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

Autor:	Kwan, Jolin Shaynn-Ly, Lim, Kwan Hui
Rok vydání:	2021
Předmět:	Computer Science - Social and Information Networks Computer Science - Computers and Society Computer Science - Information Retrieval
Druh dokumentu:	Working Paper
Popis:	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. Comment: Accepted to the 26th International Conference on Intelligent User Interfaces (IUI'21), Demo Track
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2103.01472 Zobrazit plný text záznamu View this record from Arxiv