Steam User Review Data – 1,000 Most Recent Reviews from 500 Popular Games

This dataset contains 1,000 of the most recent Steam user reviews from 500 games, ordered by organic visibility / relevance at the time of collection – December 6th 2023. The dataset includes review text and associated metadata to support research on player feedback, platform cultures, and user experience evaluation.Included fields:recommendationid; author; language; review; timestamp_created; timestamp_updated; voted_up; votes_up; votes_funny; weighted_vote_score; comment_count; steam_purchase; received_for_free; written_during_early_access; hidden_in_steam_china; steam_china_location; timestamp_dev_responded; developer_response.This dataset provides a broader sampling frame for examining how users evaluate games through public reviews. It is suitable for qualitative coding, descriptive analysis of review metadata, and computational text analysis.Relationship to associated publication:The OzCHI ’25 paper Evaluating Time in Play and Temporal Satisfaction: Time-Centric Language in Video Game User Reviews on Steam used this dataset to examine how players evaluate video games through time-centric language in Steam user reviews.From the first 100 games ordered by relevance at the time of collection, a time-centric keyword filter was applied, identifying 12,337 reviews containing time-related terms. From these, 5,423 reviews that explicitly addressed player time were thematically analysed, leading to six Temporal Priorities and the construct of Temporal Satisfaction.This larger repository is designed to complement that study by extending the sampling frame beyond the 100-game analytic subset and enabling future qualitative and mixed-method work that builds on player-led temporal evaluation – offering a user-centred lens that can sit alongside (and enrich) existing quantitative approaches to playtime and review analysis.本数据集包含2023年12月6日采集时，按自然曝光度与相关性排序的500款游戏的1000条最新Steam用户评测。数据集涵盖评测文本及关联元数据，可用于支持玩家反馈、平台文化及用户体验评估相关研究。 包含字段如下：推荐ID（recommendationid）、作者（author）、语言（language）、评测内容（review）、创建时间戳（timestamp_created）、更新时间戳（timestamp_updated）、是否推荐（voted_up）、有用投票数（votes_up）、趣味投票数（votes_funny）、加权投票得分（weighted_vote_score）、评论数（comment_count）、是否通过Steam购买（steam_purchase）、是否免费获取（received_for_free）、是否在游戏抢先体验阶段撰写评测（written_during_early_access）、是否在Steam中国区隐藏（hidden_in_steam_china）、Steam中国区位置（steam_china_location）、开发者回复时间戳（timestamp_dev_responded）、开发者回复内容（developer_response）。 本数据集为通过公开评测分析玩家游戏评价的研究提供了更广泛的抽样框架，适用于定性编码、评测元数据描述性分析及计算文本分析。 本数据集与以下发表成果相关：发表于OzCHI ’25的论文《游玩时长与时序满意度评估：Steam平台电子游戏用户评测中的时序相关语言》（*Evaluating Time in Play and Temporal Satisfaction: Time-Centric Language in Video Game User Reviews on Steam*）使用本数据集，分析玩家如何通过Steam用户评测中的时序相关语言评价电子游戏。 在采集时按相关性排序的前100款游戏中，研究人员应用了时序关键词筛选规则，共识别出12337条包含时间相关术语的评测。其中5423条明确提及玩家游玩体验时长的评测被开展主题分析，最终提炼出六大时序优先级（Temporal Priorities）及时序满意度（Temporal Satisfaction）这一研究构念。 本大型数据集旨在补充上述研究，将抽样范围扩展至100款游戏的分析子集之外，可支持后续基于玩家主导的时序评价展开的定性与混合方法研究——提供以用户为中心的视角，可与现有针对游玩时长与评测分析的定量研究方法互补并丰富其内涵。