Guiding Sentiment Analysis with Hierarchical Text Clustering: Analyzing the German X/Twitter Discourse on Face Masks in the 2020 COVID-19 Pandemic

Silvan Wehrli, Chisom Ezekannagha, Georges Hattab, T. Sonia Boender, Bert Arnrich, Christopher Irrgang

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Abstract

Social media are a critical component of the information ecosystem during public health crises. Understanding the public discourse is essential for effective communication and misinformation mitigation. Computational methods can aid these efforts through online social listening. We combined hierarchical text clustering and sentiment analysis to examine the face mask-wearing discourse in Germany during the COVID-19 pandemic using a dataset of 353,420 German X (formerly Twitter) posts from 2020. For sentiment analysis, we annotated a subsample of the data to train a neural network for classifying the sentiments of posts (neutral, negative, or positive). In combination with clustering, this approach uncovered sentiment patterns of different topics and their subtopics, reflecting the online public response to mask mandates in Germany. We show that our approach can be used to examine long-term narratives and sentiment dynamics and to identify specific topics that explain peaks of interest in the social media discourse.

Original languageEnglish
Title of host publicationProceedings of the 14th Workshop on Computational Approaches to Subjectivity, Sentiment, & Social Media Analysis
EditorsOrphee De Clercq, Valentin Barriere, Jeremy Barnes, Roman Klinger, Joao Sedoc, Shabnam Tafreshi
PublisherAssociation for Computational Linguistics (ACL)
Pages153-167
Number of pages15
ISBN (Electronic)9798891761568
Publication statusPublished - 2024
Event14th Workshop on Computational Approaches to Subjectivity, Sentiment, and Social Media Analysis, WASSA 2024 - Bangkok, Thailand
Duration: 15 Aug 2024 → …

Conference

Conference14th Workshop on Computational Approaches to Subjectivity, Sentiment, and Social Media Analysis, WASSA 2024
Country/TerritoryThailand
CityBangkok
Period15/08/24 → …

Bibliographical note

Publisher Copyright:
© 2024 Association for Computational Linguistics.

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