Referral Web: combining social networks and collaborative filtering
Communications of the ACM
Authoritative sources in a hyperlinked environment
Journal of the ACM (JACM)
Expertise recommender: a flexible recommendation system and architecture
CSCW '00 Proceedings of the 2000 ACM conference on Computer supported cooperative work
Working Knowledge: How Organizations Manage What They Know
Working Knowledge: How Organizations Manage What They Know
Group formation in large social networks: membership, growth, and evolution
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Structure and evolution of online social networks
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Internet-scale collection of human-reviewed data
Proceedings of the 16th international conference on World Wide Web
Optimizing web search using social annotations
Proceedings of the 16th international conference on World Wide Web
Measurement and analysis of online social networks
Proceedings of the 7th ACM SIGCOMM conference on Internet measurement
International Journal of Human-Computer Studies
Predictors of answer quality in online Q&A sites
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Knowledge sharing and yahoo answers: everyone knows something
Proceedings of the 17th international conference on World Wide Web
Predicting information seeker satisfaction in community question answering
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
mimir: a market-based real-time question and answer service
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
A measurement-driven analysis of information propagation in the flickr social network
Proceedings of the 18th international conference on World wide web
The value of socially tagged urls for a search engine
Proceedings of the 18th international conference on World wide web
SmallBlue: Social Network Analysis for Expertise Search and Collective Intelligence
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Social search and discovery using a unified approach
Proceedings of the 20th ACM conference on Hypertext and hypermedia
On the evolution of user interaction in Facebook
Proceedings of the 2nd ACM workshop on Online social networks
The use of categorization information in language models for question retrieval
Proceedings of the 18th ACM conference on Information and knowledge management
Personalized social search based on the user's social network
Proceedings of the 18th ACM conference on Information and knowledge management
What do people ask their social networks, and why?: a survey study of status message q&a behavior
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
The anatomy of a large-scale social search engine
Proceedings of the 19th international conference on World wide web
What is Twitter, a social network or a news media?
Proceedings of the 19th international conference on World wide web
Measurement and analysis of an online content voting network: a case study of Digg
Proceedings of the 19th international conference on World wide web
An elaborated model of social search
Information Processing and Management: an International Journal
Supporting synchronous social q&a throughout the question lifecycle
Proceedings of the 20th international conference on World wide web
Effects of community size and contact rate in synchronous social q&a
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
CollabSeer: a search engine for collaboration discovery
Proceedings of the 11th annual international ACM/IEEE joint conference on Digital libraries
Hi-index | 0.00 |
Question and Answer (Q&A) websites such as Yahoo!Answers provide a platform where users can post questions and receive answers. These systems take advantage of the collective intelligence of users to find information. In this paper, we analyze the online social network (OSN) in Yahoo!Answers. Based on a large amount of our collected data, we studied the OSN's structural properties, which reveals strikingly distinct properties such as low link symmetry and weak correlation between indegree and outdegree. After studying the knowledge base and behaviors of the users, we find that a small number of top contributors answer most of the questions in the system. Also, each top contributor focuses on only a few knowledge categories. In addition, the knowledge categories of the users are highly clustered. We also study the knowledge base in a user's social network, which reveals that the members in a user's social network share only a few knowledge categories. Based on the findings, we provide guidance in the design of spammer detection algorithms and distributed Q&A systems. We also propose a friendship-knowledge oriented Q&A framework that synergically combines current OSN-based Q&A and web Q&A. We believe that the results presented in this paper are crucial in understanding the collective intelligence in the web Q&A OSNs and lay a cornerstone for the evolution of next-generation Q&A systems.