Am i more similar to my followers or followees? Analyzing homophily effect in directed social networks

Mohammad Ali Abbasi, Reza Zafarani, Jiliang Tang, Huan Liu

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

4 Citations (Scopus)

Abstract

Homophily is the formation of social ties between two individuals due to similar characteristics or interests. Based on homophily, in a social network it is expected to observe a higher degree of homogeneity among connected than disconnected people. Many researchers use this simple yet effective principal to infer users' missing information and interests based on the information provided by their neighbors. In a directed social network, the neighbors can be further divided into followers and followees. In this work, we investigate the homophily effect in a directed network. To explore the homophily effect in a directed network, we study if a user's personal preferences can be inferred from those of users connected to her (followers or followees). We investigate which of followers or followees are more effective in helping to infer users' personal preferences. Our findings can help to raise the awareness of users over their privacy and can help them better manage their privacy.

Original languageEnglish (US)
Title of host publicationHT 2014 - Proceedings of the 25th ACM Conference on Hypertext and Social Media
PublisherAssociation for Computing Machinery
Pages200-205
Number of pages6
ISBN (Print)9781450329545
DOIs
StatePublished - 2014
Event25th ACM Conference on Hypertext and Social Media, HT 2014 - Santiago, Chile
Duration: Sep 1 2014Sep 4 2014

Other

Other25th ACM Conference on Hypertext and Social Media, HT 2014
CountryChile
CitySantiago
Period9/1/149/4/14

Keywords

  • homophily
  • preference prediction
  • relational learning
  • social media mining

ASJC Scopus subject areas

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

Cite this

Abbasi, M. A., Zafarani, R., Tang, J., & Liu, H. (2014). Am i more similar to my followers or followees? Analyzing homophily effect in directed social networks. In HT 2014 - Proceedings of the 25th ACM Conference on Hypertext and Social Media (pp. 200-205). Association for Computing Machinery. https://doi.org/10.1145/2631775.2631828

Am i more similar to my followers or followees? Analyzing homophily effect in directed social networks. / Abbasi, Mohammad Ali; Zafarani, Reza; Tang, Jiliang; Liu, Huan.

HT 2014 - Proceedings of the 25th ACM Conference on Hypertext and Social Media. Association for Computing Machinery, 2014. p. 200-205.

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

Abbasi, MA, Zafarani, R, Tang, J & Liu, H 2014, Am i more similar to my followers or followees? Analyzing homophily effect in directed social networks. in HT 2014 - Proceedings of the 25th ACM Conference on Hypertext and Social Media. Association for Computing Machinery, pp. 200-205, 25th ACM Conference on Hypertext and Social Media, HT 2014, Santiago, Chile, 9/1/14. https://doi.org/10.1145/2631775.2631828
Abbasi MA, Zafarani R, Tang J, Liu H. Am i more similar to my followers or followees? Analyzing homophily effect in directed social networks. In HT 2014 - Proceedings of the 25th ACM Conference on Hypertext and Social Media. Association for Computing Machinery. 2014. p. 200-205 https://doi.org/10.1145/2631775.2631828
Abbasi, Mohammad Ali ; Zafarani, Reza ; Tang, Jiliang ; Liu, Huan. / Am i more similar to my followers or followees? Analyzing homophily effect in directed social networks. HT 2014 - Proceedings of the 25th ACM Conference on Hypertext and Social Media. Association for Computing Machinery, 2014. pp. 200-205
@inproceedings{91a32dd882ed4068a4bef0214325af46,
title = "Am i more similar to my followers or followees? Analyzing homophily effect in directed social networks",
abstract = "Homophily is the formation of social ties between two individuals due to similar characteristics or interests. Based on homophily, in a social network it is expected to observe a higher degree of homogeneity among connected than disconnected people. Many researchers use this simple yet effective principal to infer users' missing information and interests based on the information provided by their neighbors. In a directed social network, the neighbors can be further divided into followers and followees. In this work, we investigate the homophily effect in a directed network. To explore the homophily effect in a directed network, we study if a user's personal preferences can be inferred from those of users connected to her (followers or followees). We investigate which of followers or followees are more effective in helping to infer users' personal preferences. Our findings can help to raise the awareness of users over their privacy and can help them better manage their privacy.",
keywords = "homophily, preference prediction, relational learning, social media mining",
author = "Abbasi, {Mohammad Ali} and Reza Zafarani and Jiliang Tang and Huan Liu",
year = "2014",
doi = "10.1145/2631775.2631828",
language = "English (US)",
isbn = "9781450329545",
pages = "200--205",
booktitle = "HT 2014 - Proceedings of the 25th ACM Conference on Hypertext and Social Media",
publisher = "Association for Computing Machinery",

}

TY - GEN

T1 - Am i more similar to my followers or followees? Analyzing homophily effect in directed social networks

AU - Abbasi, Mohammad Ali

AU - Zafarani, Reza

AU - Tang, Jiliang

AU - Liu, Huan

PY - 2014

Y1 - 2014

N2 - Homophily is the formation of social ties between two individuals due to similar characteristics or interests. Based on homophily, in a social network it is expected to observe a higher degree of homogeneity among connected than disconnected people. Many researchers use this simple yet effective principal to infer users' missing information and interests based on the information provided by their neighbors. In a directed social network, the neighbors can be further divided into followers and followees. In this work, we investigate the homophily effect in a directed network. To explore the homophily effect in a directed network, we study if a user's personal preferences can be inferred from those of users connected to her (followers or followees). We investigate which of followers or followees are more effective in helping to infer users' personal preferences. Our findings can help to raise the awareness of users over their privacy and can help them better manage their privacy.

AB - Homophily is the formation of social ties between two individuals due to similar characteristics or interests. Based on homophily, in a social network it is expected to observe a higher degree of homogeneity among connected than disconnected people. Many researchers use this simple yet effective principal to infer users' missing information and interests based on the information provided by their neighbors. In a directed social network, the neighbors can be further divided into followers and followees. In this work, we investigate the homophily effect in a directed network. To explore the homophily effect in a directed network, we study if a user's personal preferences can be inferred from those of users connected to her (followers or followees). We investigate which of followers or followees are more effective in helping to infer users' personal preferences. Our findings can help to raise the awareness of users over their privacy and can help them better manage their privacy.

KW - homophily

KW - preference prediction

KW - relational learning

KW - social media mining

UR - http://www.scopus.com/inward/record.url?scp=84907391264&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84907391264&partnerID=8YFLogxK

U2 - 10.1145/2631775.2631828

DO - 10.1145/2631775.2631828

M3 - Conference contribution

SN - 9781450329545

SP - 200

EP - 205

BT - HT 2014 - Proceedings of the 25th ACM Conference on Hypertext and Social Media

PB - Association for Computing Machinery

ER -