Metadata vs. Ground-truth: A Myth behind the Evolution of Community Detection Methods

Tanmoy Chakraborty, Zhe Cui, Noseong Park

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

3 Citations (Scopus)

Abstract

A community detection (CD) method is usually evaluated by what extent it is able to discover the 'ground-truth' community structure of a network. A certain 'node-centric metadata' is used to define the ground-truth partition. However, nodes in real networks often have multiple metadata types (e.g., occupation, location); each can potentially form a ground-truth partition. Our experiment with 10 CD methods on 5 datasets (having multiple metadata-based ground-truth partitions) show that the metadata-based evaluation is misleading because there is no single CD method that can outperform others by detecting all types of metadata-based partitions. We further show that the community structure obtained from the CD methods is usually topologically stronger than any metadata-based partitions. Finally, we suggest a new task-based evaluation framework for CD methods and show that a certain type of CD methods is useful for a certain type of task.

Original languageEnglish
Title of host publicationThe Web Conference 2018 - Companion of the World Wide Web Conference, WWW 2018
PublisherAssociation for Computing Machinery, Inc
Pages45-46
Number of pages2
ISBN (Electronic)9781450356404
DOIs
Publication statusPublished - 2018 Apr 23
Event27th International World Wide Web, WWW 2018 - Lyon, France
Duration: 2018 Apr 232018 Apr 27

Publication series

NameThe Web Conference 2018 - Companion of the World Wide Web Conference, WWW 2018

Conference

Conference27th International World Wide Web, WWW 2018
CountryFrance
CityLyon
Period18/4/2318/4/27

Bibliographical note

Funding Information:
ACKNOWLEDGMENTS The work was partially supported by the Ramanujan Fellowship, SERB-DST, Govt. of India. REFERENCES

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Software

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