M&A Dataset

该数据集包含了关于并购事件的新闻文章或推文，专门为分类任务设计了交易结果的分类。为了确保训练过程中两类数据平衡，该数据集在预处理阶段重点关注了已完成的交易和传闻。数据集规模为4,098个实例，其任务是对并购结果进行二元分类（已完成交易与传闻的分类）。

This dataset comprises news articles and tweets related to merger and acquisition (M&A) events, and is tailored for classification tasks focusing on transaction outcomes. To ensure a balanced distribution of the two categories during model training, priority was given to completed transactions and rumors during the preprocessing stage. The dataset contains 4,098 instances in total, and its core task is binary classification of M&A outcomes, distinguishing between completed transactions and related rumors.