MT2-CSD

MT2-CSD是一个针对多目标、多轮对话立场检测的综合数据集，由深圳技术大学大数据与互联网学院的研究团队创建。该数据集包含24,457个精心标注的实例，是目前为止最大的此类数据集，展现了最大的对话深度，为立场检测带来了新的挑战。MT2-CSD的创建旨在解决传统立场检测数据集的局限性，如回复轮次较少、标注质量不佳、数据量有限等问题。该数据集的应用领域主要包括社交媒体的立场检测、意见挖掘等，旨在帮助研究人员更好地理解用户在不同话题上的观点和态度，从而提高社交媒体分析的准确性和有效性。

MT2-CSD is a comprehensive dataset for multi-target, multi-turn conversational stance detection, developed by the research team from the School of Big Data and Internet, Shenzhen Technology University. It contains 24,457 carefully annotated instances, making it the largest dataset of this kind to date with the maximum conversational depth, which introduces new challenges for stance detection. This dataset was created to address the limitations of traditional stance detection datasets, such as limited conversational turns, poor annotation quality, and insufficient data scale. Its main application scenarios include social media stance detection, opinion mining and other related fields, aiming to help researchers better understand users' viewpoints and attitudes towards different topics, thereby improving the accuracy and effectiveness of social media analysis.