Social media analysis
Dynamics of platforms
I’ve analyzed how social media platforms work, and what can be changed in terms of algorithms and design decisions to improve them beyond engagement metrics. I approach this through large-scale data analysis and modelling.
Telegram is an important platform, given its size and use for less visible, more private content-sharing. We parsed and made available a large-scale multimodal (text, audio & video transcriptions) dataset of German-language telegram channels [1]. The underlying 25TB multimodal ETL pipeline (Python, Snakemake, PyTorch, Whisper) achieved a ~250× real-time transcription factor per GPU on whisper/large-v3-turbo through finetuned batching and VAD.
Publications
- Angermaier, M., Hoeldrich, E., Lasser, J., Neto, J.P., 2025. The Schwurbelarchiv: a German Language Telegram dataset for the Study of Conspiracy Theories. DOI:10.48550/arXiv.2504.06318
Dynamics within platforms
I’ve analyzed how certain important societal issues interact with, and are affected by, social media. These include
- how conspiracy theories evolve on German Telegram [1]
- how the discourse around climate change has evolved on Reddit [2]
Publications
- Höldrich, E., Angermaier, M., Lasser, J., Pinheiro-Neto, J., 2025. Characterizing the Dynamics of Conspiracy Related German Telegram Conversations during COVID-19. DOI:10.48550/arXiv.2507.13398
- Di Natale, A., Neto, J.P., Gaupp, F., Eker, S., 2024. The Impact of Fridays for Future on Climate Change Attitudes and Behavior on Reddit. DOI:10.2139/ssrn.4904128