Monitoring public attention for a topic is of interest for many target groups like social scientists or public relations. Several examples demonstrate how public attention caused by real-world events is accompanied by an accordant visibility of topics on the web. It is shown that the hitcount values of a search engine we use as initial visibility values have to be adjusted by taking the semantic relations between topics into account. We model these relations using semantic networks and present an algorithm based on Spreading Activation that adjusts the initial visibilities. The concept of co-visibility between topics is integrated to obtain an algorithm that mostly complies with an intuitive view on visibilities. The reliability of search engine hitcounts is discussed. © 2006 Springer-Verlag.
CITATION STYLE
Kiefer, P., Stein, K., & Schlieder, C. (2006). Visibility analysis on the web using co-visibilities and semantic networks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4289 LNAI, pp. 34–50). https://doi.org/10.1007/11908678_3
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