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Sentiment analysis of tweets and government translations

Assessing China’s post-Covid-19 landscape for signs of withering or booming

Bibliographic Data

ID21215596
AuthorsHuan Wang (0000-0003-3219-7226, Beijing Language and Culture University, corresponding author), Xiaohui Wang (0000-0003-2126-1712, Beijing Language and Culture University)
Year2023
Volume8
Issue2
Pages213-233
Publication date2023-06-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueGlobal Media and China (JOURNAL)
Journal identifiersISSN: 2059-4364 • E-ISSN: 2059-4372
PublisherSAGE Publications (PUBLISHER • US)
DOI10.1177/20594364231181745
OpenAlexW4379383248
LanguageEN
Citations received2
References cited49

This article aims to gain insights into the prevailing public sentiment during the policy relaxation period by examining whether the post-COVID-19 landscape reflects signs of withering or booming conditions. Employing methods from natural language processing (NLP) and machine learning (ML), the analysis reveals a predominance of positive sentiment from December 7, 2022 to May 17, 2023, indicative of an optimistic perspective and a potentially flourishing environment. A predictive model based on logistic regression emerges as a notably effective tool for sentiment prediction, suggesting potential utility in predicting future public health crises. A comparison of sentiments in translations by the government aligns with previous research, revealing a less favorable depiction of translated texts compared to the source texts. Furthermore, the commonality index, a measure of group consensus value, surpasses the typical range, while the certainty index, a measure of confidence, slightly falls below the norm. These findings offer valuable insights for policy considerations while highlighting areas for international communication and understanding improvement

Certainty · China · Consumer confidence index · Data science · Economics · Epistemology · Flourishing · Linguistics · Logistic regression · Machine learning · Macroeconomics · Political science · Sentiment analysis · Computer Science · Law · Medicine · Mental Health via Writing · Misinformation and Its Impacts · Psychology · Sentiment Analysis and Opinion Mining · Social Psychology · Artificial Intelligence

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Unique citing works2
Citations per year1
Citation span2024 - 2026 (3)
Citation velocitycurrent
Highly citedNo
Citation typesNeutral: 2

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