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Detecting Abusive Arabic Language Twitter Accounts Using a Multidimensional Analysis Model

Date

2017

Authors

Abozinadah, Ehab

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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.

Description

Keywords

Information technology, Computer science, Big Data, Classification, Cyber Security, Data Analysis, Machine learning, Social media Analysis

Citation