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Extracting Emotion Quotient of Viral Information Over Twitter

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Distributed Computing and Intelligent Technology (ICDCIT 2022)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 13145))

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Abstract

In social media platforms, a viral information or trending term draws attention, as it asserts potential user content towards topic/terms and sentiment flux. In real-time sentiment analysis, this viral information deliver potential insights, as encompass sentiment and co-located ranges of emotions be useful for the analysis and decision support. A traditional sentiment analysis tool generates the level of predefined sentiments over social media content for the defined duration and lacks in the extraction of emotional impact created by the same. In these settings, it is a multifaceted task to estimate precisely the emotional quotient viral information creates. The proposed novel algorithm aims, to (i) extract the sentiment and co-located emotions quotient of viral information and (ii) utilities for comprehensive comparison on co-occurring viral informations, and sentiment analysis over Twitter text data. The generated emotion quotients and micro-sentiment reveals several valuable insight of a viral topic and assists in decision support. A use-case analysis over real-time extracted data asserts significant insights, as generated sentiments and emotional effects reveals co-relations caused by viral/trending information. The algorithm delivers an efficient, robust, and adaptable solution for the sentiment analysis also.

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Authors and Affiliations

  1. National Institute of Technology, Surathkal, India

    Pawan Kumar & Reiben Eappen Reji

  2. National Institute of Technology, Kurukshetra, India

    Vikram Singh

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  1. Pawan Kumar
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  2. Reiben Eappen Reji
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  3. Vikram Singh
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Correspondence to Vikram Singh .

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Editors and Affiliations

  1. International Institute of Information Technology, Hyderabad, India

    Raju Bapi

  2. Michigan State University, East Lansing, MI, USA

    Sandeep Kulkarni

  3. Ericsson India Global Services Private Ltd., Bangalore, India

    Swarup Mohalik

  4. Indian Institute of Technology Hyderabad, Kandi, Telangana, India

    Sathya Peri

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Kumar, P., Reji, R.E., Singh, V. (2022). Extracting Emotion Quotient of Viral Information Over Twitter. In: Bapi, R., Kulkarni, S., Mohalik, S., Peri, S. (eds) Distributed Computing and Intelligent Technology. ICDCIT 2022. Lecture Notes in Computer Science(), vol 13145. Springer, Cham. https://doi.org/10.1007/978-3-030-94876-4_15

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  • DOI: https://doi.org/10.1007/978-3-030-94876-4_15

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