本仓库包含了基于机器学习模型预测Steam平台游戏热度和玩家情绪的实现与分析。通过多任务学习方法，本项目旨在预测游戏的热度（评论量）和好评度（正向推荐比例）在未来一段时间的变化趋势。模型结合了历史评论数据、情绪分析特征和游戏元数据，使用LSTM和Transformer架构进行预测。该框架为游戏开发者和运营商提供了关于游戏表现和用户反馈之间动态关系的深入洞察，
active 2026-01-11 → 2026-05-26 (UTC)
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