Detection of Cyberbullying in GIF using AI
Pal Dave, Xiaohong Yuan, Madhuri Siddula, Kaushik Roy

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…
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Taxonomy
TopicsHate Speech and Cyberbullying Detection · Bullying, Victimization, and Aggression · Authorship Attribution and Profiling
