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International Conference on Intelligent Technologies and Applications

INTAP 2019: Intelligent Technologies and Applications pp 309–321Cite as

Classification of Social Media Users Based on Disagreement and Stance Analysis

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1198))

Abstract

Analyzing conversational behavior is a primary task in the field of sentiment analysis. Different researchers have proposed their models to perform the sentiment analysis of social media discussions. Existing approaches mainly studying the conversational behavior based on the text in the conversation. In any discussion, the users could have different viewpoints about the topic of conversation. A user can agree or disagree on the topic of discussion. Agreement of a user to the topic is called a stance, and if the user disagrees to the topic, we refer it as disagreement. The classification of the users based on stance and disagreement is not a well-researched area, and need to be explored further. In this work, we have proposed a computational model to classify the members according to stance or disagreement. The proposed model uses the novel approach, and it is a hybrid of topic modeling and VADER (Valence Aware Dictionary and sEntiment Reasoner). To evaluate the proposed model, we have conducted an experiment, and we did use the WhatsApp group discussion, Facebook comments as a dataset. We also compared the proposed model with two baseline approach, topic modeling, and VADER. From the results, we can conclude that the proposed model can effectively classify social media users based on disagreement and stance.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Sir Syed Science College, Tipu Road, Rawalpindi, Pakistan

    Farhad Muhammad Riaz

  2. University Institute of Information Technology, PMAS-AAUR, Rawalpindi, Pakistan

    Sarfraz Bibi

  3. SERL Sweden, Blekinge Institute of Technology, Karlskrona, Sweden

    Nasir Mahmood Minhas

  4. Foundation University Rawalpindi, New Lalazar, Pakistan

    Waqas Ahmed

Authors
  1. Farhad Muhammad Riaz
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  2. Nasir Mahmood Minhas
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  3. Sarfraz Bibi
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  4. Waqas Ahmed
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Corresponding authors

Correspondence to Farhad Muhammad Riaz or Nasir Mahmood Minhas .

Editor information

Editors and Affiliations

  1. Islamia University of Bahawalpur, Baghdad, Pakistan

    Imran Sarwar Bajwa

  2. Metropolitan University, Belgrade, Serbia

    Tatjana Sibalija

  3. University of Technology Malaysia, Johor Bahru, Malaysia

    Dayang Norhayati Abang Jawawi

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Riaz, F.M., Minhas, N.M., Bibi, S., Ahmed, W. (2020). Classification of Social Media Users Based on Disagreement and Stance Analysis. In: Bajwa, I., Sibalija, T., Jawawi, D. (eds) Intelligent Technologies and Applications. INTAP 2019. Communications in Computer and Information Science, vol 1198. Springer, Singapore. https://doi.org/10.1007/978-981-15-5232-8_27

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  • DOI: https://doi.org/10.1007/978-981-15-5232-8_27

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