@inproceedings{a79bf5936fa8465a9708766bc5d2df4a,
title = "A statistical approach to the discovery of ephemeral associations among news topics",
abstract = "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.",
author = "M. Montes-Y-G{\'o}mez and A. Gelbukh and A. L{\'o}pez-L{\'o}pez",
note = "Publisher Copyright: {\textcopyright} Springer-Verlag Berlin Heidelberg 2001.; 12th International Conference on Database and Expert Systems Applications, DEXA 2001 ; Conference date: 03-09-2001 Through 05-09-2001",
year = "2001",
doi = "10.1007/3-540-44759-8_49",
language = "Ingl{\'e}s",
isbn = "3540425276",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "491--500",
editor = "Mayr, {Heinrich C.} and Jiri Lazansky and Gerald Quirchmayr and Pavel Vogel",
booktitle = "Database and Expert Systems Applications - 12th International Conference, DEXA 2001, Proceedings",
address = "Alemania",
}