SHS Web Conf.
Volume 119, 20213rd International Conference on Quantitative and Qualitative Methods for Social Sciences (QQR’21)
|Number of page(s)||9|
|Section||Technology and Society / Covid-19 Innovations|
|Published online||24 August 2021|
Analysis of sentiments conveyed through Twitter concerning COVID-19
1 Laboratory of Computer Sciences, Ibn Tofail University, Kenitra, Morocco
2 Department of Computer Sciences, Cadi Ayyad University, Marrakesh, Morocco
Due to the social and economic fallout from the COVID-19 pandemic, we sought to gauge the attitudes of social network users, in this case, Twitter, towards the topic using a sentiment analysis approach. We collected 178,683 tweets using the Twitter API based on queries for the high-frequency hashtag #covid19. After the preprocessing step, we classified them in a binary way (positive and negative) and according to their intensity (valence) using the VADER model and then the NRCLex dictionary, which allows us to classify feelings according to their affective class. The results suggest that overall, the feelings detected through the tweets are positive. In addition, users seem to be interestedin the pandemic as a trend rather than as a topic related to other social or economic aspects.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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