Interpreting nominal compounds for information retrieval
Information Processing and Management: an International Journal - Special issue on natural language processing and information retrieval
Advances in knowledge discovery and data mining
Advances in knowledge discovery and data mining
On-line new event detection and tracking
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Data mining: concepts and techniques
Data mining: concepts and techniques
Statistical Themes and Lessons for Data Mining
Data Mining and Knowledge Discovery
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
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News reports are an important source of information about society. Their analysis allows understanding its current interests and measuring the social importance and influence of different events. In this paper, we use the analysis of news as a means to explore the society interests. We focus on the study of a very common phenomenon of news: the influence of the peak news topics on other current news topics. We propose a simple, statistical text mining method to analyze such influences. We differentiate between the observable associations-- those discovered from the newspapers--and the real-world associations, and propose a technique in which the real ones can be inferred from the observable ones. We illustrate the method with some results obtained from preliminary experiments and argue that the discovery of the ephemeral associations can be translated into knowledge about interests of society and social behavior.