Towards Cyberbullying-free social media in smart cities: a unified multi-modal approach

  • Kirti Kumari*
  • , Jyoti Prakash Singh
  • , Yogesh Kumar Dwivedi
  • , Nripendra Pratap Rana
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

70 Scopus citations

Abstract

Smart cities are shifting the presence of people from physical world to cyber world (cyberspace). Along with the facilities for societies, the troubles of physical world, such as bullying, aggression and hate speech, are also taking their presence emphatically in cyberspace. This paper aims to dig the posts of social media to identify the bullying comments containing text as well as image. In this paper, we have proposed a unified representation of text and image together to eliminate the need for separate learning modules for image and text. A single-layer Convolutional Neural Network model is used with a unified representation. The major findings of this research are that the text represented as image is a better model to encode the information. We also found that single-layer Convolutional Neural Network is giving better results with two-dimensional representation. In the current scenario, we have used three layers of text and three layers of a colour image to represent the input that gives a recall of 74% of the bullying class with one layer of Convolutional Neural Network.

Original languageEnglish
Pages (from-to)11059-11070
Number of pages12
JournalSoft Computing
Volume24
Issue number15
DOIs
StatePublished - 1 Aug 2020
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2019, Springer-Verlag GmbH Germany, part of Springer Nature.

Keywords

  • Convolutional Neural Network
  • Cyberbullying
  • Deep learning
  • Online social network
  • TF–IDF

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Software
  • Geometry and Topology

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