Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Langua 2015
DOI: 10.3115/v1/n15-1172
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Echoes of Persuasion: The Effect of Euphony in Persuasive Communication

Abstract: While the effect of various lexical, syntactic, semantic and stylistic features have been addressed in persuasive language from a computational point of view, the persuasive effect of phonetics has received little attention. By modeling a notion of euphony and analyzing four datasets comprising persuasive and nonpersuasive sentences in different domains (political speeches, movie quotes, slogans and tweets), we explore the impact of sounds on different forms of persuasiveness. We conduct a series of analyses a… Show more

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Cited by 13 publications
(19 citation statements)
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References 29 publications
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“…There has been a tremendous amount of research effort to understand the important linguistic features for identifying argument structure and determining effective argumentation strategies in monologic text (Mochales and Moens, 2011;Feng and Hirst, 2011;Stab and Gurevych, 2014;Guerini et al, 2015). For example, Habernal and Gurevych (2016) has experimented with different machine learning models to predict which of two arguments is more convincing.…”
Section: Related Work and Datasetsmentioning
confidence: 99%
“…There has been a tremendous amount of research effort to understand the important linguistic features for identifying argument structure and determining effective argumentation strategies in monologic text (Mochales and Moens, 2011;Feng and Hirst, 2011;Stab and Gurevych, 2014;Guerini et al, 2015). For example, Habernal and Gurevych (2016) has experimented with different machine learning models to predict which of two arguments is more convincing.…”
Section: Related Work and Datasetsmentioning
confidence: 99%
“…On the CORPS dataset (Guerini et al, 2013), which consists of the text of several thousand political speeches dating from 1917 to 2011, they define persuasive sentences as those that preceded annotations of either applause or laughter. Liu et al (2017), working with a corpus of TED talks, use logistic regression to predict applause from sentences using a combination of features: euphony (again from Guerini et al (2015)), linguistic style markers derived from membership in LIWC categories, markers of emotional expression derived from membership in the NRC Emotion Lexicon, mentions of names, rhetorical questions (string matching for "? "), expressions of gratitude (matching a handcrafted list of word stems including "thank * " and "grateful * "), and expressions seeking applause (matching the pattern "applau * ").…”
Section: Predicting Applausementioning
confidence: 99%
“…Park et al (2016) developed an interactive system to assist human moderators to select high quality news. Guerini et al (2015) modeled a notion of euphony and explored the impact of sounds on different forms of persuasiveness. Their research focused on the phonetic aspect instead of language usage.…”
Section: Related Workmentioning
confidence: 99%
“…Text quality and popularity evaluation has been studied in different domains in the past few years (Louis and Nenkova, 2013;Tan et al, 2014;Park et al, 2016;Guerini et al, 2015). However, 1 http://idebate.org/ 2 http://convinceme.net quality evaluation of argumentative text in the online forum has some unique characterisitcs.…”
Section: Introductionmentioning
confidence: 99%