Natural language processing for sentiment analysis: an exploratory analysis on tweets

Wei Yen Chong, Bhawani Selvaretnam, Lay Ki Soon

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

16 Citations (Scopus)

Abstract

In this paper, we present our preliminary experiments on tweets sentiment analysis. This experiment is designed to extract sentiment based on subjects that exist in tweets. It detects the sentiment that refers to the specific subject using Natural Language Processing techniques. To classify sentiment, our experiment consists of three main steps, which are subjectivity classification, semantic association, and polarity classification. The experiment utilizes sentiment lexicons by defining the grammatical relationship between sentiment lexicons and subject. Experimental results show that the proposed system is working better than current text sentiment analysis tools, as the structure of tweets is not same as regular text.

Original languageEnglish
Title of host publicationProceedings - 2014 4th International Conference on Artificial Intelligence with Applications in Engineering and Technology, ICAIET 2014
EditorsDavid Al-Dabass, Ismail Saad, Khairul Anuar Mohamad, Mohd Hanafi Ahmad Hijazi
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages212-217
Number of pages6
ISBN (Electronic)9781479979103
DOIs
Publication statusPublished - 2014
Externally publishedYes
EventInternational Conference on Artificial Intelligence with Applications in Engineering and Technology 2014 - Kota Kinabalu, Sabah, Malaysia
Duration: 2 Dec 20145 Dec 2014
Conference number: 4th
https://ieeexplore.ieee.org/xpl/conhome/7347855/proceeding (Proceedings)

Conference

ConferenceInternational Conference on Artificial Intelligence with Applications in Engineering and Technology 2014
Abbreviated titleICAIET 2014
Country/TerritoryMalaysia
CityKota Kinabalu, Sabah
Period2/12/145/12/14
Internet address

Keywords

  • Natural Language Processing
  • Sentiment Analysis
  • Tweets

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