"An iterative topic model filtering framework for short and noisy ..."

Gillian Kant et al. (2025)

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DOI: 10.1007/S41060-022-00321-4

access: closed

type: Journal Article

metadata version: 2025-11-02

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  - https://dblp.org/rec/journals/ijdsa/KantWWKLS25
Gillian Kant, Levin Wiebelt, Christoph Weisser, Krisztina Kis-Katos, Mattias Luber, Benjamin Säfken:
An iterative topic model filtering framework for short and noisy user-generated data: analyzing conspiracy theories on twitter. Int. J. Data Sci. Anal. 20(2): 269-289 (2025)

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