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

ABSTRACT

Ephemeral 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.

Acknowledgments

The author expresses gratitude to the associate editor, Dr. Marko Bachl, and the three anonymous reviewers for the thorough and constructive review process.

Disclosure statement

No potential conflict of interest was reported by the author.

Notes

¹ Public chat groups on Telegram are referred to as Groups and public channels are called Channels from hereon.

² The online appendix, pre-processed message metadata and replication code for this study are available via OSF: https://osf.io/b7x3p/.

Additional information

Funding

This work was supported by the German Federal Ministry of Education and Research under grant numbers 16DII125, 16DII135 and 13N16049 (in the context of the call for proposals ‘civil security - societies in transition’).

Notes on contributors

Kilian Buehling

Kilian Buehling is a doctoral researcher in the research group Digitalization and the Transnational Public Sphere at the Weizenbaum Institute for the Networked Society, Berlin, and the Institute for Media and Communication Studies, Freie Universität Berlin. His previous work contains research in information science, quantitative innovation economics and scientometrics.