Recommender systems have been widely utilized by online merchants and online advertisers to promote their products in order to improve profits. By evaluating customer interests based on their purchase history and relating it to commodities for sale these retailers could excavate out products which are most likely to be chosen by a specific customer. In this case, online ratings given by custome...

Online movie ratings are often used in studies of Internet word-of-mouth, but the cross-platform consistency of such ratings has not been well established. Mean user ratings were obtained for 500 movies using the rating systems in place on Netflix and IMDb. Mean volume was 1,480,931 (SD = 2,636,388) and 104,746 (SD = 193,532) on the Netflix and IMDb sites, respectively, suggesting the movies we...

Ranking problem has attracted much attention in real systems. How to design a robust ranking method is especially significant for online rating systems under the threat of spamming attacks. By building reputation systems for users, many well-performed ranking methods have been applied to address this issue. In this Letter, we propose a group-based ranking method that evaluates users’ reputation...

Subjective perceptions of websites can be reliably measured with questionnaires. But it is unclear how such scores should be interpreted in practice, e.g. is an aesthetics score of 4 points on a 7-point-scale satisfactory? The current paper introduces a ROC-based methodology to establish meaningful cut points for the VisAWI (Visual Aesthetics of Websites Inventory) and it’s short form the VisAW...

In this study, we conducted an online survey and collected 86 reliable responses on both a personality assessment inventory and ratings retail products ratings, with the aim of investigating whether personality characteristics have an impact on user rating behaviors. Besides personality factors, another four independent variables (i.e., age, gender, previous experience on using recommenders and...

We propose a novel unsupervised extractive approach for summarizing online reviews by exploiting review helpfulness ratings. In addition to using the helpfulness ratings for review-level filtering, we suggest using them as the supervision of a topic model for sentence-level content scoring. The proposed method is metadata-driven, requiring no human annotation, and generalizable to different kin...

Today, e-commerce has occupied a large volume of economic exchanges. It is known as one of the most effective business practices. Predicted trust which means trusting an anonymous user is important in online communities. In this paper, the trust was predicted by combining two methods of multiplex network and community detection. In modeling the network in terms of a multiplex network, the relat...

Have2eat is a popular mobile application available for iPhone and Android-based devices that helps users to find and assess nearby restaurants. It lists restaurants located around the device and provides a quick highlight about the opinions expressed by online reviewers. Have2eat summarizes textual reviews by extracting relevant sentences and by automatically generating detailed ratings about s...

The increasing online reviews regarding products and services have provided an important reference for people considering pruchasing a products. The rating prediction thus can further help online shopping portals to shape their recommendation system by recommending products that might get higher ratings. In this project, we conduct the rating prediction for beer review. We conduct the analysis ...

Internet ratings panels represent a distinctive type of online panel. Internet ratings panels are designed to provide systematic data on audience size, demographics, and exposure patterns for individual web sites and mobile applications. These ratings data play a central role in the transactions that take place between online content providers and advertisers, in addition to serving a variety o...