Statistics of co-occurring keywords in confined text messages on Twitter

TY - JOUR

T1 - Statistics of co-occurring keywords in confined text messages on Twitter

AU - Mathiesen, Joachim

AU - Angheluta, L.

AU - Jensen, M. H.

PY - 2014/9/1

Y1 - 2014/9/1

N2 - Online social media such as the micro-blogging site Twitter has become a rich source of real-time data on online human behaviors. Here we analyze the occurrence and co-occurrence frequency of keywords in user posts on Twitter. From the occurrence rate of major international brand names, we provide examples of predictions of brand-user behaviors. From the co-occurrence rates, we further analyze the user-perceived relationships between international brand names and construct the corresponding relationship networks. In general the user activity on Twitter is highly intermittent and we show that the occurrence rate of brand names forms a highly correlated time signal.

AB - Online social media such as the micro-blogging site Twitter has become a rich source of real-time data on online human behaviors. Here we analyze the occurrence and co-occurrence frequency of keywords in user posts on Twitter. From the occurrence rate of major international brand names, we provide examples of predictions of brand-user behaviors. From the co-occurrence rates, we further analyze the user-perceived relationships between international brand names and construct the corresponding relationship networks. In general the user activity on Twitter is highly intermittent and we show that the occurrence rate of brand names forms a highly correlated time signal.

U2 - 10.1140/epjst/e2014-02230-y

DO - 10.1140/epjst/e2014-02230-y

M3 - Journal article

AN - SCOPUS:84919933493

SN - 1951-6355

VL - 223

SP - 1849

EP - 1858

JO - European Physical Journal. Special Topics

JF - European Physical Journal. Special Topics

IS - 9

ER -