| With the continuous development of the Internet in recent years,the web2.0 era indicates that science and technology has become an indispensable part of today's society.The development of the Internet has brought many new products.Among them,online shopping has developed especially rapidly.Due to the characteristics of online shopping,consumers often read online comments before purchasing goods,and select useful online comments to assist them in purchasing.decision making.Moreover,with the popularity of smart phones in recent years,more and more electronic devices that can be photographed are emerging one after another.The form of comments is no longer limited to text comments and ratings.More and more consumers are beginning to ask for“pictures”when reading comments.The picture with the truth is combined with comments.Therefore,the management of user generated images is worthy of the attention of e-commerce platforms and merchants.Previous research on online reviews has yielded fruitful results.The key question surrounding what kind of comments is more useful is that scholars explore the four perspectives of text comments,star ratings,commenter information characteristics,and user-generated images.For the first three angles,scholars and experts have made great achievements,but since user-generated images have only begun to emerge in recent years,scholars and experts have only focused on user-generated images from the perspective of user-generated images.The direct impact of the number of images generated by the user and the user on the usefulness of the comment does not take into account the effect of the textual comment on the usefulness of the online comment after the introduction of the user-generated image.Based on the theory of interpretation level and the theory of double coding,this paper constructs a theoretical model of the effect of user-generated images on the depth of text comments and the influence of commentary emotions on the usefulness of comments,and uses the Java crawler program to capture from Ctrip.com as a sample of this study,2,998,997 online reviews of hotels in Beijing were conducted using R-lang language using Poisson regression,literature analysis,and empirical research methods to conduct data analysis and hypothesis testing of theoretical models.The results of data analysis show that:First,the depth of comments presents an inverted "U" relationship to the usefulness of comments,and when online comments include user-generated images,the depth of comments has a greater impact on the usefulness of comments.Second,positive comments are positive.To influence the usefulness of the comments,and when the online comments contain user-generated images,the positive comments have a stronger impact on the usefulness of the comments;third,the negative comments positively affect the usefulness of the reviews,and when the online reviews include user-generated When the picture is taken,the negative comments have a stronger influence on the usefulness of the comments.This research broadens the research field of the usefulness of online reviews,reveals the interaction between user-generated images and text comments and its impact on the usefulness of online reviews.Specifically:first,in previous studies,the depth of comments affects online.Based on the usefulness of the review,this study further found that user-generated images will not only reduce the impact of comment depth on the usefulness of comments,but will increase the impact of comment depth on the usefulness of comments.Second,in previous studies,it was found that commentary emotions will affect Based on the usefulness of online reviews,this study further found that the effect of user-generated images on enhancing the extreme emotions on the usefulness of comments confirms that "there is a picture with truth".This study is more effective for e-commerce platforms and merchants to manage and use online reviews,especially to integrate consumer reviews with text comments and user-generated images,and to improve the performance of platforms and businesses. |
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