A Two-Phase Framework for Detecting Manipulation Campaigns in Social Media
Zusammenfassung
The identification of coordinated campaigns within Social Media is a complex task that is often hindered by missing labels and large amounts of data that have to be processed. We propose a new two-phase framework that uses unsupervised stream clustering for detecting suspicious trends over time in a first step. Afterwards, traditional offline analyses are applied to distinguish between normal trend evolution and malicious manipulation attempts. We demonstrate the applicability of our framework in the context of the final days of the Brexit in 2019/2020.
Schlüsselwörter
Social campaign detection; Stream clustering; Unsupervised learning
Zitieren als
Assenmacher, D., Clever, L., Pohl, J., Trautmann, H., & Grimme, C. (2020). A Two-Phase Framework for Detecting Manipulation Campaigns in Social Media. In Meiselwitz, G. (Ed.), Proceedings of the International Conference on Human-Computer Interaction (HCII 2020): Social Computing and Social Media. Design, Ethics, User Behavior, and Social Network Analysis (pp. 201–214). Cham: Springer International Publishing.Details
Publikationstyp
Forschungsartikel in Sammelband (Konferenz)
Begutachtet
Ja
Publikationsstatus
Veröffentlicht
Jahr
2020
Konferenz
International Conference on Human-Computer Interaction
Konferenzort
Copenhagen
Buchtitel
Proceedings of the International Conference on Human-Computer Interaction (HCII 2020): Social Computing and Social Media. Design, Ethics, User Behavior, and Social Network Analysis
Herausgeber
Meiselwitz G
Erste Seite
201
Letzte Seite
214
Verlag
Springer International Publishing
Ort
Cham
Sprache
Englisch
ISBN
978-3-030-49570-1
DOI