Politicians' Social Media Profiles

该数据集包含了1000位政治家的个人资料，旨在分析他们对公众意见的潜在影响力。在数据处理上，70%的数据用于训练，剩余的30%用于测试，并通过五次随机选择来确保结果的稳健性。该数据集的规模为1000个个人资料，所面临的任务是进行异常类别分类（Outlier Class Classification，简称OCC）。

This dataset comprises 1,000 politician profiles, and is intended to analyze their potential influence on public opinion. For data processing, 70% of the dataset is allocated for training, while the remaining 30% is reserved for testing. Five random splits are conducted to ensure the robustness of the results. The targeted task for this dataset is Outlier Class Classification (abbreviated as OCC).