Sentiment Analysis of Tweets Mentioning Research Articles in Medicine and Psychiatry Disciplines

  • Sampathkumar Kuppan Bharathwaj
  • Jin-Cheon NaEmail author
  • Babu Sangeetha
  • Eswaran Sarathkumar
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11853)


Recently altmetrics (short for alternative metrics) are gaining popularity among researchers to identify the impact of scholarly publications among the general public. Although altmetrics have been widely used nowadays, there has been a limited number of studies analyzing users’ sentiments towards these scholarly publications on social media platforms. In this paper, we analyzed and compared user sentiments (positive, negative and neutral) towards scholarly publications in Medicine and Psychiatry domains by analyzing user-generated content (tweets) on Twitter. We explored various machine learning algorithms, and constructed the best model with Support Vector Machine (SVM) which gave an accuracy of 91.6%.


Altmetrics Twitter Medicine Psychiatry Sentiment analysis Text classification 


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Sampathkumar Kuppan Bharathwaj
    • 1
  • Jin-Cheon Na
    • 1
    Email author
  • Babu Sangeetha
    • 1
  • Eswaran Sarathkumar
    • 1
  1. 1.Wee Kim Wee School of Communication and InformationNanyang Technological UniversitySingaporeSingapore

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