SCHOLAT Research Dataset for TaCD
TaCD: Team-Aware Community Detection Based on Multi-View Modularity

Introduction

SCHOLAT is an academic social networking service website designed to promote exchanges and cooperation between researchers. In this paper, we propose a novel community detection algorithm termed TaCD. Another contribution of this paper is that a new SCHOLAT dataset consisting of several social networks is collected and made publicly available as a testing dataset.

SCHOLAT Research Dataset for TaCD

We will update the detail when the paper is published.
(1) user_real_community
(2) link_friendship
(3) matrix_common_team_count
(4) matrix_interact_times
(5) matrix_friendship
(6) matrix_jaccard

Networks in the Dataset

Networks Nodes Edges Communities
Net-3000 3,000 689,480 157
Net-4000 4000 992,387 162
Net-5000 5,000 1,385,964 178
Net-6000 6,000 2,462,527 178
Net-7000 7,000 3,107,667 186
Net-8000 8,000 4,061,459 197
Net-9000 9,000 5,009,882 208
Net-10000 10,000 5,713,566 218

Download and Cite

If you use this Dataset in your work, please cite this publication. You can download the Dataset from here: http://www.scholat.com/research/tacd/datasets_TaCD.zip
You can find the password in the paper (tips: the password without Quotation Marks).

Related Codes

http://www.scholat.com/research/tacd/code_TaCD.zip
You can find the password in the paper (tips: the password without Quotation Marks).

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