Learning heterogeneous subgraph representations for team discovery
The team discovery task is concerned with finding a group of experts from a collaboration
network who would collectively cover a desirable set of skills. Most prior work for team …
network who would collectively cover a desirable set of skills. Most prior work for team …
ACSIMCD: A 2-phase framework for detecting meaningful communities in dynamic social networks
Detecting and analyzing community structure is a challenging topic in dynamic social
network analysis. Although the number of methods in this area is on the rise, there are only a …
network analysis. Although the number of methods in this area is on the rise, there are only a …
Community detection over feature-rich information networks: An eHealth case study
In this paper, we present a novel graph data model to analyze eating habits and physical
activities of a large number of persons, aiming at automatically detect groups of users …
activities of a large number of persons, aiming at automatically detect groups of users …
Effective influence estimation in twitter using temporal, profile, structural and interaction characteristics
Influence diffusion is extensively studied in social networks for product or service promotion
and viral-marketing applications. This paper proposes two models for social influence …
and viral-marketing applications. This paper proposes two models for social influence …
Detection of sociolinguistic features in digital social networks for the detection of communities
E Puertas, LG Moreno-Sandoval, J Redondo… - Cognitive …, 2021 - Springer
The emergence of digital social networks has transformed society, social groups, and
institutions in terms of the communication and expression of their opinions. Determining how …
institutions in terms of the communication and expression of their opinions. Determining how …
Learning node representation via Motif Coarsening
R Yan, P Bao, H Shen, X Li - Knowledge-Based Systems, 2023 - Elsevier
Motifs, as fundamental units of the graph, play a significant role in modeling complex
systems in a variety of domains, including social networks, as well as biology and …
systems in a variety of domains, including social networks, as well as biology and …
Community detection in error-prone environments based on particle cooperation and competition with distance dynamics
B Wang, Y Gu, D Zheng - Physica A: Statistical Mechanics and its …, 2022 - Elsevier
Community detection has attracted a lot of attention in recent decades for understanding
structures and functions of complex networks. A plethora of exhaustive studies have proved …
structures and functions of complex networks. A plethora of exhaustive studies have proved …
Enhancing decision-making support by mining social media data with social network analysis
This paper explores the use of social network analysis (SNA) on airlines' online social
networks (OSNs) to extract valuable information for decision support, by analyzing …
networks (OSNs) to extract valuable information for decision support, by analyzing …
Evaluation of herd behavior caused by population-scale concept drift in collaborative filtering
Concept drift in stream data has been well studied in machine learning applications. In the
field of recommender systems, this issue is also widely observed, as known as temporal …
field of recommender systems, this issue is also widely observed, as known as temporal …
Predicting users' future interests on social networks: A reference framework
Predicting users' interests on social networks is gaining attention due to its potential to cater
customized information and services to the end users. Although previous works have …
customized information and services to the end users. Although previous works have …