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Demystifying Misconceptions in Social Bots Research
March 28, 2024, 4:43 a.m. | Stefano Cresci, Kai-Cheng Yang, Angelo Spognardi, Roberto Di Pietro, Filippo Menczer, Marinella Petrocchi
cs.LG updates on arXiv.org arxiv.org
Abstract: Research on social bots aims at advancing knowledge and providing solutions to one of the most debated forms of online manipulation. Yet, social bot research is plagued by widespread biases, hyped results, and misconceptions that set the stage for ambiguities, unrealistic expectations, and seemingly irreconcilable findings. Overcoming such issues is instrumental towards ensuring reliable solutions and reaffirming the validity of the scientific method. In this contribution, we review some recent results in social bots research, …
abstract arxiv biases bot bots cs.ai cs.cy cs.lg cs.si forms knowledge manipulation research results set social solutions stage type
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