Abstract
Social media platforms like Facebook and Twitter have been popular tools for social and political movements in non-democratic societies in which traditional media outlets are under government control. Activists in Saudi Arabia, particularly women, have launched several campaigns through social media to demand the right to drive for women. This study used framing theory as the foundation for looking at the degree to which cognitive, emotion, and religious or moral language has been used to frame discussion of this issue on Twitter. Additionally, this study observed the relationship between these linguistic attributes in Twitter and retweeting behavior to understand the characteristics of the discourse that relate to the potential influence of the message. The results suggested that, within the sociopolitical discussion in social media, cognitive language was expressed the most often, particularly insight and causation language. The results also suggested that tweets containing cognitive language are more likely to be retweeted than those with emotion language. However, among the components of cognitive and emotion language, anger was the strongest specific predictor of retweeting behavior. The implications of the presence of linguistic attributes and their relationship to retweeting behavior and suggestions for future communication research within the context of social and political movements are discussed.
Notes
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Graduation Date
2016
Semester
Summer
Advisor
Kinnally, William
Degree
Master of Arts (M.A.)
College
College of Sciences
Department
Communication
Degree Program
Communication; Mass Communication
Format
application/pdf
Identifier
CFE0006386
URL
http://purl.fcla.edu/fcla/etd/CFE0006386
Language
English
Release Date
August 2016
Length of Campus-only Access
None
Access Status
Masters Thesis (Open Access)
STARS Citation
Sahly, Abdulsamad, "Examining presence and influence of linguistic characteristics in the Twitter discourse surrounding the women's right to drive movement in Saudi Arabia" (2016). Electronic Theses and Dissertations. 5125.
https://stars.library.ucf.edu/etd/5125