Persuasion of the Undecided: Language vs. the Listener

Abstract

This paper examines the factors that govern persuasion for a priori UNDECIDED versus DECIDED audience members in the context of on-line debates. We separately study two types of influences: linguistic factors-features of the language of the debate itself; and audience factors-features of an audience member encoding demographic information, prior beliefs, and debate platform behavior. In a study of users of a popular debate platform, we find first that different combinations of linguistic features are critical for predicting persuasion outcomes for UNDECIDED versus DECIDED members of the audience. We additionally find that audience factors have more influence on predicting the side (PRO/CON) that persuaded UNDECIDED users than for DECIDED users that flip their stance to the opposing side. Our results emphasize the importance of considering the undecided and decided audiences separately when studying linguistic factors of persuasion.

Analyzing the Persuasive Effect of Style in News Editorial Argumentation

“…In related work, Lukin et al (2017) found that emotional and rational arguments affect people with different personalities, and Durmus and Cardie (2018) take into account the religious and political ideology of debate portal participants. In followup work, Longpre et al (2019) observed that style is more important for decided listeners. Unlike them, we focus on the stylistic choices made in well-planned argumentative texts.…”

Leveraging Topic Relatedness for Argument Persuasion

“…Representing User Information. Previous work shows that both characteristics of the debaters and the audience and the linguistic features of the debate arguments are important factors in persuasion studies (Lukin et al, 2017;Cardie, 2018, 2019;Longpre et al, 2019). Similar to prior work, to encode the background information, we first represent the user background with one-hot representation (ONE-HOT) to capture the users' selections on the categories (e.g., gender, political ideology, religious ideology, and etc.)…”

Exploring the Role of Argument Structure in Online Debate Persuasion

“…Luu et al (2019) further found that the debater's skill estimated from debate text history is also predictive of convincing the audience. User factors are explored in previous papers Cardie, 2019a, 2018;Longpre et al, 2019), demonstrating the importance of characteristics and beliefs of the audience. Furthermore, Potash and Rumshisky (2017) proposed a recurrent neural network architecture with attention and annotated audience favorability to predict the winner of the debate.…”

“…The user features include opinion similarity for big issues, religious and political ideology match and persuadability score (how likely a person will be persuaded) (Longpre et al, 2019).…”