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

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 e...

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Bibliographic Details
Published inThe European physical journal. ST, Special topics Vol. 223; no. 9; pp. 1849 - 1858
Main Authors Mathiesen, J., Angheluta, L., Jensen, M. H.
Format Journal Article
LanguageEnglish
Published Berlin/Heidelberg Springer Berlin Heidelberg 01.09.2014
Subjects
Atomic
Classical and Continuum Physics
Condensed Matter Physics
Materials Science
Measurement Science and Instrumentation
Molecular
Optical and Plasma Physics
Physics
Physics and Astronomy
Regular Article
Soft Matter in Confinement: Systems from Biology to Physics
Occurrence Rate
Sentiment Score
European Physical Journal Special Topic
Twitter User
Probability Distribution Function
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Summary: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.
ISSN:1951-6355
1951-6401
DOI:10.1140/epjst/e2014-02230-y