CoV2eX: A COVID-19 Website with Region-wise Sentiment Classification using the Top Trending Social Media Keywords

被引：0
|
作者：
Rajmohan, Akshay [1 ]
Ravi, Akash [1 ]
Aakash, K. O. [1 ]
Adarsh, K. [1 ]
Raj, Anjuna D. [1 ]
Anjali, T. [1 ]
机构：
[1] Amrita Vishwa Vidyapeetham, Dept Comp Sci & Engn, Amritapuri, India
来源：
2021 SIXTH INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS, SIGNAL PROCESSING AND NETWORKING (WISPNET) | 2021年
关键词：
COVID-19; Web development; Sentiment analysis; NLP; Naive Bayes; Psychological support;
D O I：
10.1109/WISPNET51692.2021.9419415
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
The ongoing pandemic has caused several impacts on human life. Social media has become more popular during the pandemic, wherein people share all their thoughts and emotions. Due to the social distancing norms and other preventive measures, people are connecting with each other through this platform. This gave us an occasion to study the overall mental reaction of the public to this disease. To measure the region-wise sentiment value, we used the tweets associated with COVID-19 in this paper. This is then used for the model's training. Then, we generate the average emotion conveyed by each region. This can be beneficial in validating the psychological impact that COVID-19 had on the people, helping governments to take effective actions. The output as well as the COVID-19 guidelines and data are then represented in a website.
引用
收藏
页码：113 / 117
页数：5
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