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Entity Level Contextual Sentiment Detection of Topic Sensitive Influential Twitterers Using SentiCircles

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Data Engineering and Intelligent Computing

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 542 ))

Abstract

Sentiment analysis, when combined with the vast amounts of data present in the social networking domain like Twitter data, becomes a powerful tool for opinion mining. In this paper we focus on identifying ‘the most influential sentiment’ for topics extracted from tweets using Latent Dirichlet Allocation (LDA) method. The most influential twitterers for various topics are identified using the TwitterRank algorithm. Then a SentiCircle based approach is used for capturing the dynamic context based entity level sentiment.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, TKM College of Engineering, Kollam, Kerala, India

    Reshma Sheik, Sebin S. Philip, Arjun Sajeev, Sinith Sreenivasan & Georgin Jose

Authors
  1. Reshma Sheik
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  2. Sebin S. Philip
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  3. Arjun Sajeev
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  4. Sinith Sreenivasan
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  5. Georgin Jose
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Corresponding author

Correspondence to Reshma Sheik .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Anil Neerukonda Institute of Technology and Sciences, Visakhapatnam, Andhra Pradesh, India

    Suresh Chandra Satapathy

  2. Shri Ramswaroop Memorial Group of Professional Colleges (SRMGPC), Lucknow, Uttar Pradesh, India

    Vikrant Bhateja

  3. Department of Computer Science and Engineering, CMR Technical Campus, Hyderabad, India

    K. Srujan Raju

  4. DVR and Dr. HS MIC College of Technology, Kanchikacherla, Andhra Pradesh, India

    B. Janakiramaiah

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© 2018 Springer Nature Singapore Pte Ltd.

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Sheik, R., Philip, S.S., Sajeev, A., Sreenivasan, S., Jose, G. (2018). Entity Level Contextual Sentiment Detection of Topic Sensitive Influential Twitterers Using SentiCircles. In: Satapathy, S., Bhateja, V., Raju, K., Janakiramaiah, B. (eds) Data Engineering and Intelligent Computing. Advances in Intelligent Systems and Computing, vol 542 . Springer, Singapore. https://doi.org/10.1007/978-981-10-3223-3_19

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  • DOI: https://doi.org/10.1007/978-981-10-3223-3_19

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-3222-6

  • Online ISBN: 978-981-10-3223-3

  • eBook Packages: EngineeringEngineering (R0)

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