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 Adapt-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 Adapt-TaCD
(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-1000 | 1,000 | 164,024 | 123 |
| Net-2000 | 2000 | 261,120 | 149 |
| Net-3000 | 3000 | 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/adapt_tacd/datasets_adapt-tacd.zipYou can find the password in the paper.
Related Codes
http://www.scholat.com/research/adapt-tacd/code_adapt-tacd.zipYou can find the password in the paper.