Graph Theory: A Comprehensive Survey about Graph Theory Applications in Computer Science and Social Networks

Majeed, Abdul; Rauf, Ibtisam

doi:10.3390/inventions5010010

Cited by 84 publications

(42 citation statements)

References 132 publications

(131 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Graphs are important elements of modern social network analysis [25]. Much research was done to identify efficient ways of checking graph morphism.…”

Section: Discussionmentioning

confidence: 99%

Graph Analysis Using Fast Fourier Transform Applied on Grayscale Bitmap Images

Baszuro¹,

Swacha

2021

Information

View full text Add to dashboard Cite

There is spiking interest in graph analysis, mainly sparked by social network analysis done for various purposes. With social network graphs often achieving very large size, there is a need for capable tools to perform such an analysis. In this article, we contribute to this area by presenting an original approach to calculating various graph morphisms, designed with overall performance and scalability as the primary concern. The proposed method generates a list of candidates for further analysis by first decomposing a complex network into a set of sub-graphs, transforming sub-graphs into intermediary structures, which are then used to generate grey-scaled bitmap images, and, eventually, performing image comparison using Fast Fourier Transform. The paper discusses the proof-of-concept implementation of the method and provides experimental results achieved on sub-graphs in different sizes randomly chosen from a reference dataset. Planned future developments and key considered areas of application are also described.

show abstract

“…Graphs are important elements of modern social network analysis [25]. Much research was done to identify efficient ways of checking graph morphism.…”

Section: Discussionmentioning

confidence: 99%

Graph Analysis Using Fast Fourier Transform Applied on Grayscale Bitmap Images

Baszuro¹,

Swacha

2021

Information

View full text Add to dashboard Cite

show abstract

“…However, the applications of those theories in different domains are less mentioned. For instance, the graph theory can be used to build recommendation engines in e-commerce or social networks [37]. In addition, the knowledge of matrix and associated manipulations can be applied to image presentation and processing.…”

Section: Interdisciplinary Learningmentioning

confidence: 99%

Enriching Undergraduate Mathematics Curriculum with Computer Science Courses

Kao

2021

Int. J. Eng. Ped.

View full text Add to dashboard Cite

Traditional mathematics curriculum faces several issues nowadays. The gap between course materials and students’ real-life mathematical experiences, the scattering of knowledge in different courses, and the lack of mathematics applications to other subjects all hinder the learning of students. The emerg-ing trends in data science, machine learning, and artificial intelligence also impel higher education to enrich and refine mathematics education. In order to better incubate students for future, the experience of enriching undergrad-uate mathematics curriculum with computer science courses is introduced in this study. The curriculum is designed and implemented for students who major in applied mathematics to better stimulate the learning, participation, exercise, and innovation. It provides students with comprehensive theoretical and practical knowledge for the challenges and industrial requirements now-adays. Evaluations, major findings, and lessons learned from three refined courses are discussed for more insight into the following deployment and re-finement of the curriculum.

show abstract

“…A graph is a mathematical approach which is the main approach in SNA. Graph theory is derived from a mathematical investigation carried out by Euler and provides a method for studying all types of networks [13], [14]. Informally, a graph is a group of objects called nodes connected by edges.…”

Section: Literature Review 21 Graphmentioning

confidence: 99%

Network analysis of Youtube videos based on keyword search with graph centrality approach

Negara

Andryani

Amanda

2021

IJEECS

View full text Add to dashboard Cite

<p>Youtube is a social media that has billions of users, with this can be used as a promotional media, trends, business, and so forth. This study aims to analyze the correlation between Youtube videos by utilizing hashtags on video using graph theory. Data collection in this study uses scraping techniques taken from the Youtube website in the form of links, titles, keywords, and hashtags. The method used in this research is Social Network Analysis, the measurements used in this study are degree centrality and betweenness centrality. The results of this study indicate that the most popular hashtags with the keyword search for "viruses" are #KidflixPT, #Portugues, and #Mondo with degree centrality values equal to 0.071875. and the correlation between the most closely related videos about #Coronavirus with a value of betweenness centrality of 0.082626.</p>

show abstract

Graph Theory: A Comprehensive Survey about Graph Theory Applications in Computer Science and Social Networks

Cited by 84 publications

References 132 publications

Graph Analysis Using Fast Fourier Transform Applied on Grayscale Bitmap Images

Graph Analysis Using Fast Fourier Transform Applied on Grayscale Bitmap Images

Enriching Undergraduate Mathematics Curriculum with Computer Science Courses

Network analysis of Youtube videos based on keyword search with graph centrality approach

Contact Info

Product

Resources

About