Combating Hostile Posts on Social Media: Detection, Characterization, Mitigation, and Beyond
Speaker: Tanmoy Chakraborty – New Delhi, IndiaTopic(s): Artificial Intelligence, Machine Learning, Computer Vision, Natural language processing
Abstract
Online social media platforms are popular mediums for the dissemination and consumption of information. Unfortunately, due to decentralized generation and propagation of content, they also come with limited liability for harmful posts and collusive persuasion. It is often the experience that online users are subjected to a barrage of harmful posts (fake news, hate speech, offensive posts, etc.) within a short span of time. In this talk, I will present a series of our recent studies on combating three types of hostile posts – hate speech, misinformation and harmful memes. The talk will cover different detection strategies that leverage unimodal and multimodal signals (text, image, social network and other exogenous signals). I will then present how to characterize such hostile posts in terms of who these posts target (victims of these posts), how such posts are written, how they propagate on social media and how cohesive echo-chambers of users are formed to strategise the spread. The talk will also cover several predictive models to forecast the amount of damage such a hostile post can cause. I will then discuss how proactive measures can help stop the spread of hostile posts even before it is written! The talk will end by presenting the challenges and opportunities in designing machine learning models for defense against toxic content on social media.About this Lecture
Number of Slides: 50Duration: 45 minutes
Languages Available: English
Last Updated:
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