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1 Publikation
2021 | Konferenzbeitrag | FH-PUB-ID: 6951
Luber, M., Weisser, C., Säfken, B., Silbersdorff, A., Kneib, T., & Kis-Katos, K. (2021). Identifying Topical Shifts in Twitter Streams: An Integration of Non-Negative Matrix Factorisation, Sentiment Analysis, and Structural Break Models for Large-Scale Data. In J. Bright, A. Giachanou, V. Spaiser, F. Spezzano, A. George, & A. Pavliuc (Eds.), Disinformation in Open Online Media. MISDOOM 2021 (pp. 33–49). Cham: Springer. https://doi.org/10.1007/978-3-030-87031-7_3
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