在线视频作为安全隐患报告来源的调查。
An investigation into online videos as a source of safety hazard reports.
机构信息
Department of Business Information Technology, Pamplin College of Business, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA.
Department of Business Information Technology, Pamplin College of Business, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA.
出版信息
J Safety Res. 2018 Jun;65:89-99. doi: 10.1016/j.jsr.2018.03.004. Epub 2018 Mar 14.
INTRODUCTION
Despite the advantages of video-based product reviews relative to text-based reviews in detecting possible safety hazard issues, video-based product reviews have received no attention in prior literature. This study focuses on online video-based product reviews as possible sources to detect safety hazards.
METHODS
We use two common text mining methods - sentiment and smoke words - to detect safety issues mentioned in videos on the world's most popular video sharing platform, YouTube.
RESULTS
15,402 product review videos from YouTube were identified as containing either negative sentiment or smoke words, and were carefully manually viewed to verify whether hazards were indeed mentioned. 496 true safety issues (3.2%) were found. Out of 9,453 videos that contained smoke words, 322 (3.4%) mentioned safety issues, vs. only 174 (2.9%) of the 5,949 videos with negative sentiment words. Only 1% of randomly-selected videos mentioned safety hazards.
CONCLUSIONS
Comparing the number of videos with true safety issues that contain sentiment words vs. smoke words in their title or description, we show that smoke words are a more accurate predictor of safety hazards in video-based product reviews than sentiment words. This research also discovers words that are indicative of true hazards versus false positives in online video-based product reviews. Practical applications: The smoke words lists and word sub-groups generated in this paper can be used by manufacturers and consumer product safety organizations to more efficiently identify product safety issues from online videos. This project also provides realistic baselines for resource estimates for future projects that aim to discover safety issues from online videos or reviews.
简介
尽管基于视频的产品评论相对于基于文本的评论在发现潜在安全隐患问题方面具有优势，但基于视频的产品评论在之前的文献中并未受到关注。本研究专注于在线基于视频的产品评论，将其作为发现安全隐患的可能来源。
方法
我们使用两种常见的文本挖掘方法——情感分析和烟雾词检测，来检测世界上最受欢迎的视频分享平台 YouTube 上视频中提到的安全问题。
结果
从 YouTube 上识别出 15402 个包含负面情绪或烟雾词的产品评论视频，并仔细手动查看以验证是否确实提到了安全隐患。共发现 496 个真实的安全问题（3.2%）。在包含烟雾词的 9453 个视频中，有 322 个（3.4%）提到了安全问题，而在包含负面情绪词的 5949 个视频中，只有 174 个（2.9%）提到了安全问题。仅 1%的随机选择视频提到了安全隐患。
结论
通过比较标题或描述中包含情感词和烟雾词的视频中真正包含安全问题的视频数量，我们表明烟雾词比情感词更能准确预测基于视频的产品评论中的安全隐患。本研究还发现了在线基于视频的产品评论中真正的安全隐患与误报之间的指示性词汇。
实际应用
制造商和消费者产品安全组织可以使用本文生成的烟雾词列表和词汇子组，更有效地从在线视频中识别产品安全问题。该项目还为未来旨在从在线视频或评论中发现安全问题的项目提供了现实的资源估计基准。
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