The nature of statistical learning theory
The nature of statistical learning theory
On-line new event detection and tracking
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Learning Approaches for Detecting and Tracking News Events
IEEE Intelligent Systems
Event detection from online news documents for supporting environmental scanning
Decision Support Systems - Special issue: Knowledge management technique
Information diffusion through blogspace
Proceedings of the 13th international conference on World Wide Web
A probabilistic model for retrospective news event detection
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
CHI '06 Extended Abstracts on Human Factors in Computing Systems
Event detection from evolution of click-through data
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Are raw RSS feeds suitable for broad issue scanning? A science concern case study
Journal of the American Society for Information Science and Technology
tagging, communities, vocabulary, evolution
CSCW '06 Proceedings of the 2006 20th anniversary conference on Computer supported cooperative work
Tagging video: conventions and strategies of the YouTube community
Proceedings of the 7th ACM/IEEE-CS joint conference on Digital libraries
The use of topic evolution to help users browse and find answers in news video corpus
Proceedings of the 15th international conference on Multimedia
Evaluating tagging behavior in social bookmarking systems: metrics and design heuristics
Proceedings of the 2007 international ACM conference on Supporting group work
Understanding the efficiency of social tagging systems using information theory
Proceedings of the nineteenth ACM conference on Hypertext and hypermedia
Can Social Tags Help You Find What You Want?
ECDL '08 Proceedings of the 12th European conference on Research and Advanced Technology for Digital Libraries
Social tags as news event detectors
Journal of Information Science
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The accelerated news cycle and constantly emerging news-worthy events have led to `citizen journalism' where people who are non-journalists collect, analyze and disseminate news pieces. This paper seeks to leverage tags drawn from iReport, an active citizen journalism Website to detect major news events. The goal is to examine the coverage and efficacy of news detected in iReport vis-à-vis those reported in the mainstream media. The data collection procedure involved manually culling major news events reported in Fox News between April 8 2008 and June 6 2008. Additionally, 81,815 tags from 15,216 documents were drawn from iReport during the same study period. Relative frequencies of all unique tags were used to check for spikes and bursts in the dataset. The results show that out of the 10 major news events reported in Fox News, five could be detected in iReport. This paper concludes by presenting the main findings, limitations and suggestions for future research.