Persistent Roles in Online Social Networks
Abstract
Users in online social networks often have very different structural positions which may be attributed to a latent factor: roles. In this paper, we analyze dynamic networks from two datasets (Facebook and Scratch) to find roles which define users’ structural positions. Each dynamic network is partitioned into snapshots and we independently find roles for each network snapshot. We present our role discovery methodology and investigate how roles differ between snapshots and datasets. Six persistent roles are found and we investigate user role membership, transitions between roles, and interaction preferences.
Cite
Text
Revelle et al. "Persistent Roles in Online Social Networks." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2016. doi:10.1007/978-3-319-46227-1_4Markdown
[Revelle et al. "Persistent Roles in Online Social Networks." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2016.](https://mlanthology.org/ecmlpkdd/2016/revelle2016ecmlpkdd-persistent/) doi:10.1007/978-3-319-46227-1_4BibTeX
@inproceedings{revelle2016ecmlpkdd-persistent,
title = {{Persistent Roles in Online Social Networks}},
author = {Revelle, Matt and Domeniconi, Carlotta and Johri, Aditya},
booktitle = {European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases},
year = {2016},
pages = {47-62},
doi = {10.1007/978-3-319-46227-1_4},
url = {https://mlanthology.org/ecmlpkdd/2016/revelle2016ecmlpkdd-persistent/}
}