Official code and datasets of How Transitive Are Real-World Group Interactions? - Measurement and Reproduction

Publication

• Title: How Transitive Are Real-World Group Interactions? - Measurement and Reproduction.
• Authors: Sunwoo Kim, Fanchen Bu, Minyoung Choe, Jaemin Yoo, and Kijung Shin.
• Venue: KDD 2023 [to appear]

Description

• This is an official code and datasets for How Transitive Are Real-World Group Interactions? - Measurement and Reproduction.
• FastHyperTrans and THera are implemented with JAVA
• Experimental results (Tables, Figures) are implemented with Python

Dataset

Overview and Source

We used 12 real-world hypergraph datasets. Details and source of each datasets are as follows.

1. Email (Enron, EU) [1]
2. NDC (Substances, Classes) [1]
3. Contact (High, Primary) [1]
4. Co-Authorship (DBLP, MAG-Geology, -History) [1]
5. Q&A (Ubuntu, Server, Math) [1, 2]

Since file sizes are greater than 25MB, we uploaded datasets in the following URL: https://www.dropbox.com/sh/in4x4vly764su8g/AAAZZ3J81jY2dc7YaxmCmJVaa?dl=0

Example

Each line of data indicates each hyperedge. Comma-seperated numbers are all node. Shape of each dataset is as follows:

0,1,2
1,3,4,5

where the first hyperedge consists of node index 0, 1, and 2, and the second hyperedge consists of node index 1, 3, 4, and 5.

We also provide generated hypergraphs by THera

Implementation

Codes are in src folder.

Overview

In this repo, there are three main codes: HyperTrans.jar, THera.jar, and Observation.py.

• /src/HyperTrans.jar: It receives any hypergraph dataset (same format as explained in dataset section), and computes hyperwedge with resulting transitivity by using HyperTrans and Fast-HyperTrans (see Section 3 of the main paper).
• /src/THera.jar: It receives real-world hypergraph dataset (same format as explained in dataset section), and generates a synthetic hypergraph by using THera (see Section 5 of the main paper).
• /src/Observation.py: It receives hypergraph dataset and resulting transitivity, and reproduces observations of hypergraphs (see Section 4 and 5 of the main paper).

Execution

HyperTrans.jar

Input

java -jar HyperTrans.jar [data path]

Note that data path is a path of input hypergraph.

Output

It returns dataname_output.txt file with hyperwedge and the corresponding transitivity. For example, with "email_enron_HE.txt" file, it creates "email_enron_HE_output.txt", which looks like

0,3,0.1525
1,5,0.5815

This implies

• hyperedge index 0 and 3 is hyperwedge and the corresponding hyperwedge transitivity is 0.1525
• hyperedge index 1 and 5 is hyperwedge and the corresponding hyperwedge transitivity is 0.5815

THera.jar

Input

java -jar HyperTrans.jar [data path] [C] [p] [alpha]

• Data path is a path to the original real-world hypergraph.
• C is a size of each community.
• p is a ratio of intra-community hyperedge.
• alpha is a base of hierarchical hyperedge generation scalar.

Output

It returns dataname_output.txt file with hyperwedge and the corresponding transitivity. For example, with "email_enron_HE.txt" file and C = 10, p = 0.6, alpha = 3.0, it creates "email_enron_HE_10_0.6_3.0_THera.txt", which looks like

0,1,2
0,2,3,4

This implies

• First hyperedge consist of node index 0, 1, and 2.
• Second hyperedge consist of node index 0, 2, 3, and 4. Note that this format is identical to the original hypergraph

Observation.py

Input

python [-obs: observation type] [-obs_detail: type of hypergraph] [-real_data_name: file path to real-world hypergraph] [-gen_data_name: file path to generated hypergraph] [-real_result_name: file path to the real-world transitivity results] [-gen_result_name: file path to the generated transitivity results]

• obs indicates whether observation 1, 2, 3, or 4.
• obs_detail indicates whether to check observation of real-world or generated .
• real_data_name indicates file path to the real-world hypergraph.
• gen_data_name indicates file path to the generated hypergraph.
• real_result_name indicates file path to the resulting hypergraph transitivity of real-world hypergraph.
• gen_result_name indicates file path to the resulting hypergraph transitivity of generated hypergraph.

Output

It reproduces result of real-world hypergraphs.

Reference

[1]: Austin R. Benson, Rediet Abebe, Michael T. Schaub, Ali Jadbabaie, and Jon Kleinberg. Simplicial closure and higher-order link prediction. Proceedings of the National Academy of Sciences (PNAS), 2018.

[2]: Sunwoo Kim, Minyoung Choe, Jaemin Yoo, and Kijung Shin. Reciprocity in Directed Hypergraphs: Measures, Findings, and Generators. IEEE International Conference On Data Mining (ICDM), 2022.