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A Survey Paper on Text Analytics Methods for Classifying Tweets

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Advances in Data Science and Artificial Intelligence (ICDSAI 2022)

Part of the book series: Springer Proceedings in Mathematics & Statistics ((PROMS,volume 403))

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Abstract

Social media has demonstrated to be a strong medium that makes a durable effect on the manner in which individuals communicate and has now turned into a fundamental piece of their lives. Especially with the COVID-19 pandemic, people have taken to social media to voice their thoughts and views on various topics. Twitter ranks highest amongst all the social media platforms, when one wants to exchange ideas and information or express their opinions in the form of text. Hence, tweets are often the most useful in generating a vast amount of data in text source, and hence, it is preferred as a text analytics platform. Text analytics is used for gaining deeper insights from a piece of unstructured text. Specifically, for tweets, it has various applications such as identifying patterns and trends or understanding the thought process of the users. This has resulted in techniques such as sentiment analysis, opinion mining, argument mining, stance detection, and many more. This survey paper discusses the various text analytics methods on tweets with a focused literature survey on sentiment analysis, opinion mining, argument mining, and stance detection.

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Author information

Authors and Affiliations

  1. Department of Electronics Engineering, Veermata Jijabai Technological Institute, Mumbai, India

    Utkarsh Bansod, Dheetilekha Nath, Chanchal Agrawal & Srishti Yadav

  2. Department of Computer Engineering, Veermata Jijabai Technological Institute, Mumbai, India

    Ashwini Dalvi

  3. Department of Electrical Engineering, Veermata Jijabai Technological Institute, Mumbai, India

    Faruk Kazi

Authors
  1. Utkarsh Bansod
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  2. Dheetilekha Nath
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  3. Chanchal Agrawal
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  4. Srishti Yadav
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  5. Ashwini Dalvi
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  6. Faruk Kazi
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Corresponding author

Correspondence to Chanchal Agrawal .

Editor information

Editors and Affiliations

  1. Department of Computer Science & Engineering, Indian Institute of Technology Patna, Patna, Bihar, India

    Rajiv Misra

  2. Department of Computer Science, Central University of Rajasthan, Ajmer, Rajasthan, India

    Nishtha Kesswani

  3. Department of EE Engineering, University of London, London, UK

    Muttukrishnan Rajarajan

  4. Department of ECE, National University of Singapore, Singapore, Singapore

    Bharadwaj Veeravalli

  5. EMLYON Business School, Écully, France

    Imene Brigui

  6. Department of Computer Science, Florida Polytechnic University, Lakeland, FL, USA

    Ashok Patel

  7. Director, Indian Institute of Technology Patna, Bihar, India

    T. N. Singh

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© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

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Bansod, U., Nath, D., Agrawal, C., Yadav, S., Dalvi, A., Kazi, F. (2023). A Survey Paper on Text Analytics Methods for Classifying Tweets. In: Misra, R., et al. Advances in Data Science and Artificial Intelligence. ICDSAI 2022. Springer Proceedings in Mathematics & Statistics, vol 403. Springer, Cham. https://doi.org/10.1007/978-3-031-16178-0_22

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