Weibo Fake News Dataset and Experiment Models

The rumdect folder contains the original Weibo fake news dataset (Weibo folder and Weibo. txt text) and the processed dataset used in this experiment (data, label0, and label1 folders). The original Weibo dataset is Jing Ma's Weibo dataset. This experiment uses a subset of the Weibo dataset, which includes 1280 real news and 1280 fake news, each with 80 comments. The saved-loss folder and saved-model folder are used to save the results and model parameters generated during the experiment process. Due to the large size of model parameters, they are not saved but can be obtained by running experiment code. The used_model folder includes the three models used in this experiment: chinese-bert-wwm, bert-base-personality, trans-opus-mt-zh-en. These three models can all be obtained from the hugging face website.code.zip includes all experiment codes.

rumdect文件夹包含原始微博假新闻数据集（内含Weibo文件夹与Weibo.txt文本文件）以及本实验所用的预处理数据集（内含data、label0与label1三个文件夹）。该原始微博数据集为马静（Jing Ma）的微博数据集。本实验选取该数据集的一个子集，包含1280条真实新闻与1280条假新闻，每条新闻均配有80条配套评论。saved-loss文件夹与saved-model文件夹用于存储实验过程中生成的结果与模型参数。由于模型参数量级庞大，本次未存储该部分数据，但可通过运行实验代码获取。used_model文件夹包含本实验所用的三款模型：chinese-bert-wwm、bert-base-personality与trans-opus-mt-zh-en，上述三款模型均可从hugging face网站获取。code.zip压缩包包含全部实验代码。

搜集汇总

背景与挑战

背景概述

该数据集是一个用于假新闻检测的微博数据集，包含原始和处理后的数据，其中实验子集有2560条新闻（真实和假新闻各1280条），每条新闻附带80条评论。数据集还提供了实验代码和预训练模型，适用于自然语言处理和假新闻识别研究。