Contribution of graph theory to the understanding of social dynamics

Authors

DOI:

https://doi.org/10.47909/awari.51

Keywords:

network analysis, centrality, social cohesion, information diffusion, social dynamics, human interaction, social networks, graph theory

Abstract

This review article examines how graph theory has contributed significantly to understanding social dynamics by discussing its applicability to social network analysis. A predominantly qualitative study was carried out, with a scoping review design aimed at understanding how this set of tools facilitates studying human interactions and the structure of social groups. The main results highlighted key concepts such as centrality, clusters, connectivity, and network resilience, as well as their applications to analyzing social phenomena such as information diffusion, opinion formation, disease spread, and social cohesion. In addition, the methodological challenges and limitations of graph theory were examined, to propose future directions for interdisciplinary research that delve into the interaction between mathematics and social sciences, especially Social Psychology applied to collective behavior and the social network analysis.

Downloads

Download data is not yet available.

References

Acevedo Duque, Á., Álvarez-Herranz, A., & Marinao-Artigas, E. (2023). Scientometrics study of country branding and its contribution to sustainable development in nations. Data and Metadata, 2, 163. https://doi.org/10.56294/dm2023163

Alomia-Padilla, B., Alvarez-Guzman, C., Alvarez-Guzman, A., Morales-García, M., Sairitupa-Sanchez, L. Z., Morales-García, S. B., Álvarez-Manrique, V., Paredes-Saavedra, M., & Morales-García, W. C. (2023). Sociodemographic factors, work motivation, emotional intelligence, quality of work life, and their association with work performance in peruvian health workers. Salud, Ciencia y Tecnología - Serie de Conferencias, 2, 565. https://doi.org/10.56294/sctconf2023565

Álvarez Contreras, D. E., Díaz Pérez, C. M., & Herazo Morales, R. (2023). Factores académicos asociados al proceso de investigación formativa en las instituciones educativas del sector oficial de Sincelejo, Sucre. Región Científica, 2(1), 202319. https://doi.org/10.58763/rc202319

Anugerah, A. R., Muttaqin, P. S., & Trinarningsih, W. (2022). Social network analysis in business and management research: A bibliometric analysis of the research trend and performance from 2001 to 2020. Heliyon, 8(4), e09270. https://doi.org/10.1016/j.heliyon.2022.e09270

Araque Geney, E. A. (2023). Una mirada a la realidad económica y educativa de la mujer indígena Zenú: reflexiones desde el Cabildo Menor el Campo Mirella. Región Científica, 2(2), 202366. https://doi.org/10.58763/rc202366

Bacsu, J.-D. R., O’Connell, M. E., Webster, C., Poole, L., Wighton, M. B., & Sivananthan, S. (2021). A scoping review of COVID-19 experiences of people living with dementia. Canadian Journal of Public Health, 112, 400–411. https://doi.org/10.17269/s41997-021-00500-z

Bernardini, R., & Robledo, M. (2023). Clínica feminista en red-es. Salud, Ciencia y Tecnología - Serie de Conferencias, 2(1), 122. https://doi.org/10.56294/sctconf2023122

Blanco-Gonzalez-Tejero, C., & Cano-Marin, E. (2023). Empowerment of women's entrepreneurship in family business through Twitter. Journal of Family Business Management, 13(3), 607-625. https://doi.org/10.1108/JFBM-04-2022-0050

Brusco, M., Davis-Stober, C. P., & Steinley, D. (2021). Ising formulations of some graph-theoretic problems in psychological research: Models and methods. Journal of Mathematical Psychology, 102, 102536. https://doi.org/10.1016/j.jmp.2021.102536

Camacho, D., Panizo-LLedot, Á., Bello-Orgaz, G., Gonzalez-Pardo, A., & Cambria, E. (2020). The four dimensions of social network analysis: An overview of research methods, applications, and software tools. Information Fusion, 63, 88-120. https://doi.org/10.1016/j.inffus.2020.05.009

Campos Sánchez, C., Guillén León, L., Acosta Yanes, R., & Gil Oloriz, M. (2022). Metaverse: the future of medicine in a virtual world. Metaverse Basic and Applied Research, 1. https://doi.org/10.56294/mr20224

