A Guide for Choosing Community Detection Algorithms in Social Network Studies: The Question Alignment Approach

Smith, Natalie; Zivich, Paul N; Frerichs, Leah; Moody, James; Aiello, Allison E.

doi:10.1016/j.amepre.2020.04.015

Cited by 62 publications

(40 citation statements)

References 39 publications

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“…Walktrap proposed by Pons and Latapy 17 is a robust algorithm in graph theory used to identify communities/clusters in the networks via random walks regardless of network size 16 , 56 . Moreover, random walks have been studied for many decades in networks with a variety of structures to extract information about important nodes or dense groups of nodes in a network 57 .…”

Section: Methodsmentioning

confidence: 99%

“…The algorithm eventually returns a hierarchical structure of communities called a dendrogram and the algorithm stops when a partition with maximum modularity is obtained. Walktrap is preferred when researchers want flexibility in choosing community structures or the ability to explore several different cut points for communities since Walktrap returns a dendrogram 56 .…”

Section: Methodsmentioning

confidence: 99%

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Network analysis to identify symptoms clusters and temporal interconnections in oncology patients

Kalantari

Kouchaki

Miaskowski

et al. 2022

Sci Rep

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Oncology patients experience numerous co-occurring symptoms during their treatment. The identification of sentinel/core symptoms is a vital prerequisite for therapeutic interventions. In this study, using Network Analysis, we investigated the inter-relationships among 38 common symptoms over time (i.e., a total of six time points over two cycles of chemotherapy) in 987 oncology patients with four different types of cancer (i.e., breast, gastrointestinal, gynaecological, and lung). In addition, we evaluated the associations between and among symptoms and symptoms clusters and examined the strength of these interactions over time. Eight unique symptom clusters were identified within the networks. Findings from this research suggest that changes occur in the relationships and interconnections between and among co-occurring symptoms and symptoms clusters that depend on the time point in the chemotherapy cycle and the type of cancer. The evaluation of the centrality measures provides new insights into the relative importance of individual symptoms within various networks that can be considered as potential targets for symptom management interventions.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Network analysis to identify symptoms clusters and temporal interconnections in oncology patients

Kalantari

Kouchaki

Miaskowski

et al. 2022

Sci Rep

View full text Add to dashboard Cite

show abstract

“…People from psychology, social science and anthropology defined self-esteem in different views like competence or ability to handle achievement in meaningful way, feeling or attitude of self-worth, and overall opinion about ourselves (Mruk, 2013). People with high self-esteem have high positive perception about themselves, but people from low self-esteem have poor evaluation and negative feelings with their own (Smith et al, 2020). Self-esteem starts to develop itself as early in childhood periods, then slowly increases over lifespan (Robins & Trzesniewski, 2005).…”

Section: Self-esteemmentioning

confidence: 99%

Self-esteem and mental health among obese and non-obese people

Adam

Wani²

2022

ijhs

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Obesity and mental health problems are becoming as major health related issues in 21st century due to improper and unhealthy lifestyles. In other hand the term self-esteem is derived word “esteem” (in Latin aestimare means to value), it denotes how we value ourselves. It plays important role in body mass index and mental health. Aim and objectives of present study to explore various research input in obesity research through multiple linear analysis and non-parametric test such as Mann-Whitney test and Kruskal Wallis test among 560 obese and non-obese participants from Cuddalore district in Tamil Nadu, India using Rosenberg’s Self-esteem Scale (RSES) and the Mental Health Inventory-38 (MHI-38) along with body mass index (BMI) measurement. The results stated self-esteem have significant mean difference at the level of .001 with respect to age, and at level of .000 with respect to body mass index, whereas gender have showed statistical insignificant mean difference at .181. Whereas mental health have significant mean difference only in body mass index at the level of .000 and showed no significant mean difference in age and gender with p-value .504 and .421 respectively.

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“…(3) Label Propagation (LP) proposed in [37], the main notion of the algorithm is to assign each vertex in a graph into a specific community, to which most of its adjacent vertices belong. For more details, see [38].…”

Section: Community Structure Preservationmentioning

confidence: 99%

An Improved K-anonymization Approach for Preserving Graph Structural Properties

Hanafy¹,

Barakat²,

Rezk³

2021

IJACSA

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Privacy risks are an important issue to consider during the release of network data to protect personal information from potential attacks. Network data anonymization is a successful procedure used by researchers to prevent an adversary from revealing the user's identity. Such an attack is called a re-identification attack. However, this is a tricky task where the primary graph structure should be maintained as much as feasible within the anonymization process. Most existing solutions used edge-perturbation methods directly without any concern regarding the structural information of the graph. While that preserving graph structure during the anonymization process requires keeping the most important knowledge edges in the graph without any modifications. This paper introduces a high utility K-degree anonymization method that could utilize edge betweenness centrality ( ) as a measure to map the edges that have a central role in the graph. Experimental results showed that preserving these edges during the modification process will lead the anonymization algorithm to better preservation for the most important structural properties of the graph. This method also proved its efficiency for preserving community structure as a trade-off between graph utility and privacy.

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A Guide for Choosing Community Detection Algorithms in Social Network Studies: The Question Alignment Approach

Cited by 62 publications

References 39 publications

Network analysis to identify symptoms clusters and temporal interconnections in oncology patients

Network analysis to identify symptoms clusters and temporal interconnections in oncology patients

Self-esteem and mental health among obese and non-obese people

An Improved K-anonymization Approach for Preserving Graph Structural Properties

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