乡村振兴信息网络平台用户分析数据集

该数据适用的条件是各大信息发布平台需要针对乡村振兴赛道的创作者进行用户粘性分析时可以分析用户活跃度；数据适用的范围是各个信息网络平台；数据适用的对象是需要对乡村振兴赛道信息发布者进行分析的用户；该数据能解决的问题和产生的有益效果是：通过分析各大网络平台对于乡村振兴信息发布用户的访问情况计算RFE模型，评估用户的活跃度，将活跃度分为多个等级，以根据不同的活跃等级推送不同的活动信息，例如通过活动邀请、相关领域内容创作活动推荐等提升用户的活段度；RFE模型可以为所有平台针对不同赛道需要对信息发布用户进行活跃度分析管理提供数据支持，增加平台用户粘性，吸引创作者入驻。

This dataset is applicable when major information publishing platforms need to conduct user stickiness analysis for creators in the rural revitalization track, specifically for analyzing user activity levels. Its applicable scope covers all information network platforms, and its applicable targets are users who need to analyze information publishers in the rural revitalization track. The problems it solves and its beneficial effects are as follows: By analyzing the access status of users who publish rural revitalization-related information on major online platforms, the Recursive Feature Elimination (RFE) model can be employed to calculate and evaluate user activity levels, which are then categorized into multiple tiers. Based on these activity tiers, different promotional information can be pushed—such as activity invitations and recommendations for content creation activities in relevant fields—to enhance user activity. Additionally, the RFE model can provide data support for all platforms to carry out activity analysis and management of information publishers across different tracks, thereby increasing platform user stickiness and attracting more creators to settle in.