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An Enhanced Model for Abusive Behavior Detection in Social Network

  • Kefaya QaddoumEmail author
  • Israr Ahmad
  • Yasir Javed
  • Ali Rodan
Conference paper
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 29)

Abstract

Due to the growing use of social media, incidents of online abuse are also on rise. Online abusive behavior is defined as the use of electronic devices connected through internet for offensive activities. It is mostly in the form of comments containing abusive words about others, which affect the target users’ psychology and depresses them. This paper is aimed at devising method for detecting abusive behavior using supervised learning techniques. Two hypotheses are presented to extract features for detection of offensive comments. The initial experiments show that using features using our proposed method has better accuracy than the traditional feature extraction techniques like TF-IDF.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Kefaya Qaddoum
    • 1
    Email author
  • Israr Ahmad
    • 1
  • Yasir Javed
    • 1
  • Ali Rodan
    • 1
  1. 1.Higher College of TechnologyAl Ain Women’s CollegeAbu DhabiUAE

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