Message Deletion on Telegram: Affected Data Types and Implications for Computational Analysis

dc.contributor.authorBühling, Kilian
dc.date.accessioned2023-08-28T13:49:03Z
dc.date.available2023-08-28T13:49:03Z
dc.date.issued2023
dc.description.abstractEphemeral digital trace data can decrease the completeness, reproducibility, and reliability of social media datasets. Systematic post deletions thus potentially bias the results of computational methods used to map actors, content, and online information diffusion. Therefore, the aim of this study was to assess the extent and distribution of message deletion across different data types using data from the hybrid messenger service Telegram, which has experienced an influx of deplatformed users from mainstream social media platforms. A repeatedly scraped sample of messages from public Telegram groups and channels was used to investigate the effect of message ephemerality on the consistency of Telegram datasets. The findings revealed that message deletion introduces biases to the computational collection and analysis of Telegram data. Further, message ephemerality reduces dataset consistency, the quality of social network analyses, and the results of computational content analysis methods, such as topic modeling or dictionaries. The implications of these findings for scholars aiming to use Telegram data for computational research, possible solutions, and contributions to the methodological advancement of studying online political communication are discussed further in this article.
dc.identifier.citationBuehling, K. (2024). Message Deletion on Telegram: Affected Data Types and Implications for Computational Analysis. Communication Methods and Measures, 18(1), 92–114. https://doi.org/10.1080/19312458.2023.2183188
dc.identifier.doihttps://doi.org/10.1080/19312458.2023.2183188
dc.identifier.urihttps://doi.org/10.1080/19312458.2023.2183188
dc.identifier.urihttps://www.weizenbaum-library.de/handle/id/47
dc.language.isoeng
dc.publisherTaylor & Francis
dc.relation.issupplementedbyhttps://www.weizenbaum-library.de/handle/id/383
dc.rightsopen access
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectTelegram
dc.subjectnetwork analysis
dc.subjectcomputational research
dc.subjectpolitical communication
dc.subject.ddc004 Informatik
dc.subject.ddc300 Sozialwissenschaften
dc.titleMessage Deletion on Telegram: Affected Data Types and Implications for Computational Analysis
dc.typeArticle
dc.type.statuspublishedVersion
dcmi.typeText
dcterms.bibliographicCitation.issue1
dcterms.bibliographicCitation.journaltitleCommunication Methods and Measures
dcterms.bibliographicCitation.pageend114
dcterms.bibliographicCitation.pagestart92
dcterms.bibliographicCitation.volume18
local.researchgroupDynamiken der digitalen Mobilisierungde
local.researchtopicDigitale Märkte und Öffentlichkeiten auf Plattformen
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