Modular networks of word correlations on Twitter View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2012-12

AUTHORS

Joachim Mathiesen, Pernille Yde, Mogens H. Jensen

ABSTRACT

Complex networks are important tools for analyzing the information flow in many aspects of nature and human society. Using data from the microblogging service Twitter, we study networks of correlations in the occurrence of words from three different categories, international brands, nouns and US major cities. We create networks where the strength of links is determined by a similarity measure based on the rate of co-occurrences of words. In comparison with the null model, where words are assumed to be uncorrelated, the heavy-tailed distribution of pair correlations is shown to be a consequence of groups of words representing similar entities. More... »

PAGES

814

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/srep00814

DOI

http://dx.doi.org/10.1038/srep00814

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1027583449

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/23139863


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