Stance Characterization and Detection On Social Media
| dc.contributor.advisor | Walid Magdy | |
| dc.contributor.author | ABEER IBRAHIM ALDAYEL | |
| dc.date | 2021 | |
| dc.date.accessioned | 2022-05-28T18:48:02Z | |
| dc.date.available | 2022-05-28T18:48:02Z | |
| dc.degree.department | Informatics: ILCC: Language Processing, Speech Technology, Information Retrieval, Cognition | |
| dc.degree.grantor | University of Edinburgh | |
| dc.description.abstract | Finally, we study the dynamics of polarized stance to understand the factors that influence online stance. Particularly, we extend the analysis of online stance signals and examine the interplay between stance and automated accounts (bots). Furthermore, we pose the problem of gauging the bots' effect on polarized stance through a sole focus on the diffusion of bots on the online social network. | |
| dc.identifier.uri | https://drepo.sdl.edu.sa/handle/20.500.14154/39107 | |
| dc.language.iso | en | |
| dc.title | Stance Characterization and Detection On Social Media | |
| sdl.thesis.level | Doctoral | |
| sdl.thesis.source | SACM - United Kingdom |