Social Information Processing in News Aggregation
IEEE Internet Computing
Analysis of social voting patterns on digg
Proceedings of the first workshop on Online social networks
Adaptive search engines as discovery games: an evolutionary approach
Proceedings of the 6th International Conference on Advances in Mobile Computing and Multimedia
Community Adaptive Search Engines
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The "top N" news recommender: count distortion and manipulation resistance
Proceedings of the fifth ACM conference on Recommender systems
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Intelligent Social Media Indexing and Sharing Using an Adaptive Indexing Search Engine
ACM Transactions on Intelligent Systems and Technology (TIST)
Automatic categorisation of comments in social news websites
Expert Systems with Applications: An International Journal
Open government 2.0: citizen empowerment through open data, web and mobile apps
Proceedings of the 6th International Conference on Theory and Practice of Electronic Governance
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The social news aggregator Digg allows users to submit and moderate stories by voting on (digging) them. As is true of most social sites, user participation on Digg is non-uniformly distributed, with few users contributing a disproportionate fraction of content. We studied user participation on Digg, to see whether it is motivated by competition, fueled by user ranking, or social factors, such as community acceptance. For our study we collected activity data of the top users weekly over the course of a year. We computed the number of stories users submitted, dugg or commented on weekly. We report a spike in user activity in September 2006, followed by a gradual decline, which seems unaffected by the elimination of user ranking. The spike can be explained by a controversy that broke out at the beginning of September 2006. We believe that the lasting acrimony that this incident has created led to a decline of top user participation on Digg.