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Presentations

Completed Papers 5: Data Science and Analytics
Time: 23/Mar/2017: 3:30pm-5:00pm · Location: Wuchang Hall

Writing to Persuade: Analysis and Detection of Persuasive Discourse

Taraneh Khazaei2, Lu Xiao1, Robert Mercer2

1Syracuse University, United States of America; 2University of Western Ontario, Canada

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.

 
 
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