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Mining the News: Trends, Associations, and Deviations

By Manuel Montes-y-Gómez, Alexander Gelbukh and Aurelio López-López

Abstract

News reports are an important source of information about society. Their analysis allows to understand its current interests and to measure the social importance of many events.\ud In this paper, we use the analysis of news as a means to explore the society interests. We present a text mining technique that uncovers trends, discovers associations and detects deviations from news notes. The method uses simple statistical representations of the news reports (frequencies\ud and probability distributions of topics) and statistical measures (the average or median, the standard deviation, and the correlation coefficient) for analysis and discovery of useful information.\ud We illustrate the method with some results obtained from preliminary experiments and discuss their main implications

Topics: Work done under partial support of CONACyT, REDII
Year: 2001
OAI identifier: oai:CiteSeerX.psu:10.1.1.19.3319
Provided by: CiteSeerX
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