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CommuniMents: A Framework for Detecting Community Based Sentiments for Events

CommuniMents: A Framework for Detecting Community Based Sentiments for Events

Muhammad Aslam Jarwar, Rabeeh Ayaz Abbasi, Mubashar Mushtaq, Onaiza Maqbool, Naif R. Aljohani, Ali Daud, Jalal S. Alowibdi, J.R. Cano, S. García, Ilyoung Chong
Copyright: © 2021 |Pages: 23
ISBN13: 9781799890201|ISBN10: 1799890201|EISBN13: 9781799890218
DOI: 10.4018/978-1-7998-9020-1.ch019
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MLA

Jarwar, Muhammad Aslam, et al. "CommuniMents: A Framework for Detecting Community Based Sentiments for Events." Research Anthology on Strategies for Using Social Media as a Service and Tool in Business, edited by Information Resources Management Association, IGI Global, 2021, pp. 382-404. https://doi.org/10.4018/978-1-7998-9020-1.ch019

APA

Jarwar, M. A., Abbasi, R. A., Mushtaq, M., Maqbool, O., Aljohani, N. R., Daud, A., Alowibdi, J. S., Cano, J., García, S., & Chong, I. (2021). CommuniMents: A Framework for Detecting Community Based Sentiments for Events. In I. Management Association (Ed.), Research Anthology on Strategies for Using Social Media as a Service and Tool in Business (pp. 382-404). IGI Global. https://doi.org/10.4018/978-1-7998-9020-1.ch019

Chicago

Jarwar, Muhammad Aslam, et al. "CommuniMents: A Framework for Detecting Community Based Sentiments for Events." In Research Anthology on Strategies for Using Social Media as a Service and Tool in Business, edited by Information Resources Management Association, 382-404. Hershey, PA: IGI Global, 2021. https://doi.org/10.4018/978-1-7998-9020-1.ch019

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Abstract

Social media has revolutionized human communication and styles of interaction. Due to its effectiveness and ease, people have started using it increasingly to share and exchange information, carry out discussions on various events, and express their opinions. Various communities may have diverse sentiments about events and it is an interesting research problem to understand the sentiments of a particular community for a specific event. In this article, the authors propose a framework CommuniMents which enables us to identify the members of a community and measure the sentiments of the community for a particular event. CommuniMents uses automated snowball sampling to identify the members of a community, then fetches their published contents (specifically tweets), pre-processes the contents and measures the sentiments of the community. The authors perform qualitative and quantitative evaluation for a variety of real world events to validate the effectiveness of the proposed framework.

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