163 citations · 724 across the 59 of their papers we have counts for
16 papers · 1 filter
DANI: Fast Diffusion Aware Network Inference with Preserving Topological Structure Property
Maryam Ramezani, Aryan Ahadinia, Erfan Farhadi +1
The fast growth of social networks and their data access limitations in recent years has led to increasing difficulty in obtaining the complete topology of these networks. However,…
Network-based Control of Epidemic via Flattening the Infection Curve: High-Clustered vs. Low-Clustered Social Networks
Mohammadreza Doostmohammadian, Hamid R. Rabiee
Recent studies in network science and control have shown a meaningful relationship between the epidemic processes (e.g., COVID-19 spread) and some network properties. This paper st…
Joint Inference of Diffusion and Structure in Partially Observed Social Networks Using Coupled Matrix Factorization
Maryam Ramezani, Aryan Ahadinia, Amirmohammad Ziaei +1
Access to complete data in large-scale networks is often infeasible. Therefore, the problem of missing data is a crucial and unavoidable issue in the analysis and modeling of real-…
News Labeling as Early as Possible: Real or Fake?
Maryam Ramezani, Mina Rafiei, Soroush Omranpour +1
Making disguise between real and fake news propagation through online social networks is an important issue in many applications. The time gap between the news release time and det…
Steering Social Activity: A Stochastic Optimal Control Point Of View
Ali Zarezade, Abir De, Utkarsh Upadhyay +2
User engagement in online social networking depends critically on the level of social activity in the corresponding platform--the number of online actions, such as posts, shares or…
Continuous-Time Relationship Prediction in Dynamic Heterogeneous Information Networks
Sina Sajadmanesh, Sogol Bazargani, Jiawei Zhang +1
Online social networks, World Wide Web, media and technological networks, and other types of so-called information networks are ubiquitous nowadays. These information networks are…
DANI: A Fast Diffusion Aware Network Inference Algorithm
Maryam Ramezani, Hamid R. Rabiee, Maryam Tahani +1
The fast growth of social networks and their privacy requirements in recent years, has lead to increasing difficulty in obtaining complete topology of these networks. However, diff…
Recurrent Poisson Factorization for Temporal Recommendation
Seyed Abbas Hosseini, Keivan Alizadeh, Ali Khodadadi +4
Poisson factorization is a probabilistic model of users and items for recommendation systems, where the so-called implicit consumer data is modeled by a factorized Poisson distribu…
Continuous-Time User Modeling in the Presence of Badges: A Probabilistic Approach
Ali Khodadadi, Seyed Abbas Hosseini, Erfan Tavakoli +1
User modeling plays an important role in delivering customized web services to the users and improving their engagement. However, most user models in the literature do not explicit…
Spatio-Temporal Modeling of Users' Check-ins in Location-Based Social Networks
Ali Zarezade, Sina Jafarzadeh, Hamid R. Rabiee
Social networks are getting closer to our real physical world. People share the exact location and time of their check-ins and are influenced by their friends. Modeling the spatio-…
Predicting Anchor Links between Heterogeneous Social Networks
Sina Sajadmanesh, Hamid R. Rabiee, Ali Khodadadi
People usually get involved in multiple social networks to enjoy new services or to fulfill their needs. Many new social networks try to attract users of other existing networks to…
Bayesian Overlapping Community Detection in Dynamic Networks
Mahsa Ghorbani, Hamid R. Rabiee, Ali Khodadadi
Detecting community structures in social networks has gained considerable attention in recent years. However, lack of prior knowledge about the number of communities, and their ove…
Correlated Cascades: Compete or Cooperate
Ali Zarezade, Ali Khodadadi, Mehrdad Farajtabar +2
In real world social networks, there are multiple cascades which are rarely independent. They usually compete or cooperate with each other. Motivated by the reinforcement theory in…
Diffusion-Aware Sampling and Estimation in Information Diffusion Networks
Motahareh Eslami Mehdiabadi, Hamid R. Rabiee, Mostafa Salehi
Partially-observed data collected by sampling methods is often being studied to obtain the characteristics of information diffusion networks. However, these methods usually do not…
Sampling from Diffusion Networks
Motahareh Eslami Mehdiabadi, Hamid R. Rabiee, Mostafa Salehi
The diffusion phenomenon has a remarkable impact on Online Social Networks (OSNs). Gathering diffusion data over these large networks encounters many challenges which can be allevi…
A Measurement Framework for Directed Networks
Mostafa Salehi, Hamid R. Rabiee
Partially-observed network data collected by link-tracing based sampling methods is often being studied to obtain the characteristics of a large complex network. However, little at…