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Amplifying the Polarity Categorization on Twitter Data Using Tweet Polarizer Algorithm and Emoticons Score

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Evolution in Computational Intelligence

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1176))

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Abstract

Mining is utilized to help individuals to separate important data from huge amount of information. Opinion Mining or Sentiment Analysis concentrates on the exploration and grasp of the feelings from the content generated in social media. It recognizes the supposition or attitude that an individual has towards a point or an article and it looks to distinguish the perspective hidden in the large content range. Knowing clients’ sentiments and giving the best arrangement or administration is an outstanding business sector procedure pursued by each business. In this paper, we center around producing polarities of tweets to know the general feeling on a given word or a trump card string. An algorithm Tweet Polarizer is used in this paper to categorize the tweets. A couple of NLP procedures are used to develop a superior methodology for making the most appropriate and possible fringe for a given tweet and to imagine the few trademark features of customers like from which area he has posted the tweet and when.

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Authors and Affiliations

  1. Gudlavalleru Engineering College, Gudlavalleru, AP, India

    D. N. V. S. L. S. Indira & J. N. V. R. Swarup Kumar

Authors
  1. D. N. V. S. L. S. Indira
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  2. J. N. V. R. Swarup Kumar
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Corresponding author

Correspondence to D. N. V. S. L. S. Indira .

Editor information

Editors and Affiliations

  1. Department of Electronics and Communication Engineering, Shri Ramswaroop Memorial Group of Professional Colleges (SRMGPC), Lucknow, Uttar Pradesh, India

    Vikrant Bhateja

  2. Department of Computer Science and Information Engineering, National Dong Hwa University, Hualien, Taiwan

    Sheng-Lung Peng

  3. School of Computer Engineering, Kalinga Institute of Industrial Technology (KIIT), Bhubaneswar, Odisha, India

    Suresh Chandra Satapathy

  4. Department of Informatics, University of Leicester, Leicester, UK

    Yu-Dong Zhang

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© 2021 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Indira, D.N.V.S.L.S., Kumar, J.N.V.R.S. (2021). Amplifying the Polarity Categorization on Twitter Data Using Tweet Polarizer Algorithm and Emoticons Score. In: Bhateja, V., Peng, SL., Satapathy, S.C., Zhang, YD. (eds) Evolution in Computational Intelligence. Advances in Intelligent Systems and Computing, vol 1176. Springer, Singapore. https://doi.org/10.1007/978-981-15-5788-0_31

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