Writing to persuade: Analysis and detection of persuasive discourse

Khazaei, Taraneh; Xiao, Lu; Mercer, Robert

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https://hdl.handle.net/2142/96673 Copy

Description

Title

Writing to persuade: Analysis and detection of persuasive discourse

Author(s)

• Khazaei, Taraneh
• Xiao, Lu
• Mercer, Robert

Issue Date

2017

Keyword(s)

• Online persuasion
• Reddit
• 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.

Publisher

iSchools

Series/Report Name or Number

iConference 2017 Proceedings

Type of Resource

text

Language

en

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http://hdl.handle.net/2142/96673

Copyright and License Information

Copyright 2017 Taraneh Khazaei, Xiao Lu, and Robert Mercer

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