Looking for COVID-19 misinformation in multilingual social media texts
Birla Institute of Technology, Mesra, India（比拉理工学院（梅斯拉））；Univ. Grenoble Alpes, CNRS, LIG, Grenoble, France（格勒诺布尔阿尔卑斯大学，法国国家科学研究中心，LIG实验室）；CNRS, LIRIS-LAFMIA Lyon, France（法国国家科学研究中心，LIRIS-LAFMIA实验室）
This paper presents the Multilingual COVID-19 Analysis Method (CMTA) for detecting and observing the spread of misinformation about this disease within texts. CMTA proposes a data science (DS) pipeline that applies machine learning models for processing, classifying (Dense-CNN) and analyzing (MBERT) multilingual (micro)-texts. DS pipeline data preparation tasks extract features from multilingual textual data and categorize it into specific information classes (i.e., 'false', 'partly false', 'misleading'). The CMTA pipeline has been experimented with multilingual micro-texts (tweets), showing misinformation spread across different languages. To assess the performance of CMTA and put it in perspective, we performed a comparative analysis of CMTA with eight monolingual models used for detecting misinformation. The comparison shows that CMTA has surpassed various monolingual models and suggests that it can be used as a general method for detecting misinformation in multilingual micro-texts. CMTA experimental results show misinformation trends about COVID-19 in different languages during the first pandemic months.
Lost in translation: using global fact-checks to measure multilingual misinformation prevalence, spread, and evolution
Department of Mathematical Modeling and Machine Learning, University of Zurich, Switzerland（苏黎世大学数学建模与机器学习系）；Digital Society Initiative, University of Zurich, Switzerland（苏黎世大学数字社会倡议）；Oxford Internet Institute, University of Oxford, United Kingdom（牛津大学网络研究所）；Meedan, San Francisco, United States（梅丹公司，旧金山，美国）
Same Claim, Different Judgment: Benchmarking Scenario-Induced Bias in Multilingual Financial Misinformation Detection
The University of Manchester（曼彻斯特大学）；Stevens Institute of Technology（史蒂文斯理工学院）；The Fin AI（Fin AI）；Columbia University（哥伦比亚大学）；Islamic University of Technology（伊斯兰科技大学）；Athens University of Economics and Business（雅典经济与商业大学）；Archimedes, Athena Research Center（阿基米德，亚特兰蒂斯研究中心）；MBZUAI；McGill University（麦吉尔大学）；Mila - Quebec AI Institute（魁北克人工智能研究所）；Dubai Police（迪拜警察）；University of Melbourne（墨尔本大学）；Halmstad University（哈姆斯塔德大学）；University of Florida（佛罗里达大学）；ELLIS Manchester（曼彻斯特ELLIS）
Echoes of Unrest: A Multimodal NLP Framework for Early Warning of Fake News and Violence-Driven Mob Activity
Department of Computer Science and Engineering, Dhaka International University（达卡国际大学计算机科学与工程系）；Department of Computer Science and Engineering, Bangladesh University of Engineering and Technology（孟加拉国工程技术大学计算机科学与工程系）
ICPR 2024 Competition on Multilingual Claim-Span Identification
Indian Institute of Technology Kharagpur（印度理工学院卡拉格普尔分校）；Centre for Artificial Intelligence and Robotics, DRDO（国防研究与发展组织人工智能与机器人中心）；NSHM Institute of Computing & Analytics（NSHM计算与分析学院）
University of Bucharest（布加勒斯特大学）；Faculty of Mathematics and Computer Science（数学与计算机科学学院）；Interdisciplinary School of Doctoral Studies（跨学科研究生院）；HLT Research Center（HLT研究中心）
PartisanLens: A Multilingual Dataset of Hyperpartisan and Conspiratorial Immigration Narratives in European Media
Centro Singular de Investigación en Tecnoloxías Intelixentes da USC（乌拉特大学智能技术研究中心）；IRLab, CITIC Research Centre, Universidade da Coruña（IR实验室，CITIC研究中心，科鲁纳大学）；Universidade de Évora（埃夫拉大学）；Universidad de La Rioja（里瓦达维亚大学）；GESIS Leibniz Institute for the Social Sciences（莱比锡社会科学院）
