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ECIR
2016
Springer

Inferring the Socioeconomic Status of Social Media Users Based on Behaviour and Language

4 years 3 months ago
Inferring the Socioeconomic Status of Social Media Users Based on Behaviour and Language
This paper presents a method to classify social media users based on their socioeconomic status. Our experiments are conducted on a curated set of Twitter profiles, where each user is represented by the posted text, topics of discussion, interactive behaviour and estimated impact on the microblogging platform. Initially, we formulate a 3-way classification task, where users are classified as having an upper, middle or lower socioeconomic status. A nonlinear, generative learning approach using a composite Gaussian Process kernel provides significantly better classification accuracy (75 %) than a competitive linear alternative. By turning this task into a binary classification – upper vs. medium and lower class – the proposed classifier reaches an accuracy of 82 %.
Vasileios Lampos, Nikolaos Aletras, Jens K. Geyti,
Added 02 Apr 2016
Updated 02 Apr 2016
Type Journal
Year 2016
Where ECIR
Authors Vasileios Lampos, Nikolaos Aletras, Jens K. Geyti, Bin Zou, Ingemar J. Cox
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