Detection of Cyberbullying in GIF using AI

TL;DR

This paper presents a deep learning approach using VGG16 to detect cyberbullying in GIFs collected from Twitter, achieving high accuracy and providing a new dataset for future research.

Contribution

The study introduces a novel dataset of cyberbullying GIFs and applies a pre-trained deep learning model for detection, filling a gap in existing research.

Findings

Achieved 97% accuracy in cyberbullying GIF detection

Collected over 4100 GIFs related to cyberbullying and non-cyberbullying

Provided a new dataset for future research in this area

Abstract

Cyberbullying is a well-known social issue, and it is escalating day by day. Due to the vigorous development of the internet, social media provide many different ways for the user to express their opinions and exchange information. Cyberbullying occurs on social media using text messages, comments, sharing images and GIFs or stickers, and audio and video. Much research has been done to detect cyberbullying on textual data; some are available for images. Very few studies are available to detect cyberbullying on GIFs/stickers. We collect a GIF dataset from Twitter and Applied a deep learning model to detect cyberbullying from the dataset. Firstly, we extracted hashtags related to cyberbullying using Twitter. We used these hashtags to download GIF file using publicly available API GIPHY. We collected over 4100 GIFs including cyberbullying and non cyberbullying. we applied deep learning pre-trained model VGG16 for the detection of the cyberbullying. The deep learning model achieved the accuracy of 97%. Our work provides the GIF dataset for researchers working in this area.