Analyzing public sentiment toward economic stimulus using natural language processing
Mohammad Ashraful Ferdous Chowdhury,
Mohammad Abdullah,
Mousa Albashrawi
Abstract:Purpose
This study aims to investigate public sentiment toward economic stimulus using textual analysis. Specifically, it analyzes Twitter’s public opinion, emotion-based sentiment and topics related to COVID-19 economic stimulus packages.
Design/methodology/approach
This study applies natural language processing techniques, such as sentiment analysis, t-distributed stochastic neighbor embedding and semantic network analysis, to a global data set of 88,441 tweets from January 2020 to December 2021 extracted … Show more
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