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Teens are from Mars, Adults are from Venus": Analyzing and Predicting Age Groups with Behavioral Characteristics in Instagram

Cited 9 time in Web of Science Cited 10 time in Scopus
Authors

Han, Kyungsik; Lee, Sanghack; Jang, Jin Yea; Jung, Yong; Lee, Dongwon

Issue Date
2016
Publisher
ASSOC COMPUTING MACHINERY
Citation
PROCEEDINGS OF THE 2016 ACM WEB SCIENCE CONFERENCE (WEBSCI'16), pp.35-44
Abstract
We present behavioral characteristics of teens and adults in Instagram and prediction of them from their behaviors. Based on two independently created datasets from user profiles and tags, we identify teens and adults, and carry out comparative analyses on their online behaviors. Our study reveals: (1) significant behavioral differences between two age groups; (2) the empirical evidence of classifying teens and adults with up to 82% accuracy, using traditional predictive models, while two baseline methods achieve 68% at best; and (3) the robustness of our models by achieving 76%-81% when tested against an independent dataset obtained without using user profiles or tags. Our datasets are available at: https://goo.gl/LqTYNv
URI
https://hdl.handle.net/10371/201565
DOI
https://doi.org/10.1145/2908131.2908160
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  • Graduate School of Data Science
Research Area Causal Decision Making, Causal Discovery, Causal Inference

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