Abstract

We present a comprehensive overview of the challenges and opportunities in social bot detection in the context of the rise of sophisticated AI-based chatbots. By examining the state of the art in social bot detection techniques and the more salient real-world application to date, we identify gaps and emerging trends in the field, with a focus on addressing the unique challenges posed by AI-generated conversations and behaviors. We suggest potentially promising opportunities and research directions in social bot detection, including (i) the use of generative agents for synthetic data generation, testing and evaluation;(ii) the need for multimodal and cross-platform detection based on network and behavioral signatures of coordination and influence;(iii) the opportunity to extend bot detection to non-English and low-resource language settings; and,(iv) the room for development of collaborative, federated learning detection models that can help facilitate cooperation between different organizations and platforms while preserving user privacy.

Date

June 15, 2023

Authors

Emilio Ferrara

Journal

First Monday

Volume

28

Issue

6