SMP2020微博情绪分类技术评测数据集

上传者: u011239443 | 上传时间: 2023-02-09 16:48:42 | 文件大小: 44.7MB | 文件类型: ZIP
SMP2020微博情绪分类技术评测数据集 本次技术评测使用的标注数据集由哈尔滨工业大学社会计算与信息检索研究中心提供,原始数据源于新浪微博,由微热点大数据研究院提供,数据集分为两部分。     第一部分为通用微博数据集,该数据集内的微博内容是随机获取到微博内容,不针对特定的话题,覆盖的范围较广。     第二部分为疫情微博数据集,该数据集内的微博内容是在疫情期间使用相关关键字筛选获得的疫情微博,其内容与新冠疫情相关。     因此,本次评测训练集包含上述两类数据:通用微博训练数据和疫情微博训练数据,相对应的,测试集也分为通用微博测试集和疫情微博测试集。参赛成员可以同时使用两种训练数据集来训练模型。     每条微博被标注为以下六个类别之一:neutral(无情绪)、happy(积极)、angry(愤怒)、sad(悲伤)、fear(恐惧)、surprise(惊奇)。     通用微博训练数据集包括27,768条微博,验证集包含2,000条微博,测试数据集包含5,000条微博。     疫情微博训练数据集包括8,606条微博,验证集包含2,000条微博,测试数据集包含3,000

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