Complex and Social Networks

Inferring structure from information diffusion, modelling cascades, and predicting what spreads.

The structure of a social network is rarely available, but the traces left by information moving through it usually are. That asymmetry drives a family of problems the lab has worked on for years: inferring the underlying network from observed cascades while preserving its real topological properties, recovering what was missing when the data is only partially observed, detecting communities from diffusion rather than links, and predicting early which cascades will grow.

This line of work produced DANI and DiffStru, and continues through survival-analysis models for early popularity prediction.

Publications in this area

DANI: Fast Diffusion Aware Network Inference with Preserving Topological Structure Property

Maryam Ramezani, Aryan Ahadinia, Erfan Farhadi, Hamid R. Rabiee

Scientific Reports, 2024Cited by 5

DOI Publisher arXiv Code

BibTeX

@article{ramezani2024dani,
  title = {{DANI: Fast Diffusion Aware Network Inference with Preserving Topological Structure Property}},
  author = {Maryam Ramezani and Aryan Ahadinia and Erfan Farhadi and Hamid R. Rabiee},
  journal = {Scientific Reports},
  year = {2024},
  doi = {10.1038/s41598-024-82286-x},
  eprint = {2310.01696},
  archivePrefix = {arXiv},
  url = {https://www.nature.com/articles/s41598-024-82286-x}
}

Detecting Popular Social Events through Limited Observation with Deep Survival Analysis

Maryam Ramezani, Hossein Goli, AmirMohammad Izadi, Hamid R. Rabiee

arXiv preprint, 2024PreprintCited by 1

arXiv

BibTeX

@misc{ramezani2024detecting,
  title = {{Detecting Popular Social Events through Limited Observation with Deep Survival Analysis}},
  author = {Maryam Ramezani and Hossein Goli and AmirMohammad Izadi and Hamid R. Rabiee},
  year = {2024},
  eprint = {2410.01320},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2410.01320}
}

Joint Inference of Diffusion and Structure in Partially Observed Social Networks Using Coupled Matrix Factorization

Maryam Ramezani, Aryan Ahadinia, Amirmohammad Ziaei Bideh, Hamid R. Rabiee

ACM Transactions on Knowledge Discovery from Data (ACM TKDD), 2023

arXiv

BibTeX

@article{ramezani2023joint,
  title = {{Joint Inference of Diffusion and Structure in Partially Observed Social Networks Using Coupled Matrix Factorization}},
  author = {Maryam Ramezani and Aryan Ahadinia and Amirmohammad Ziaei Bideh and Hamid R. Rabiee},
  journal = {ACM Transactions on Knowledge Discovery from Data},
  year = {2023},
  eprint = {2010.01400},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2010.01400}
}

Community Detection Using Diffusion Information

Maryam Ramezani, Ali Khodadadi, Hamid R. Rabiee

ACM Transactions on Knowledge Discovery from Data (ACM TKDD), 2018

BibTeX

@article{ramezani2018community,
  title = {{Community Detection Using Diffusion Information}},
  author = {Maryam Ramezani and Ali Khodadadi and Hamid R. Rabiee},
  journal = {ACM Transactions on Knowledge Discovery from Data},
  year = {2018}
}

Inferring Dynamic Diffusion Networks in Online Media

Maryam Tahani, Ali Mohammad Afshin Hemmatyar, Hamid R. Rabiee, Maryam Ramezani

ACM Transactions on Knowledge Discovery from Data (ACM TKDD), 2016

BibTeX

@article{tahani2016inferring,
  title = {{Inferring Dynamic Diffusion Networks in Online Media}},
  author = {Maryam Tahani and Ali Mohammad Afshin Hemmatyar and Hamid R. Rabiee and Maryam Ramezani},
  journal = {ACM Transactions on Knowledge Discovery from Data},
  year = {2016}
}

Software and data

DANI Software