Schulze H., Buehling, K., Zehring, M. (forthcoming). The Telegram COVID-19 Protest Dataset 2020–2022. Computational Communication Research.
Schindler, J., Jha, S., Zhang, X., Buehling, K., Heft, A., & Barahona, M. (2025). LGDE: Local Graph-based Dictionary Expansion. Computational Linguistics, 1–32. https://doi.org/10.1162/coli_a_00562
Buehling, K., Zhang, X., & Heft, A. (2025). Veiled conspiracism: Particularities and convergence in the styles and functions of conspiracy-related communication across digital platforms. New Media & Society, 0(0). https://doi.org/10.1177/14614448251315756
Heft, A., Buehling, K., Zhang, X., Schindler, D., & Milzner, M. (2024). Challenges of and approaches to data collection across platforms and time: Conspiracy-related digital traces as examples of political contention. Journal of Information Technology & Politics, 21(3), 323–339. https://doi.org/10.1080/19331681.2023.2250779
Buehling, 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
Buehling, K., & Heft, A. (2023). Pandemic Protesters on Telegram: How Platform Affordances and Information Ecosystems Shape Digital Counterpublics. Social Media + Society, 9(3), 20563051231199430. https://doi.org/10.1177/20563051231199430
Jost, P., Heft, A., Buehling, K., Zehring, M., Schulze, H., Bitzmann, H., & Domahidi, E. (2023). Mapping a Dark Space: Challenges in Sampling and Classifying Non- Institutionalized Actors on Telegram. M&K Medien & Kommunikationswissenschaft, 71(3–4), 212–229. https://doi.org/10.5771/1615-634X-2023-3-4-212
Heft, A., & Buehling, K. (2022). Measuring the diffusion of conspiracy theories in digital information ecologies. Convergence, 13548565221091808. https://doi.org/10.1177/13548565221091809
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