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Winning Arguments: Interaction Dynamics and Persuasion Strategies in Good-faith Online Discussions

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arxiv 1602.01103 v2 pith:EE7AZDZF submitted 2016-02-02 cs.SI cs.CLphysics.soc-ph

classification cs.SIcs.CLphysics.soc-ph
keywords opinionsomeoneinteractionargumentsdifficultdiscussionsdynamicslanguage
verification ladder T0 review T1 audit T2 compute T3 formal
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Changing someone's opinion is arguably one of the most important challenges of social interaction. The underlying process proves difficult to study: it is hard to know how someone's opinions are formed and whether and how someone's views shift. Fortunately, ChangeMyView, an active community on Reddit, provides a platform where users present their own opinions and reasoning, invite others to contest them, and acknowledge when the ensuing discussions change their original views. In this work, we study these interactions to understand the mechanisms behind persuasion. We find that persuasive arguments are characterized by interesting patterns of interaction dynamics, such as participant entry-order and degree of back-and-forth exchange. Furthermore, by comparing similar counterarguments to the same opinion, we show that language factors play an essential role. In particular, the interplay between the language of the opinion holder and that of the counterargument provides highly predictive cues of persuasiveness. Finally, since even in this favorable setting people may not be persuaded, we investigate the problem of determining whether someone's opinion is susceptible to being changed at all. For this more difficult task, we show that stylistic choices in how the opinion is expressed carry predictive power.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. OpenAlex reports about 58 citations worldwide. Full citation record

  1. A Model of Multi-turn Human Persuadability Using Probabilistic Belief Tracing

    cs.CL 2026-06 unverdicted novelty 7.0 of 10

    PERSUASIONTRACE introduces a Bayesian-network simulated target for multi-turn persuasion that matches human belief dynamics (81 vs 80) better than LLM baselines (64) and enables process-level evaluation.

  2. Investigating Subjective Factors of Argument Strength: Storytelling, Emotions, and Hedging

    cs.CL 2025-07 conditional novelty 6.0 of 10

    Storytelling and hedging help subjective persuasion in online debate but hurt objective argument quality, while emotions show mostly domain-independent effects.

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