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Emotion Detection from Social Media Using Machine Learning Techniques: A Survey

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Applied Information Processing Systems

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1354))

Abstract

The work carried out in this paper is to overview and compare various sentiment analysis methodologies and approaches in detail and also discuss the limitations of existing work and future direction about sentiment analysis methodologies. The main goal of sentiment analysis for market prediction is to recognize the customer's opinion about the available products. The work carried out in this paper is to overview and compare various sentiment analysis methodologies and approaches in detail with Sentiment Emotion Detection (SED) and also discuss the limitations of existing work and future direction about sentiment analysis methodologies on SED. The main goal of sentiment analysis for market prediction is to recognize the customer's opinion about the available products. It can pave the way for improvement and prevent future defects and flaws. The tools for identifying and classifying opinion communicated in a bit of text, in sound, or video formats indicate whether the creator's mood toward a specific issue, thread, item, and so on is positive, negative, or neutral. Human emotions are limited to being positive or negative. Still, it has more categories like happiness, sadness, joy, disgust, surprise, depression, frustration, anger, fear, confidence, trust, anticipation, shame, kindness, love, friendship, faith, and wonder. Analyzing people's comments/emotions is essential for the country, business, or individuals for their existence, which gives the researcher motivation on sentiment analysis on emotion detection.

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Author information

Authors and Affiliations

  1. RCPET’s Institute of Management Research and Development, Shirpur, India

    Vijaya Ahire

  2. SSVPSs. Late Karmveer Dr. P. R. Ghogrey Science College, Dhule, India

    Swati Borse

Authors
  1. Vijaya Ahire
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  2. Swati Borse
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Editor information

Editors and Affiliations

  1. Department of Electronics and Telecommunications Engineering, Dr. Babasaheb Ambedkar Technological University, Lonere, India

    Brijesh Iyer

  2. Department of Electronics and Computer Engineering, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India

    Debashis Ghosh

  3. Department of Automatics and Applied Software, Aurel Vlaicu University of Arad, Arad, Romania

    Valentina Emilia Balas

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© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Ahire, V., Borse, S. (2022). Emotion Detection from Social Media Using Machine Learning Techniques: A Survey. In: Iyer, B., Ghosh, D., Balas, V.E. (eds) Applied Information Processing Systems . Advances in Intelligent Systems and Computing, vol 1354. Springer, Singapore. https://doi.org/10.1007/978-981-16-2008-9_8

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