SIAICYLGMar 30, 2023

Demystifying Misconceptions in Social Bots Research

arXiv:2303.17251v428 citationsh-index: 49
Originality Synthesis-oriented
AI Analysis

This addresses reliability issues in social bot research for researchers and practitioners, but it is incremental as it critiques existing work without introducing new methods.

The paper tackles widespread biases and misconceptions in social bot research, identifying methodological and conceptual issues and providing directions for sounder methodologies.

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. Here, we discuss a broad set of consequential methodological and conceptual issues that affect current social bots research, illustrating each with examples drawn from recent studies. More importantly, we demystify common misconceptions, addressing fundamental points on how social bots research is discussed. Our analysis surfaces the need to discuss research about online disinformation and manipulation in a rigorous, unbiased, and responsible way. This article bolsters such effort by identifying and refuting common fallacious arguments used by both proponents and opponents of social bots research, as well as providing directions toward sound methodologies for future research.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes