{"title":"视觉信息和外观：用户生成的照片的视觉属性对评论有用性的影响","authors":"Lijuan Luo , Ling Liu , Yujie Zheng , Jing Chen","doi":"10.1016/j.tele.2024.102164","DOIUrl":null,"url":null,"abstract":"<div><p>Images have become integral to consumers’ sharing of consumption experiences due to their abilities of carrying rich and vivid information. Drawing from the perspective of information theory and the elaboration likelihood model (ELM), this study investigates impacts of visual information and visual appearance of user-generated photos (UGPs) on customers’ perceived review helpfulness. We utilize deep learning techniques to calculate the breadth and depth of photos (visual information), and evaluate the aesthetic value of the photos (visual appearance). By collecting a substantial amount of review, reviewer and restaurant information from the Yelp platform, our results demonstrate that the visual breadth and visual depth of review photos have a significant positive impact on review helpfulness. Notably, reviewer status and review length moderate these effects. These insights offer valuable strategies for both restaurant managers and online restaurant platforms regarding UGP management.</p></div>","PeriodicalId":48257,"journal":{"name":"Telematics and Informatics","volume":"92 ","pages":"Article 102164"},"PeriodicalIF":7.6000,"publicationDate":"2024-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Visual information and appearance: The impact of visual attributes of user-generated photos on review helpfulness\",\"authors\":\"Lijuan Luo , Ling Liu , Yujie Zheng , Jing Chen\",\"doi\":\"10.1016/j.tele.2024.102164\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Images have become integral to consumers’ sharing of consumption experiences due to their abilities of carrying rich and vivid information. Drawing from the perspective of information theory and the elaboration likelihood model (ELM), this study investigates impacts of visual information and visual appearance of user-generated photos (UGPs) on customers’ perceived review helpfulness. We utilize deep learning techniques to calculate the breadth and depth of photos (visual information), and evaluate the aesthetic value of the photos (visual appearance). By collecting a substantial amount of review, reviewer and restaurant information from the Yelp platform, our results demonstrate that the visual breadth and visual depth of review photos have a significant positive impact on review helpfulness. Notably, reviewer status and review length moderate these effects. These insights offer valuable strategies for both restaurant managers and online restaurant platforms regarding UGP management.</p></div>\",\"PeriodicalId\":48257,\"journal\":{\"name\":\"Telematics and Informatics\",\"volume\":\"92 \",\"pages\":\"Article 102164\"},\"PeriodicalIF\":7.6000,\"publicationDate\":\"2024-07-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Telematics and Informatics\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0736585324000686\",\"RegionNum\":2,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"INFORMATION SCIENCE & LIBRARY SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Telematics and Informatics","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0736585324000686","RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"INFORMATION SCIENCE & LIBRARY SCIENCE","Score":null,"Total":0}
Visual information and appearance: The impact of visual attributes of user-generated photos on review helpfulness
Images have become integral to consumers’ sharing of consumption experiences due to their abilities of carrying rich and vivid information. Drawing from the perspective of information theory and the elaboration likelihood model (ELM), this study investigates impacts of visual information and visual appearance of user-generated photos (UGPs) on customers’ perceived review helpfulness. We utilize deep learning techniques to calculate the breadth and depth of photos (visual information), and evaluate the aesthetic value of the photos (visual appearance). By collecting a substantial amount of review, reviewer and restaurant information from the Yelp platform, our results demonstrate that the visual breadth and visual depth of review photos have a significant positive impact on review helpfulness. Notably, reviewer status and review length moderate these effects. These insights offer valuable strategies for both restaurant managers and online restaurant platforms regarding UGP management.
期刊介绍：
Telematics and Informatics is an interdisciplinary journal that publishes cutting-edge theoretical and methodological research exploring the social, economic, geographic, political, and cultural impacts of digital technologies. It covers various application areas, such as smart cities, sensors, information fusion, digital society, IoT, cyber-physical technologies, privacy, knowledge management, distributed work, emergency response, mobile communications, health informatics, social media's psychosocial effects, ICT for sustainable development, blockchain, e-commerce, and e-government.
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