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Sentiment Analytics: Extraction of Challenging Influencing Factors from COVID-19 Pandemics

Mahmoud Oglah Al Hasan Baniata*, Sohail Asghar

Department of Computer Science, COMSAT University, Islamabad, Pakistan

* Corresponding Author: Mahmoud Oglah Al Hasan Baniata. Email: email

Intelligent Automation & Soft Computing 2021, 30(3), 821-836.


The advancement in electronic devices and communication technologies in social media have introduced major changes in today’s communication and people have accepted such communicational habits at a rapid pace. The changes involve the way people started interacting with each other, and modern mean of discovering new groups of people, and individuals with similar mindsets, mutual interests, and ideas to share with. As far as the communities are concerned, there are so many social drives (such as “Say No to Plastic”) that need to be discussed on a certain platform for their promotion. Although, it’s quit is challenging, but with the advancement of communication technologies propagations and the increasing engagement of the youth on social media towards social drives made this achievable. There exists a need to examine the influencing factors that peoples express when such drives are promoted on any social media forum in order to evaluate their sentiments. The objective of this research is to explore the influencing factors of pandemic Corona Virus Disease 2019 (COVID-19) when it has been promoted as a social drive on social media forums. In this research effort, sentiment analysis along with novel similarity measures such as THINKMAP, VADER++ and lexicons have been utilized to analyze the influencing factors of those peoples who are affected by COVID-19 when social media forums promote it as a common social drive. The significance of this research is that it would help to demonstrate that participation of youth of different countries could boost up the promotion of social drives and fasten the process which leads towards the positive awareness about any common social drive. Moreover, it would cover the gap of common issues on social media that are not in practice in past studies. It also strengthens the awareness phenomena in youth beyond boundaries. From the experimental results and discussion, it has been observed that the proposed research performed well in term of accuracy.


Cite This Article

APA Style
Baniata, M.O.A.H., Asghar, S. (2021). Sentiment analytics: extraction of challenging influencing factors from COVID-19 pandemics. Intelligent Automation & Soft Computing, 30(3), 821-836.
Vancouver Style
Baniata MOAH, Asghar S. Sentiment analytics: extraction of challenging influencing factors from COVID-19 pandemics. Intell Automat Soft Comput . 2021;30(3):821-836
IEEE Style
M.O.A.H. Baniata and S. Asghar, "Sentiment Analytics: Extraction of Challenging Influencing Factors from COVID-19 Pandemics," Intell. Automat. Soft Comput. , vol. 30, no. 3, pp. 821-836. 2021.

cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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