In this paper, we start by pointing out the limitations on the validation of existing signed network embedding (NE) methods. To address the limitations, we design the two research questions: (1) are signed NE methods consistently more effective in various types of tasks than unsigned NE methods? (2) in signed NE methods, does the utilization of negative links help provide higher accuracy in various tasks? To answer the questions, we present our evaluation framework consisting of three components: (1) five signed network datasets; (2) six signed and two unsigned NE methods; (3) five types of tasks. Through extensive experiments on our evaluation framework, we demonstrate that additional utilization of negative links really helps only in some tasks related to negative links but not in tasks related to positive links.

• Are Negative Links Really Beneficial to Network Embedding? In-Depth Analysis and Interesting Results

Yeon-Chang Lee, Nayoun Seo, and Sang-Wook Kim (*equal contribution)

ACM Int’l Conf. on Information and Knowledge Management (CIKM), Oct. 19-23, 2020

We encourage you to cite our paper if you have used the code in your work. You can use the following BibTex citation:

@inproceedings{DBLP:conf/cikm/LeeSK20,

author = {Yeon{-}Chang Lee and

Nayoun Seo and

Sang{-}Wook Kim},

title = {Are Negative Links Really Beneficial to Network Embedding?: In-Depth

Analysis and Interesting Results},

booktitle = {{CIKM} '20: The 29th {ACM} International Conference on Information

and Knowledge Management, Virtual Event, Ireland, October 19-23, 2020},

pages = {2113--2116},

year = {2020}

}