loading
Documents

Research.Publish.Connect.

Paper

Authors: Andreas Kanavos ; Georgios Drakopoulos and Athanasios Tsakalidis

Affiliation: University of Patras, Greece

ISBN: 978-989-758-246-2

Keyword(s): CNM Algorithm, Community Discovery, Graph Databases, Graph Mining, Graph Signal Processing, Louvain Algorithm, Newman-Girvan Algorithm, Neo4j, Regularization, Walktrap Algorithm.

Related Ontology Subjects/Areas/Topics: Internet Technology ; Web Information Systems and Technologies ; Web Services and Web Engineering

Abstract: Community discovery is central to social network analysis as it provides a natural way for decomposing a social graph to smaller ones based on the interactions among individuals. Communities do not need to be disjoint and often exhibit recursive structure. The latter has been established as a distinctive characteristic of large social graphs, indicating a modularity in the way humans build societies. This paper presents the implementation of four established community discovery algorithms in the form of Neo4j higher order analytics with the Twitter4j Java API and their application to two real Twitter graphs with diverse structural properties. In order to evaluate the results obtained from each algorithm a regularization-like metric, balancing the global and local graph self-similarity akin to the way it is done in signal processing, is proposed.

PDF ImageFull Text

Download
CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.80.4.76

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Kanavos, A.; Drakopoulos, G. and Tsakalidis, A. (2017). Graph Community Discovery Algorithms in Neo4j with a Regularization-based Evaluation Metric.In Proceedings of the 13th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST, ISBN 978-989-758-246-2, pages 403-410. DOI: 10.5220/0006382104030410

@conference{webist17,
author={Andreas Kanavos. and Georgios Drakopoulos. and Athanasios Tsakalidis.},
title={Graph Community Discovery Algorithms in Neo4j with a Regularization-based Evaluation Metric},
booktitle={Proceedings of the 13th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST,},
year={2017},
pages={403-410},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006382104030410},
isbn={978-989-758-246-2},
}

TY - CONF

JO - Proceedings of the 13th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST,
TI - Graph Community Discovery Algorithms in Neo4j with a Regularization-based Evaluation Metric
SN - 978-989-758-246-2
AU - Kanavos, A.
AU - Drakopoulos, G.
AU - Tsakalidis, A.
PY - 2017
SP - 403
EP - 410
DO - 10.5220/0006382104030410

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.