Earticle

초록

영어

We explore the idea of creating a classifier that can be used to detect presence of hate speech in web discourses such as web forums and blogs. In this work, hate speech problem is abstracted into three main thematic areas of race, nationality and religion. The goal of our research is to create a model classifier that uses sentiment analysis techniques and in particular subjectivity detection to not only detect that a given sentence is subjective but also to identify and rate the polarity of sentiment expressions. We begin by whittling down the document size by removing objective sentences. Then, using subjectivity and semantic features related to hate speech, we create a lexicon that is employed to build a classifier for hate speech detection. Experiments with a hate corpus show significant practical application for a real-world web discourse.

목차

Abstract
 1. Introduction
 2. Hate Speech
 3. Related Works
  3.1. Sentence-level Subjectivity Detection
  3.2. Lexicon Building
  3.3. Hate Speech Detection
 4. Hate Speech Corpuses
 5. Proposed Approach
  5.1. Subjectivity Analysis
  5.2. Lexicon for Hate Speech
 6. Aggregating Opinions for Hate Speech Detection
 7. Experiment Setup
  7.1 Results and Evaluation
 8. Conclusion
 Acknowledgements
 References

키워드

저자

• Njagi Dennis Gitari [ School of Information Science and Engineering, Central South University Changsha, 410083, China ]
• Zhang Zuping [ School of Information Science and Engineering, Central South University Changsha, 410083, China ]
• Hanyurwimfura Damien [ College of Information Science and Engineering, Hunan University, China ]
• Jun Long [ School of Information Science and Engineering, Central South University Changsha, 410083, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Multimedia and Ubiquitous Engineering

• 간기

  월간

• pISSN

  1975-0080

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605