A Multitude of Opinions: Mining Online Rating Data

• Main Authors: LAUW, Hady Wirawan, LIM, Ee Peng
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2007
• Subjects: Databases and Information Systems; Numerical Analysis and Scientific Computing
• Online Access: https://ink.library.smu.edu.sg/sis_research/1262; https://ink.library.smu.edu.sg/context/sis_research/article/2261/viewcontent/HLauw_2007_MultitudeOpinions.pdf
• Institution: Singapore Management University

Online rating system is a popular feature of Web 2.0 applications. It typically involves a set of reviewers assigning rating scores (based on various evaluation criteria) to a set of objects. We identify two objectives for research on online rating data, namely achieving effective evaluation of objects and learning behaviors of reviewers/objects. These two objectives have conventionally been pursued separately. We argue that the future research direction should focus on the integration of these two objectives, as well as the integration between rating data and other types of data.