research-article

Predicting Tie Strength with the Facebook API

Authors:

Tasos Spiliotopoulos,

Ian OakleyAuthors Info & Claims

PCI '14: Proceedings of the 18th Panhellenic Conference on Informatics

Pages 1 - 5

https://doi.org/10.1145/2645791.2645817

Published: 02 October 2014 Publication History

Abstract

This paper presents a user study that employed a Facebook application to calculate the strength of Facebook users' friendships. Specifically, 18 variables were collected via the Facebook API for 1728 friendships and used to predict tie strength reported by 90 participants. The resulting model had an accuracy of 65.9% in differentiating between strong and weak ties, and 86.3% in differentiating between very strong and weaker ties. The tie-strength calculation was performed in real time by the application, conferring the key advantage that the result can be instantly used by the live application. We argue this functionality has the potential to enable many novel customization and recommendation scenarios. Furthermore, examining the effect of the use of different Facebook features and types of communication on the perceived tie strength gives a more comprehensive understanding of the concept of tie strength in social media and sheds light on people's use of social network sites.

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Cited By

Zou MYan MLi WTang ZYe XFan D(2022)GEM: Execution-Aware Cache Management for Graph AnalyticsAlgorithms and Architectures for Parallel Processing10.1007/978-3-031-22677-9_15(273-292)Online publication date: 10-Oct-2022
https://dl.acm.org/doi/10.1007/978-3-031-22677-9_15
Ahmed JVillata SGovernatori G(2019)Information and friend segregation for online social networks: a user studyAI & Society10.1007/s00146-017-0789-134:4(753-766)Online publication date: 1-Dec-2019
https://dl.acm.org/doi/10.1007/s00146-017-0789-1
Raber FKrüger A(2019)Applications for In-Situ Feedback on Social Network NotificationsHuman-Computer Interaction – INTERACT 201910.1007/978-3-030-29390-1_50(626-629)Online publication date: 23-Aug-2019
https://doi.org/10.1007/978-3-030-29390-1_50
Show More Cited By

Index Terms

Predicting Tie Strength with the Facebook API
1. Human-centered computing
  1. Collaborative and social computing

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Information & Contributors

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Published In

cover image ACM Other conferences

PCI '14: Proceedings of the 18th Panhellenic Conference on Informatics

October 2014

355 pages

ISBN:9781450328975

DOI:10.1145/2645791

General Chairs:
Katsikas Sokratis
Department of Digital Systems, University of Piraeus
,
Hatzopoulos Michael
Department of Informatics and Telecommunications, National and Kapodistrian University of Athens
,
Apostolopoulos Theodoros
Department of Informatics, Athens University of Economics and Business
,
Anagnostopoulos Dimosthenis
Department of Informatics & Telematics, Harokopio University of Athens
,
Program Chairs:
Carayiannis Elias
Department of Systems & Technology Management, School of Business, George Washington University
,
Varvarigou Theodora
School of Electrical and Computer Engineering, National Technical University of Athens
,
Nikolaidou Mara
Department of Informatics & Telematics, Harokopio University of Athens

Copyright © 2014 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

In-Cooperation

Greek Com Soc: Greek Computer Society
Univ. of Piraeus: University of Piraeus
National and Kapodistrian University of Athens: National and Kapodistrian University of Athens
Athens U of Econ & Business: Athens University of Economics and Business

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 02 October 2014

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PCI '14

PCI '14: 18th Panhellenic Conference on Informatics

October 2 - 4, 2014

Athens, Greece

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PCI '14 Paper Acceptance Rate 51 of 102 submissions, 50%;

Overall Acceptance Rate 190 of 390 submissions, 49%

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Cited By

Zou MYan MLi WTang ZYe XFan D(2022)GEM: Execution-Aware Cache Management for Graph AnalyticsAlgorithms and Architectures for Parallel Processing10.1007/978-3-031-22677-9_15(273-292)Online publication date: 10-Oct-2022
https://dl.acm.org/doi/10.1007/978-3-031-22677-9_15
Ahmed JVillata SGovernatori G(2019)Information and friend segregation for online social networks: a user studyAI & Society10.1007/s00146-017-0789-134:4(753-766)Online publication date: 1-Dec-2019
https://dl.acm.org/doi/10.1007/s00146-017-0789-1
Raber FKrüger A(2019)Applications for In-Situ Feedback on Social Network NotificationsHuman-Computer Interaction – INTERACT 201910.1007/978-3-030-29390-1_50(626-629)Online publication date: 23-Aug-2019
https://doi.org/10.1007/978-3-030-29390-1_50
Dwarakanath RCharrier JEnglert FHans RStingl DSteinmetz R(2016)Analyzing the Influence of Instant Messaging on User Relationship Estimation2016 IEEE International Conference on Mobile Services (MS)10.1109/MobServ.2016.18(49-56)Online publication date: Jun-2016
https://doi.org/10.1109/MobServ.2016.18
Socievole ACaputo AMarano SDe Rango FMittal SRisco Martín JCetinkaya D(2015)Multi-layer sociality in opportunistic networksProceedings of the International Symposium on Performance Evaluation of Computer and Telecommunication Systems10.5555/2874988.2874999(1-8)Online publication date: 26-Jul-2015
https://dl.acm.org/doi/10.5555/2874988.2874999
Petkos GPapadopoulos SKompatsiaris Y(2015)Social Circle Discovery in Ego-Networks by Mining the Latent Structure of User Connections and Profile AttributesProceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 201510.1145/2808797.2809303(880-887)Online publication date: 25-Aug-2015
https://dl.acm.org/doi/10.1145/2808797.2809303
Spiliotopoulos T(2015)Studying Social Network Sites via computational methods2015 IEEE 9th International Conference on Research Challenges in Information Science (RCIS)10.1109/RCIS.2015.7128912(498-503)Online publication date: May-2015
https://doi.org/10.1109/RCIS.2015.7128912

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