@inproceedings{02581ac69fcf4aae9d30e924f903c049,
title = "Generation like: Comparative characteristics in instagram",
abstract = "The emergence of social media has had a significant impact on how people communicate and socialize. Teens use social media to make and maintain social connections with friends and build their reputation. However, the way of analyzing the characteristics of teens in social media has mostly relied on ethnographic accounts or quantitative analyses with small datasets. This paper shows the possibility of detecting age information in user profiles by using a combination of textual and facial recognition methods and presents a comparative study of 27K teens and adults in Instagram. Our analysis highlights that (1) teens tend to post fewer photos but highly engage in adding more tags to their own photos and receiving more Likes and comments about their photos from others, and (2) to post more selfies and express themselves more than adults, showing a higher sense of self-representation. We demonstrate the application of our novel method that shows clear trends of age differences as well as substantiates previous insights in social media.",
author = "Jang, {Jin Yea} and Kyungsik Han and Shih, {Patrick C.} and Dongwon Lee",
note = "Publisher Copyright: {\textcopyright} Copyright 2015 ACM.; 33rd Annual CHI Conference on Human Factors in Computing Systems, CHI 2015 ; Conference date: 18-04-2015 Through 23-04-2015",
year = "2015",
month = apr,
day = "18",
doi = "10.1145/2702123.2702555",
language = "English (US)",
series = "Conference on Human Factors in Computing Systems - Proceedings",
publisher = "Association for Computing Machinery",
pages = "4039--4042",
booktitle = "CHI 2015 - Proceedings of the 33rd Annual CHI Conference on Human Factors in Computing Systems",
}