BotMoE: Twitter Bot Detection with Community-Aware Mixtures of Modal-Specific Experts

Author:

Liu Yuhan1ORCID,Tan Zhaoxuan1ORCID,Wang Heng1ORCID,Feng Shangbin2ORCID,Zheng Qinghua1ORCID,Luo Minnan1ORCID

Affiliation:

1. Xi'an Jiaotong University, Xi'an, China

2. University of Washington, Seattle, WA, USA

Funder

Innovative Research Group of the National Natural Science Foundation of China

National Nature Science Foundation of China

National Key Research and Development Program of China

Publisher

ACM

Reference74 articles.

1. Detect Me If You Can: Spam Bot Detection Using Inductive Representation Learning

2. SEBD: A Stream Evolving Bot Detection Framework with Application of PAC Learning Approach to Maintain Accuracy and Confidence Levels

3. Hangbo Bao , Wenhui Wang , Li Dong , Qiang Liu , Owais Khan Mohammed , Kriti Aggarwal, Subhojit Som, and Furu Wei. 2021 . Vlmo : Unified vision-language pre-training with mixture-of-modality-experts. arXiv preprint arXiv:2111.02358 (2021). Hangbo Bao, Wenhui Wang, Li Dong, Qiang Liu, Owais Khan Mohammed, Kriti Aggarwal, Subhojit Som, and Furu Wei. 2021. Vlmo: Unified vision-language pre-training with mixture-of-modality-experts. arXiv preprint arXiv:2111.02358 (2021).

4. Florian Brachten , Stefan Stieglitz , Lennart Hofeditz , Katharina Kloppenborg , and Annette Reimann . 2017. Strategies and Influence of Social Bots in a 2017 German state election-A case study on Twitter. arXiv preprint arXiv:1710.07562 ( 2017 ). Florian Brachten, Stefan Stieglitz, Lennart Hofeditz, Katharina Kloppenborg, and Annette Reimann. 2017. Strategies and Influence of Social Bots in a 2017 German state election-A case study on Twitter. arXiv preprint arXiv:1710.07562 (2017).

5. Debot: Twitter bot detection via warped correlation;Chavoshi Nikan;Icdm,2016

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