Phonetic-based microtext normalization for Twitter sentiment analysis
Conference Publication ResearchOnline@JCUAbstract
The proliferation of Web 2.0 technologies and the increasing use of computer-mediated communication resulted in a new form of written text, termed microtext. This poses new challenges to natural language processing tools which are usually designed for well-written text. This paper proposes a phonetic-based framework for normalizing microtext to plain English and, hence, improve the classification accuracy of sentiment analysis. Results demonstrated that there is a high (>0.8) similarity index between tweets normalized by our model and tweets normalized by human annotators in 85.31% of cases, and that there is an accuracy increase of >4% in terms of polarity detection after normalization.
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Publication Name
IEEE International Conference on Data Mining Workshops, ICDMW
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ISBN/ISSN
2375-9259
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Pages Count
7
Location
New Orleans, LA, USA
Publisher
Institute of Electrical and Electronics Engineers
Publisher Url
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Publisher Location
Piscataway, NJ, USA
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Date
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EISSN
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DOI
10.1109/ICDMW.2017.59