地球资源数据云——数据资源详情
使命召唤移动评论数据集
该数据集《Call of Duty Mobile Reviews Dataset》主要用于多分类任务，数据形态以文本为主，应用场景偏向文本内容分析。 题目说明：Anonymized Reviews for NLP and Gaming Insights 任务类型：文本多分类。 建议流程：先做文本清洗与分词，再比较 TF - IDF+线性模型 与 预训练语言模型。 评估建议：使用分层切分或交叉验证，优先关注 F1、Recall、AUC 等分类指标。 可用文件：call_of_duty_reviews_50000.csv。 Dataset Overview This dataset contains 50,000 user reviews for the popular mobile game Call of Duty Mobile. The reviews are collected from the Google Play Store and include anonymized usernames, review content, and user ratings. The dataset has been cleaned to remove URLs and preserve only meaningful feedback for analysis. Data Science Applications This large dataset is ideal for various data science applications, including: 1. Sentiment Analysis: Analyze user sentiments to understand positive, negative, or neutral feedback. 2. Natural Language Processing (NLP): Perform text mining tasks such as topic modeling, keyword extraction, or text classification.
摘要概览
该数据集《Call of Duty Mobile Reviews Dataset》主要用于多分类任务，数据形态以文本为主，应用场景偏向文本内容分析。 题目说明：Anonymized Reviews for NLP and Gaming Insights
任务类型：文本多分类。
建议流程：先做文本清洗与分词，再比较 TF - IDF+线性模型 与 预训练语言模型。
评估建议：使用分层切分或交叉验证，优先关注 F1、Recall、AUC 等分类指标。
可用文件：call_of_duty_reviews_50000.csv。
Dataset Overview
This dataset contains 50,000 user reviews for the popular mobile game Call of Duty Mobile. The reviews are collected from the Google Play Store and include anonymized usernames, review content, and user ratings. The dataset has been cleaned to remove URLs and preserve only meaningful feedback for analysis.
Data Science Applications This large dataset is ideal for various data science applications, including:
1. Sentiment Analysis: Analyze user sentiments to understand positive, negative, or neutral feedback.
2. Natural Language Processing (NLP): Perform text mining tasks such as topic modeling, keyword extraction, or text classification.