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Title:Writing to persuade: Analysis and detection of persuasive discourse
Author(s):Khazaei, Taraneh; Xiao, Lu; Mercer, Robert
Subject(s):Online persuasion
Linguistic analysis
Natural language processing
Abstract:The relation between the dialogue behavior of participants in communicative settings and whether they are perceived persuasive by other participants has long been established in the literature. In this study, we are focused on the linguistic facets of written messages, and we aim to gain insight into the dimensions of the language that can lead to persuasion. Through the analysis of various linguistic dimensions, a set of features are selected to be utilized in a supervised manner to identify persuasive text. The selected features are independent of the semantics and are mainly surface-based attributes that are related to the structure and organization of the text. The use of certain language elements, such as pronouns and articles, is also taken into account. The evaluation results of supervised machine learning algorithms are promising, which suggests that surface-based linguistic attributes can greatly contribute toward the persuasiveness of text, regardless of the underlying claims and arguments.
Issue Date:2017
Citation Info:Khazaei, T., Lu, X., & Mercer, R. (2017). Writing to Persuade: Analysis and Detection of Persuasive Discourse. In iConference 2017 Proceedings (pp. 203–215).
Series/Report:iConference 2017 Proceedings
Genre:Conference Paper / Presentation
Rights Information:Copyright 2017 Taraneh Khazaei, Xiao Lu, and Robert Mercer
Date Available in IDEALS:2017-07-27

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