用AI识别社交媒体中的表情包欺凌行为，准确率达97%。
Detection of Cyberbullying in GIF using AI
- 基于微博标签抓取4100个表情包，构建专用数据集。
- 采用VGG16模型实现97%的欺凌检测准确率。
- 为研究者提供首个公开的表情包欺凌数据集。
网络欺凌是日益严重的社会问题，随着互联网发展，在社交媒体中通过文字、评论、图片、GIF或贴纸、音频视频等形式传播。已有大量研究聚焦于文本和图像中的欺凌检测，但针对GIF/贴纸的研究极少。本文从Twitter收集与欺凌相关的标签，利用GIPHY公开API下载相关GIF，共获取超过4100个含欺凌与非欺凌内容的GIF。采用预训练深度学习模型VGG16进行检测，取得97%的准确率。本研究首次构建了面向表情包欺凌检测的公开数据集，可为后续研究提供支持。
原文摘要 · Abstract (English)
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.
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