Real Time Detection of Social Bots on Twitter Using Machine Learning and Apache Kafka

Eiman Alothali, Hany Alashwal, Motamen Salih, Kadhim Hayawi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

Social media networks, like Facebook and Twitter, are increasingly becoming important part of most people's lives. Twitter provides a useful platform for sharing contents, ideas, opinions, and promoting products and election campaigns. Due to the increased popularity, it became vulnerable to malicious attacks caused by social bots. Social bots are automated accounts created for different purposes. They are involved in spreading rumors and false information, cyberbullying, spamming, and manipulating the ecosystem of social network. Most of the social bots detection methods rely on the utilization of offline data for both training and testing. In this paper, we use Apache Kafka, a big data analytics tool to stream data from Twitter API in real time. We use profile information (metadata) as features. A machine learning technique is applied to predict the type of the incoming data (human or bot). In addition, the paper presents technical details of how to configure these different tools.

Original languageEnglish
Title of host publication2021 5th Cyber Security in Networking Conference, CSNet 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages98-102
Number of pages5
ISBN (Electronic)9781665407229
DOIs
Publication statusPublished - 2021
Event5th Cyber Security in Networking Conference, CSNet 2021 - Abu Dhabi, United Arab Emirates
Duration: Oct 12 2021Oct 14 2021

Publication series

Name2021 5th Cyber Security in Networking Conference, CSNet 2021

Conference

Conference5th Cyber Security in Networking Conference, CSNet 2021
Country/TerritoryUnited Arab Emirates
CityAbu Dhabi
Period10/12/2110/14/21

Keywords

  • Apache Kafka
  • Social bots
  • Streaming Machine learning
  • Twitter

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems and Management
  • Safety, Risk, Reliability and Quality

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