Exploring tag-based like networks

Kyungsik Han, Jin Yea Jang, Dongwon Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Citations (Scopus)

Abstract

The emergence of social media has had a significant impact on how people communicate, interact, and socialize. People engage in social media in different ways by not only adding content such as photos, texts, and videos, but also adding tags, Likes, comments, and following others. Through these activities, people form and develop social connections and networks. In this paper, we present a two-dimensional Like network formed and developed by people who have a same tag in their photos. Based on the dataset consisting of 51K photos posted by 36K users in Instagram, we present the structural and relational aspects of tag-based Like networks. Our study results highlight that Like networks have different sizes and degrees of network components depending on a tag type. We also found that a large portion of Likes came from random users for all networks.

Original languageEnglish (US)
Title of host publicationCHI 2015 - Extended Abstracts Publication of the 33rd Annual CHI Conference on Human Factors in Computing Systems
Subtitle of host publicationCrossings
PublisherAssociation for Computing Machinery
Pages1941-1946
Number of pages6
ISBN (Electronic)9781450331463
DOIs
StatePublished - Apr 18 2015
Event33rd Annual CHI Conference on Human Factors in Computing Systems, CHI EA 2015 - Seoul, Korea, Republic of
Duration: Apr 18 2015Apr 23 2015

Publication series

NameConference on Human Factors in Computing Systems - Proceedings
Volume18

Other

Other33rd Annual CHI Conference on Human Factors in Computing Systems, CHI EA 2015
CountryKorea, Republic of
CitySeoul
Period4/18/154/23/15

Fingerprint

Network components

All Science Journal Classification (ASJC) codes

  • Software
  • Human-Computer Interaction
  • Computer Graphics and Computer-Aided Design

Cite this

Han, K., Jang, J. Y., & Lee, D. (2015). Exploring tag-based like networks. In CHI 2015 - Extended Abstracts Publication of the 33rd Annual CHI Conference on Human Factors in Computing Systems: Crossings (pp. 1941-1946). (Conference on Human Factors in Computing Systems - Proceedings; Vol. 18). Association for Computing Machinery. https://doi.org/10.1145/2702613.2732908
Han, Kyungsik ; Jang, Jin Yea ; Lee, Dongwon. / Exploring tag-based like networks. CHI 2015 - Extended Abstracts Publication of the 33rd Annual CHI Conference on Human Factors in Computing Systems: Crossings. Association for Computing Machinery, 2015. pp. 1941-1946 (Conference on Human Factors in Computing Systems - Proceedings).
@inproceedings{dbf822df4d38415a8719edf501259f97,
title = "Exploring tag-based like networks",
abstract = "The emergence of social media has had a significant impact on how people communicate, interact, and socialize. People engage in social media in different ways by not only adding content such as photos, texts, and videos, but also adding tags, Likes, comments, and following others. Through these activities, people form and develop social connections and networks. In this paper, we present a two-dimensional Like network formed and developed by people who have a same tag in their photos. Based on the dataset consisting of 51K photos posted by 36K users in Instagram, we present the structural and relational aspects of tag-based Like networks. Our study results highlight that Like networks have different sizes and degrees of network components depending on a tag type. We also found that a large portion of Likes came from random users for all networks.",
author = "Kyungsik Han and Jang, {Jin Yea} and Dongwon Lee",
year = "2015",
month = "4",
day = "18",
doi = "10.1145/2702613.2732908",
language = "English (US)",
series = "Conference on Human Factors in Computing Systems - Proceedings",
publisher = "Association for Computing Machinery",
pages = "1941--1946",
booktitle = "CHI 2015 - Extended Abstracts Publication of the 33rd Annual CHI Conference on Human Factors in Computing Systems",

}

Han, K, Jang, JY & Lee, D 2015, Exploring tag-based like networks. in CHI 2015 - Extended Abstracts Publication of the 33rd Annual CHI Conference on Human Factors in Computing Systems: Crossings. Conference on Human Factors in Computing Systems - Proceedings, vol. 18, Association for Computing Machinery, pp. 1941-1946, 33rd Annual CHI Conference on Human Factors in Computing Systems, CHI EA 2015, Seoul, Korea, Republic of, 4/18/15. https://doi.org/10.1145/2702613.2732908

Exploring tag-based like networks. / Han, Kyungsik; Jang, Jin Yea; Lee, Dongwon.

CHI 2015 - Extended Abstracts Publication of the 33rd Annual CHI Conference on Human Factors in Computing Systems: Crossings. Association for Computing Machinery, 2015. p. 1941-1946 (Conference on Human Factors in Computing Systems - Proceedings; Vol. 18).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - Exploring tag-based like networks

AU - Han, Kyungsik

AU - Jang, Jin Yea

AU - Lee, Dongwon

PY - 2015/4/18

Y1 - 2015/4/18

N2 - The emergence of social media has had a significant impact on how people communicate, interact, and socialize. People engage in social media in different ways by not only adding content such as photos, texts, and videos, but also adding tags, Likes, comments, and following others. Through these activities, people form and develop social connections and networks. In this paper, we present a two-dimensional Like network formed and developed by people who have a same tag in their photos. Based on the dataset consisting of 51K photos posted by 36K users in Instagram, we present the structural and relational aspects of tag-based Like networks. Our study results highlight that Like networks have different sizes and degrees of network components depending on a tag type. We also found that a large portion of Likes came from random users for all networks.

AB - The emergence of social media has had a significant impact on how people communicate, interact, and socialize. People engage in social media in different ways by not only adding content such as photos, texts, and videos, but also adding tags, Likes, comments, and following others. Through these activities, people form and develop social connections and networks. In this paper, we present a two-dimensional Like network formed and developed by people who have a same tag in their photos. Based on the dataset consisting of 51K photos posted by 36K users in Instagram, we present the structural and relational aspects of tag-based Like networks. Our study results highlight that Like networks have different sizes and degrees of network components depending on a tag type. We also found that a large portion of Likes came from random users for all networks.

UR - http://www.scopus.com/inward/record.url?scp=84954200258&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84954200258&partnerID=8YFLogxK

U2 - 10.1145/2702613.2732908

DO - 10.1145/2702613.2732908

M3 - Conference contribution

AN - SCOPUS:84954200258

T3 - Conference on Human Factors in Computing Systems - Proceedings

SP - 1941

EP - 1946

BT - CHI 2015 - Extended Abstracts Publication of the 33rd Annual CHI Conference on Human Factors in Computing Systems

PB - Association for Computing Machinery

ER -

Han K, Jang JY, Lee D. Exploring tag-based like networks. In CHI 2015 - Extended Abstracts Publication of the 33rd Annual CHI Conference on Human Factors in Computing Systems: Crossings. Association for Computing Machinery. 2015. p. 1941-1946. (Conference on Human Factors in Computing Systems - Proceedings). https://doi.org/10.1145/2702613.2732908