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Photos don't have me, but how do you know me?: Analyzing and predicting users on instagram

Authors
Han, KyungsikJo, YonggeolJeon, YoungseungKim, BogoanSong, JunhoKim, Sang-Wook
Issue Date
Jul-2018
Publisher
Association for Computing Machinery, Inc
Keywords
Age and gender; Comparison analysis; Instagram; Social media; User modeling
Citation
UMAP 2018 - Adjunct Publication of the 26th Conference on User Modeling, Adaptation and Personalization, pp.251 - 256
Indexed
SCOPUS
Journal Title
UMAP 2018 - Adjunct Publication of the 26th Conference on User Modeling, Adaptation and Personalization
Start Page
251
End Page
256
URI
https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/149697
DOI
10.1145/3213586.3225232
ISSN
0000-0000
Abstract
This paper presents a comprehensive analysis on social media use and engagement by age and gender on Instagram. We define five user age groups (from 10s to 50s) and two user gender groups (males and females), and compare them based on three aspects: Activity, image object, and tag. We especially excluded the information that indicates human (e.g., selfies, faces, body) for each aspect in order to examine whether users are still identifiable without that information. Our study results indicate that each user group exhibits unique characteristics and the features from each aspect can be used to develop user classification models (82% for gender and 43% for age classification) without relying on the information that specifically indicates age and gender.
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서울 공과대학 > 서울 컴퓨터소프트웨어학부 > 1. Journal Articles

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