Detecting Hostile Posts using Relational Graph Convolutional Network

Hostility Detection and Covid-19 Fake News Detection in Social Media

Withtheadventofsocialmedia,therehasbeenanextremely rapid increase in the content shared online. Consequently, the propagation of fake news and hostile messages on social media platforms has also skyrocketed. In this paper, we address the problem of detecting hostile and fake content in the Devanagari (Hindi) script as a multi-class, multi-label problem. Using NLP techniques, we build a model that makes use of an abusive language detector coupled with features extracted via Hindi BERT and Hindi FastText models and metadata. Our model achieves a 0.97 F1 score on coarse grain evaluation on Hostil…

大型语言模型的时间关系推理用于检测股票投资组合崩盘

Temporal Relational Reasoning of Large Language Models for Detecting Stock Portfolio Crashes

提出时间关系推理框架，利用大型语言模型模拟人类认知能力，动态处理新闻影响与时间上下文，在检测股票投资组合崩盘上超越现有技术，并扩展至宏观经济危机检测。

Automatic Detection of Sexist Statements Commonly Used at the Workplace

Detecting hate speech in the workplace is a unique classification task, as the underlying social context implies a subtler version of conventional hate speech. Applications regarding a state-of the-art workplace sexism detection model include aids for Human Resources departments, AI chatbots and sentiment analysis. Most existing hate speech detection methods, although robust and accurate, focus on hate speech found on social media, specifically Twitter. The context of social media is much more anonymous than the workplace, therefore it tends to lend itself to more aggressive and "hostile" vers…

检测社交媒体上的多维政治不文明行为

Detecting Multidimensional Political Incivility on Social Media

本研究利用多维政治不文明视角，基于13K标注推文实现先进检测，发现不文明行为呈偏斜分布，并提出融合作者社会背景信息的建模方法以提升检测性能。

Attributed Multi-Relational Attention Network for Fact-checking URL Recommendation

To combat fake news, researchers mostly focused on detecting fake news and journalists built and maintained fact-checking sites (e.g., Snopes.com and Politifact.com). However, fake news dissemination has been greatly promoted via social media sites, and these fact-checking sites have not been fully utilized. To overcome these problems and complement existing methods against fake news, in this paper we propose a deep-learning based fact-checking URL recommender system to mitigate impact of fake news in social media sites such as Twitter and Facebook. In particular, our proposed framework consis…

Coarse and Fine-Grained Hostility Detection in Hindi Posts using Fine Tuned Multilingual Embeddings

Due to the wide adoption of social media platforms like Facebook, Twitter, etc., there is an emerging need of detecting online posts that can go against the community acceptance standards. The hostility detection task has been well explored for resource-rich languages like English, but is unexplored for resource-constrained languages like Hindidue to the unavailability of large suitable data. We view this hostility detection as a multi-label multi-class classification problem. We propose an effective neural network-based technique for hostility detection in Hindi posts. We leverage pre-trained…