An algorithmic framework for performing collaborative filtering
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Analysis of recommendation algorithms for e-commerce
Proceedings of the 2nd ACM conference on Electronic commerce
Learning Collaborative Information Filters
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Identifying the influential bloggers in a community
WSDM '08 Proceedings of the 2008 International Conference on Web Search and Data Mining
Lessons from the Netflix prize challenge
ACM SIGKDD Explorations Newsletter - Special issue on visual analytics
User Reputation Evaluation Using Co-occurrence Feature and Collective Intelligence
OCSC '09 Proceedings of the 3d International Conference on Online Communities and Social Computing: Held as Part of HCI International 2009
What is Twitter, a social network or a news media?
Proceedings of the 19th international conference on World wide web
A Content Recommendation System Based on Category Correlations
ICCGI '10 Proceedings of the 2010 Fifth International Multi-conference on Computing in the Global Information Technology
Expert Systems with Applications: An International Journal
A movie recommendation algorithm based on genre correlations
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Modelling user participation in organisations as networks
Expert Systems with Applications: An International Journal
Detecting malicious tweets in trending topics using a statistical analysis of language
Expert Systems with Applications: An International Journal
Identifying representative ratings for a new item in recommendation system
Proceedings of the 7th International Conference on Ubiquitous Information Management and Communication
Expert Systems with Applications: An International Journal
Identifying interesting Twitter contents using topical analysis
Expert Systems with Applications: An International Journal
| Hi-index | 12.06 |
Our many various relationships with persons from home, work and school give rise to our social networks. In a social network, people receive, provide, and pass a great deal of information. In this process, we often observe that certain individuals have especially strong influences on others. We call these highly influential people opinion leaders. Since the late 20th century, the number of Internet users has increased rapidly, and a huge number of people now interact with each other in online social networks. In this way, the Web community has become similar to real-world society. Internet users receive information not only from the mass media, but also from opinion leaders. For example, online articles posted by influential bloggers are often used as marketing tools or political advertisements, due to their huge influence on other users. Therefore, it is important and useful to identify the influential users in an online society. We thus propose a simple yet reliable algorithm that identifies opinion leaders in a cyber social network. In this paper, we first describe our algorithm for identifying influential users in an online society. We then demonstrate the validity of the selection of representative reviewers using the Yahoo! music and GroupLens movie databases and performing 10-fold cross-validation and z-tests.