Projects per year
Abstract
Online social networks provide a forum where people make new connections, learn more about the world, get exposed to different points of view, and access information that were previously inaccessible. It is natural to assume that content-delivery algorithms in social networks should not only aim to maximize user engagement but also to offer opportunities for increasing connectivity and enabling social networks to achieve their full potential. Our motivation and aim is to develop methods that foster the creation of new connections, and subsequently, improve the flow of information in the network. To achieve our goal, we propose to leverage the strong triadic closure principle, and consider violations to this principle as opportunities for creating more social links. We formalize this idea as an algorithmic problem related to the densest k-subgraph problem. For this new problem, we establish hardness results and propose approximation algorithms. We identify two special cases of the problem that admit a constant-factor approximation. Finally, we experimentally evaluate our proposed algorithm on real-world social networks, and we additionally evaluate some simpler but more scalable algorithms.
Original language | English |
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Pages (from-to) | 448-476 |
Number of pages | 29 |
Journal | Data Mining and Knowledge Discovery |
Volume | 36 |
Issue number | 1 |
DOIs | |
Publication status | Published - Jan 2022 |
MoE publication type | A1 Journal article-refereed |
Keywords
- Densest subgraph discovery
- Link recommendations
- STC
- Strong triadic closure
Fingerprint
Dive into the research topics of 'Strengthening ties towards a highly-connected world'. Together they form a unique fingerprint.Datasets
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STC datasets
Matakos, A. (Creator), Harvard Dataverse, 1 Jan 2020
DOI: 10.7910/dvn/2sh38f, https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/2SH38F
Dataset
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SoBigDataPlusPlus: Integrated Infrastructure for Social Mining and Big Data Analytics
Lampinen, J. (Principal investigator), Roy, C. (Project Member) & Bhattacharya, K. (Project Member)
01/01/2020 → 31/12/2024
Project: EU: Framework programmes funding
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MLDB: Model Management Systems: Machine learning meets Database Systems
Gionis, A. (Principal investigator), Aslay, C. (Project Member), Ciaperoni, M. (Project Member), Xiao, H. (Project Member), Matakos, A. (Project Member) & Muniyappa, S. (Project Member)
01/09/2019 → 31/08/2023
Project: Academy of Finland: Other research funding
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Adaptive and intelligent data
Gionis, A. (Principal investigator), Ordozgoiti Rubio, B. (Project Member), Zhang, G. (Project Member) & Muniyappa, S. (Project Member)
01/01/2018 → 30/06/2022
Project: Academy of Finland: Other research funding