140/index/v0. |
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