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


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2014-09

AUTHORS

J. Mathiesen, L. Angheluta, M. H. Jensen

ABSTRACT

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. More... »

PAGES

1849-1858

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1140/epjst/e2014-02230-y

DOI

http://dx.doi.org/10.1140/epjst/e2014-02230-y

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1022297837


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