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题目:The Effect of User Generated Photos on Online Review Helpfulness
时间:2018年6月13日(周三) 上午10:30
地点:经济与管理学院学术报告厅(南校区信远楼2区324)
报告人:樊卫国 (Patrick Fan) 教授
报告人简介:
Dr. Weiguo (Patrick) Fan is a R. B. Pamplin Endowed Chair Professor of Accounting and Information Systems, Full Professor of Computer Science (courtesy) and fellow of the Center for Business Intelligence and Analytics at Virginia Tech. He received his Ph.D. in Business Administration from the Ross School of Business, University of Michigan, Ann Arbor, in 2002, a M. Sce in Computer Science from the National University of Singapore in 1997, and a B. E. in Information and Control Engineering from the Xi'an Jiaotong University, P.R. China, in 1995. His research interests focus on the design and development of novel formation technologies --- information retrieval, data mining, text/web mining, business intelligence techniques, data science, business analytics --- to support better business information management and decision making. He has published more than 180 refereed journal and conference papers. His research has appeared in journals such as Information Systems Research, Journal of  Management Information Systems, Production and Operations Management, Tourism Management, International Journal of Hospitality Management, IEEE Transactions on Knowledge and Data Engineering, Information Systems, Communications of the ACM, Information and Management, Journal of the American Society on Information Science and Technology, Information Processing and Management, Decision Support Systems, Expert Systems and Applications, ACM Transactions on Internet Technology, Pattern Recognition, IEEE Intelligent Systems, Information Sciences, Journal of Informetrics, Information Systems Frontiers, Journal of Computer Information Systems, Pattern Recognition Letters, International Journal of e-Collaboration, and International Journal of Electronic Business, Chinese Management Studies. He currently serves on the editorial boards for several well known IS journals: MIS Quarterly, Journal of Association for Information Systems, Journal of Strategic Information Systems, Information and Management, Information Technology and Management, Journal of Database Management. His research has been cited more than 6100 times according to Google Scholar. His research has been funded by five NSF grants.
报告摘要:
Online reviews have been extensively studied in the hospitality and tourism literature. However, while user-provided photos embedded in online reviews accumulate in large quantities, their informational value has not been well understood likely due to technical challenges. The goal of this study is to introduce deep learning for computer vision to understand information value of online hotel reviews. Using a dataset collected from two social media sites, we compared deep learning models with other machine learning techniques to examine the effect of user-provided photos on review helpfulness. Findings show that deep learning models were more useful in predicting review helpfulness than other models. While user-provided photos alone did not have the same impact as review texts, combining review texts and user-provided photos produced the highest performance. Implications for the applications of deep learning technologies in hospitality and tourism research, as well as limitations and directions for future research, are discussed.
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