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Detecting Abusive Arabic Language Twitter Accounts Using a Multidimensional Analysis Model

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dc.contributor.advisor Jones, James H
dc.contributor.author Abozinadah, Ehab
dc.creator Abozinadah, Ehab
dc.date.accessioned 2018-10-22T01:21:21Z
dc.date.available 2018-10-22T01:21:21Z
dc.date.issued 2017
dc.identifier.uri https://hdl.handle.net/1920/11326
dc.description.abstract Twitter is one of the most popular social media sources for disseminating news and propaganda in the Middle East. The increased use of social media has motivated spammers to post malicious content on social media sites. Some of these Arabic language spammers use adult content to further the distribution of their malicious activities. However, the extensive number of users posting adult content in social media degrades the experience for other users for whom the adult content is not desired or appropriate. These accounts would be suspended or terminated from Twitter whenever reported by Twitter’s users as Twitter prohibits adult content in an image, a video, or a text. Moreover, some countries have attempted to detect these accounts, but have failed as these accounts use informal Arabic language and misspelled words that cannot be detected using blacklisted keywords.
dc.format.extent 127 pages
dc.language.iso en
dc.rights Copyright 2017 Ehab Abozinadah
dc.subject Information technology en_US
dc.subject Computer science en_US
dc.subject Big Data en_US
dc.subject Classification en_US
dc.subject Cyber Security en_US
dc.subject Data Analysis en_US
dc.subject Machine Learning en_US
dc.subject Social media Analysis en_US
dc.title Detecting Abusive Arabic Language Twitter Accounts Using a Multidimensional Analysis Model
dc.type Dissertation
thesis.degree.level Ph.D.
thesis.degree.discipline Computer Science
thesis.degree.grantor George Mason University


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