  Town hall-type debates are increasingly moving online, irrevocably
transforming public discourse. Yet, we know relatively little about crucial
social dynamics that determine which arguments are more likely to be
successful. This study investigates the impact of one's position in the
discussion network created via responses to others' arguments on one's
persuasiveness in unfacilitated online debates. We propose a novel framework
for measuring the impact of network position on persuasiveness, using a
combination of social network analysis and machine learning. Complementing
existing studies investigating the effect of linguistic aspects on
persuasiveness, we show that the user's position in a discussion network
influences their persuasiveness online. Moreover, the recognition of successful
persuasion further increases this dominant network position. Our findings offer
important insights into the complex social dynamics of online discourse and
provide practical insights for organizations and individuals seeking to
understand the interplay between influential positions in a discussion network
and persuasive strategies in digital spaces.
