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Opinion Maximization in Social Trust Networks (IJCAI 2020)

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Opinion Maximization in Social Trust Networks

Matlab implementation of methods proposed in "Opinion Maximization in Social Trust Networks", Pinghua Xu, Wenbin Hu, Jia Wu and Weiwei Liu, IJCAI 2020.

Overview

  • input/ contains four example graphs Bitcoin-Alpha Bitcoin WikiElec WikiRfa;
  • SIOP.mlx is the implementation of SIOP method proposed in the paper;
  • SEOP.mlx is the implementation of SEOP method;
  • initOP.m is a Matlab function for initializing internal opinion, and it is called by SIOP.mlx and SEOP.mlx.

Requirements

The implementation is tested under Matlab R2019b. The other version of Matlab, which supports live script, is also optional.

Input

We investigated social trust network, which can be represented by a directed signed (un)weighted graph, in this work.

And a toy example is illustarted in the figure.

The code takes an input graph in .txt format. Every row indicates an edge between two nodes separated by a space or \t. The file does not contain a header. Nodes can be indexed starting with any positive number (excluding 0). Four example graphs (donwloaded from SNAP, but node ID is resorted) Bitcoin-Alpha Bitcoin WikiElec WikiRfa are included in the input/ directory. The structure of the input file is the following:

Source node Target node Weight
0 1 -1
1 3 3
1 2 4
2 4 -6

Instruction

Copy this project to your Matlab. Run SIOP.mlx to test SIOP method, or run SEOP.mlx to test SEOP method.

In the parameter section of the live scripts, you can change mode to determine how to initialize internal opinions. And there are four options:

  • mode='uniform' The internal opinions follow a uniform distribution;
  • mode='normal' The internal opinions follow a standard normal distribution;
  • mode=pow The absolute values of the internal opinions follow a power-law distribution, and each entry is negated with aprobability of 0.5.
  • mode=degree The internal opinion of a node positively correlates to that node’s column connectivity, and each entry is negated with aprobability of 0.5.

And you can change budget, which is the budget of intervening, to any positve real number for SIOP and to any positve integer for SEOP.

Cite

If you find this repository useful in your research, please cite our paper:

@misc{2006.10961,
  Author = {Pinghua Xu and Wenbin Hu and Jia Wu and Weiwei Liu},
  Title = {Opinion Maximization in Social Trust Networks},
  Year = {2020},
  Eprint = {arXiv:2006.10961},
}

Moreover, if you are interested in the topic of social trust network, you may want to know our another work "Social Trust Network Embedding" (ICDM 2019).

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  • MATLAB 100.0%