Taptap reviews 游戏评论数据集

该数据集包含手游 App TapTap 上约 300 款游戏的标签评论，可用于情感分析的应用，共 4,888 个数据示例。其中用户评论低于 3 星（最多 5 星）被视为 0（不满意），其他为 1（满意）。这两个类别的比例大约是 1:1 。 手机游戏市场如今已发展成一个庞大领域，尤其在中国更是如此。监督玩家评论已成为预测游戏商业成功的关键手段。这个数据集主要被用来探索中文自然语言处理 (NLP) 技术的应用潜力。例如，每当有新游戏推出，玩家们便会在微博、游戏论坛、贴吧等社交平台上展开热烈讨论。开发专门模型以自动识别玩家讨论的趋势，对于指导市场策略和决策制定具有重要意义。通过这一自动化过程，能够更精准地把握市场动态，从而预测游戏的商业潜力。

This dataset contains labeled comments for approximately 300 mobile games on the TapTap mobile gaming app, comprising 4,888 data instances, and is suitable for sentiment analysis tasks. Comments with a rating lower than 3 stars (on a 5-star maximum scale) are labeled as 0 (dissatisfied), while all other comments are labeled as 1 (satisfied), with an approximate 1:1 class balance between the two categories.
The global mobile gaming market has expanded into a massive industry, with particularly strong growth in China. Monitoring player comments has become a key approach to predicting the commercial success of games.
This dataset is primarily utilized to explore the application potential of Chinese natural language processing (NLP) technologies. For example, upon the launch of a new mobile game, players engage in extensive discussions on social platforms including Weibo, gaming forums, and Baidu Tieba. Developing specialized models to automatically identify trends in player discussions is critical for guiding marketing strategies and corporate decision-making.
Through this automated workflow, market trends can be more accurately tracked, enabling precise prediction of the commercial potential of mobile games.

搜集汇总

背景与挑战

背景概述

该数据集包含TapTap平台上约300款手游的4,888条评论，用于情感分析任务。评论根据星级被标注为'不满意'（0）或'满意'（1），类别比例均衡，适用于中文自然语言处理研究，旨在通过自动分析玩家反馈来预测游戏商业潜力和指导市场决策。