桌面棋类（TAB）网络游戏热度分析数据

对同一日内桌面棋类（TAB）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，可以得到桌面棋类（TAB）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=(当日在线总人数比例D1/前一日在线总人数比例D2)×(当日在线总时长比例T1/前一日在线总时长比例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 counting and analyzing the proportion of total online players and total online playing duration of desktop table game (TAB) online games each day, and comparing them with the corresponding metrics of the previous day, the popularity change analysis of such games can be derived. Game genres with rising popularity will become key development priorities for the online game industry, with increased investment of capital and human resources; for genres with declining popularity, the allocation of capital and human resources will be appropriately reduced. This data analysis provides important references for the development direction of the online game industry.

The heat change index M is calculated as: M = (D1 / D2) × (T1 / T2), where D1 is the proportion of total online players of this game genre on the current day, D2 is the proportion of total online players of this game genre on the previous day, T1 is the proportion of total online playing duration of this game genre on the current day, and T2 is the proportion of total online playing duration of this game genre on the previous day.

Data analysis is performed on the calculated heat change index M as follows: when 0 < M < 0.9, the heat change status is "DEC", indicating that the popularity of this genre of online games is declining; when 0.9 ≤ M ≤ 1.1, the heat change status is "NC", indicating that the popularity of this genre of online games has no significant change; when M > 1.1, the heat change status is "RISE", indicating that the popularity of this genre of online games is rising.

搜集汇总

数据集介绍

特点

该数据集包含944条桌面棋类（TAB）网络游戏的热度分析数据，每周更新。通过计算当日和前一日在线人数及时长比例的热度变化指数，分析游戏热度变化状态（攀升、降低或无变化），为网络游戏行业的资源分配和发展方向提供重要参考。