地球资源数据云——数据资源详情

基于来源的假新闻分类

该数据集《Source based Fake News Classification》主要用于多分类任务，数据形态以文本为主，应用场景偏向文本内容分析。 题目说明：Classification of news by type and labels 任务类型：文本多分类。 建议流程：先做文本清洗与分词，再比较 TF - IDF+线性模型 与 预训练语言模型。 评估建议：使用分层切分或交叉验证，优先关注 F1、Recall、AUC 等分类指标。 可用文件：news_articles.csv。 Context Social media is a vast pool of content, and among all the content available for users to access, news is an element that is accessed most frequently. These news can be posted by politicians, news channels, newspaper websites, or even common civilians. These posts have to be checked for their authenticity, since spreading misinformation has been a real concern in today’s times, and many firms are taking steps to make the common people aware of the consequences of spread misinformation. The measure of authenticity of the news posted online cannot be definitively measured, since the manual classification of news is tedious and time - consuming, and is also subject to bias. Published paper: http://www.ijirset.com/upload/2020/june/115_4_Source.PDF Content