Understanding Users' Vaping Experiences from Social Media: Initial Study Using Sentiment Opinion Summarization Techniques.
Understanding Users' Vaping Experiences from Social Media: Initial Study Using Sentiment Opinion Summarization Techniques.
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从社交媒体了解用户的电子烟体验：使用情绪意见总结技术的初步研究
DOI：
10.2196/jmir.9373
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发表时间：
2018-08-15
影响因子：
7.4
通讯作者：
Leischow SJ
中科院分区：
文献类型：
--
作者：
Li Q;Wang C;Liu R;Wang L;Zeng DD;Leischow SJ
电子烟液是电子尼古丁输送系统（ENDS）的主要成分之一。ENDS审查意见可以作为使用模式的早期警告，甚至可以作为与使用特定电子液体有关的问题或不良事件的指标-就像食品和药物管理局（FDA）跟踪的关于药物的反应类型一样。这项研究旨在使用情感意见总结技术来了解用户的“vaping”体验，这可以帮助描述消费者如何看待特定的电子液体及其特征（例如，风味，喉咙冲击和蒸汽产生）。我们使用JuiceDB的公共应用程序编程接口收集了2013年6月27日至2017年12月31日期间JuiceDB上的电子液体评论。该数据集包含8058个电子液体产品的27，070条评论。每个评论都伴随着电子液体的整体评级和一组4个方面的评级，每个评级的范围为1-5：风味准确性，喉咙命中，价值和云生产。采用基于迭代二分法3（ID 3）的影响因素分析模型来学习影响电子烟使用的关键因素。然后，采用细粒度情感分析来挖掘与电子液体相关的vaping体验的各个方面的意见。我们发现，口味的准确性和价值是影响用户对电子液体情绪的两个最重要的方面。在JuiceDB的评论中，67.83%（18，362/27，070）是正面的，而12.67%（3430/27，070）是负面的。这表明用户普遍对电子液体持积极态度。在9种口味中，水果味和甜味是最受欢迎的两种。果味和甜味的口感好甜、性价比合理、喉感强，用户对果味和甜味的口味比较满意，而“奇怪”的口味会让用户不喜欢。与此同时，用户抱怨一些电子液体价格过高或昂贵，质量差，喉咙痛。有2342种水果电子液体和2049种甜味电子液体。分别有55.81%（1307/2342）和59.83%（1226/2049）对果味电子烟液和甜味电子烟液持积极态度，分别有13.62%（319/2342）和12.88%（264/2049）持消极态度。伟大的口味和良好的蒸汽有助于积极评价水果和甜产品。然而，“酸”或“苦”等不良口味导致负面评价。这些发现可以帮助企业和政策制定者进一步提高产品质量和制定有效的政策。该研究提供了一种基于情感意见摘要技术的有效机制，用于分析用户的ENDS vaping体验。利用该方法可以发现消费者对电子烟产品外观和产品的情感意见，对电子烟产品的监控和提高工作效率具有重要意义。
E-liquid is one of the main components in electronic nicotine delivery systems (ENDS). ENDS review comments could serve as an early warning on use patterns and even function to serve as an indicator of problems or adverse events pertaining to the use of specific e-liquids—much like types of responses tracked by the Food and Drug Administration (FDA) regarding medications. This study aimed to understand users’ “vaping” experience using sentiment opinion summarization techniques, which can help characterize how consumers think about specific e-liquids and their characteristics (eg, flavor, throat hit, and vapor production). We collected e-liquid reviews on JuiceDB from June 27, 2013 to December 31, 2017 using its public application programming interface. The dataset contains 27,070 reviews for 8058 e-liquid products. Each review is accompanied by an overall rating and a set of 4 aspect ratings of an e-liquid, each on a scale of 1-5: flavor accuracy, throat hit, value, and cloud production. An iterative dichotomiser 3 (ID3)-based influential aspect analysis model was adopted to learn the key elements that impact e-liquid use. Then, fine-grained sentiment analysis was employed to mine opinions on various aspects of vaping experience related to e-liquids. We found that flavor accuracy and value were the two most important aspects that affected users’ sentiments toward e-liquids. Of reviews in JuiceDB, 67.83% (18,362/27,070) were positive, while 12.67% (3430/27,070) were negative. This indicates that users generally hold positive attitudes toward e-liquids. Among the 9 flavors, fruity and sweet were the two most popular. Great and sweet tastes, reasonable value, and strong throat hit made users satisfied with fruity and sweet flavors, whereas “strange” tastes made users dislike those flavors. Meanwhile, users complained about some e-liquids’ steep or expensive prices, bad quality, and harsh throat hit. There were 2342 fruity e-liquids and 2049 sweet e-liquids. There were 55.81% (1307/2342) and 59.83% (1226/2049) positive sentiments and 13.62% (319/2342) and 12.88% (264/2049) negative sentiments toward fruity e-liquids and sweet e-liquids, respectively. Great flavors and good vapors contributed to positive reviews of fruity and sweet products. However, bad tastes such as “sour” or “bitter” resulted in negative reviews. These findings can help businesses and policy makers to further improve product quality and formulate effective policy. This study provides an effective mechanism for analyzing users’ ENDS vaping experience based on sentiment opinion summarization techniques. Sentiment opinions on aspect and products can be found using our method, which is of great importance to monitor e-liquid products and improve work efficiency.
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影响因子：
7.4
作者：
Kim AE;Hopper T;Simpson S;Nonnemaker J;Lieberman AJ;Hansen H;Guillory J;Porter L
通讯作者：
Porter L
影响因子：
12.7
作者：
Cheney, Marshall;Gowin, Mary;Wann, Taylor Franklin
通讯作者：
Wann, Taylor Franklin
症状分析及其与电子液体成分的潜在关联：社交媒体研究
影响因子：
4.5
作者：
Li Q;Zhan Y;Wang L;Leischow SJ;Zeng DD
通讯作者：
Zeng DD
社交聆听： Twitter 上电子烟讨论的内容分析。
影响因子：
7.4
作者：
Cole-Lewis H;Pugatch J;Sanders A;Varghese A;Posada S;Yun C;Schwarz M;Augustson E
通讯作者：
Augustson E
影响因子：
5.2
作者：
Kostygina G;Glantz SA;Ling PM
通讯作者：
Ling PM