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TweetCOVID: A System for Analyzing Public Sentiments and Discussions about COVID-19 via Twitter Activities
Conference proceeding

TweetCOVID: A System for Analyzing Public Sentiments and Discussions about COVID-19 via Twitter Activities

Jolin Shaynn-Ly Kwan, Kwan Hui Lim and ACM
Companion Proceedings of the 26th International Conference on Intelligent User Interfaces, pp.58-60
ACM Conferences
IUI '21: 26th International Conference on Intelligent User Interfaces
14/04/2021
DOI: https://doi.org/10.1145/3397482.3450733

Abstract

Applied computing Human-centered computing Information systems Information systems -- Information systems applications
The COVID-19 pandemic has created widespread health and economical impacts, affecting millions around the world. To better understand these impacts, we present the TweetCOVID system that offers the capability to understand the public reactions to the COVID-19 pandemic in terms of their sentiments, emotions, topics of interest and controversial discussions, over a range of time periods and locations, using public tweets. We also present three example use cases that illustrates the usefulness of our proposed TweetCOVID system.

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