即时战略类（RTS）网络游戏热度变化分析数据

对同一日内各类网络游戏的在线总人数比例和在线总时长进行统计并进行同比分析，可以得到不同类型的网络游戏的热度变化分析。热度在攀升游戏的游戏类型会成为接下来网络游戏行业的重点开发项目，对其投入更多的资金和人力资源；对于热度在降低的游戏类型，则会适当减少资金和人力资源分配。该项数据分析为网络游戏行业的发展方向提供了重要参考。热度变化指数M=(D1/D2)×(T1/T2),其中D1为该类型网络游戏当日在线总人数的比例，D2为该类型网络游戏前一日在线总人数的比例，T1为该类型网络游戏当日在线总时长的比例，T2为该类型网络游戏前一日在线总时长的比例。对计算所得的热度变化指数M进行数据分析：当0＜M＜0.9时，热度变化状态为“DEC”，表明该类型网络游戏的热度在降低；当0.9≤M≤1.1时，热度变化状态为“NC”，表明该类型网络游戏的热度没有明显变化；当M＞1.1时，热度变化状态为“RISE”，表明该类型网络游戏的热度在攀升。

By statistically analyzing the proportions of total online players and total online play durations across various online game genres within a single day and conducting day-over-day comparative analysis, we can obtain popularity variation analyses for different categories of online games. Game genres with rising popularity will become key development priorities for the online game industry, where more capital and human resources will be invested; for genres with declining popularity, the allocation of capital and human resources will be appropriately reduced. This data analysis provides critical references for the development direction of the online game industry. The popularity variation index M is calculated as M=(D1/D2)×(T1/T2), where D1 refers to the proportion of total online players of a specific game genre on the current day, D2 refers to the proportion of total online players of the same genre on the previous day, T1 refers to the proportion of total online play durations of the same genre on the current day, and T2 refers to the proportion of total online play durations of the same genre on the previous day. Data analysis of the calculated popularity variation index M follows the following rules: when 0 < M < 0.9, the popularity variation status is "DEC", indicating that the popularity of this game genre is declining; when 0.9 ≤ M ≤ 1.1, the popularity variation status is "NC", indicating that the popularity of this game genre has no significant change; when M > 1.1, the popularity variation status is "RISE", indicating that the popularity of this game genre is rising.

搜集汇总

数据集介绍

特点

该数据集记录了即时战略类（RTS）网络游戏的热度变化数据，包括在线人数比例、在线时长比例和热度变化指数等字段，每日更新，用于分析游戏热度变化趋势，指导行业资源分配。