Challenges with Sentiment Analysis of On-line Micro-texts

Challenges with Sentiment Analysis of On-line Micro-texts

Автор: Ritesh Srivastava, M.P.S. Bhatia

Журнал: International Journal of Intelligent Systems and Applications(IJISA) @ijisa

Статья в выпуске: 7 vol.9, 2017 года.

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With the evolution of World Wide Web (WWW) 2.0 and the emergence of many micro-blogging and social networking sites like Twitter, the internet has become a massive source of short textual messages called on-line micro-texts, which are limited to a few number of characters (e.g. 140 characters on Twitter). These on-line micro-texts are considered as real-time text streams. On-line micro-texts are extremely subjective; they contain opinions about various events, social issues, personalities, and products. However, despite being so voluminous in quantity, the qualitative nature of these micro-texts is very inconsistent. These qualitative inconsistencies of raw on-line micro-texts impose many challenges in sentiment analysis of on-line micro-texts by using the established methods of sentiment analysis of unstructured reviews. This paper presents many challenges and issues observed during sentiment analysis of On-line Micro-texts.

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Sentiment analysis, On-line micro-texts, Natural language processing, Text Mining, Machine learning

Короткий адрес: https://sciup.org/15010947

IDR: 15010947

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