Modular networks of word correlations on Twitter

TY - JOUR

T1 - Modular networks of word correlations on Twitter

AU - Mathiesen, Joachim

AU - Yde, Pernille

AU - Jensen, Mogens Høgh

PY - 2012/11/9

Y1 - 2012/11/9

N2 - 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.

AB - 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.

U2 - 10.1038/srep00814

DO - 10.1038/srep00814

M3 - Journal article

SN - 2045-2322

VL - 2

SP - 814

JO - Scientific Reports

JF - Scientific Reports

ER -