Canova Barrios, C. J., Macarena Francisco, S., & Hereñú, M. P. (2022). Workplace Violence in the Health Sector: Focus on the Argentinean context. Community and Interculturality in Dialogue, 2, 31. https://doi.org/10.56294/cid202231

Copping, A., Kuchai, N., Hattam, L., Paszkiewicz, N., Albadra, D., Shepherd, P., Burat, E. S., & Coley, D. (2022). Understanding material and supplier networks in the construction of disaster-relief shelters: the feasibility of using social network analysis as a decision-making tool. Journal of Humanitarian Logistics and Supply Chain Management, 12(1), 78-105. https://doi.org/0.1108/JHLSCM-01-2020-0007

Daud, N. N., Ab Hamid, S. H., Saadoon, M., Sahran, F., & Anuar, N. B. (2020). Applications of link prediction in social networks: A review. Journal of Network and Computer Applications, 166, 102716. https://doi.org/10.1016/j.jnca.2020.102716

Gao, Y. (2020). Constructing the social network prediction model based on data mining and link prediction analysis. Library Hi Tech, 38(2), 320-333. https://doi.org/10.1108/LHT-11-2018-0179

Gavilan, N. E., Paquiyauri, Y. Y., Meneses-Claudio, B., Lopez-Curasma, A., & Romero-Sandoval, J. (2023). Pedagogical Management and Managerial Leadership in the Secondary Educational Institutions of Network 6, UGEL 06, Ate, 2020. Data and Metadata, 2, 172. https://doi.org/10.56294/dm2023172

Gómez Cano, C. A., Sánchez Castillo, V., & Clavijo Gallego, T. A. (2023). Unveiling the Thematic Landscape of Generative Pre-trained Transformer (GPT) Through Bibliometric Analysis. Metaverse Basic and Applied Research, 2. https://doi.org/10.56294/mr202333

Gonzales Tito, Y. M., Quintanilla López, L. N., & Pérez Gamboa, A. J. (2023). Metaverse and education: a complex space for the next educational revolution. Metaverse Basic and Applied Research, 2, 56-56. https://doi.org/10.56294/mr202356

Guatemala Mariano, A., & Martínez Prats, G. (2023). Technological capabilities in emerging social enterprises: A pathway to social impact. Región Científica, 2023111. https://doi.org/10.58763/rc2023111

Han, S. H., Yoon, S. W., & Chae, C. (2020). Building social capital and learning relationships through knowledge sharing: a social network approach of management students’ cases. Journal of Knowledge Management, 24(4), 921-939. https://doi.org/10.1108/JKM-11-2019-0641

Han, Y., Caldwell, N. D., & Ghadge, A. (2020). Social network analysis in operations and supply chain management: a review and revised research agenda. International Journal of Operations & Production Management, 40(7/8), 1153-1176. https://doi.org/10.1108/IJOPM-06-2019-0500

Hernández Tique, D., Puentes Ordoñez, J. J., & Gómez Cano, C. A. (2022). How do technology equipment companies implement new billing strategies? Metaverse Basic and Applied Research, 15. https://doi.org/10.56294/mr202215

Hewa Welege, N. M., Pan, W., & Kumaraswamy, M. (2021). Social network analysis applications in sustainable construction and built environment management: a review. Built Environment Project and Asset Management, 11(4), 511-528. https://doi.org/10.1108/BEPAM-03-2020-0047

Hung, L., Leitch, S., Hung, R., & Phinney, A. (2020). Creating dementia-friendly and inclusive communities for social inclusion: a scoping review protocol. BMJ Open, 10(6), e035028. https://doi.org/10.1136/bmjopen-2019-035028

Ibrahimi, G., Merioumi, W., & Benchekroun, B. (2023). Fostering innovation through collective intelligence: A literature review. Data and Metadata, 2, 149. https://doi.org/10.56294/dm2023149

Jiang, B., Zhao, Y., Dong, J., & Hu, J. (2024). Analysis of the influence of trust in opposing opinions: An inclusiveness-degree based Signed Deffuant–Weisbush model. Information Fusion, 104, 102173. https://doi.org/10.1016/j.inffus.2023.102173

Khalil Ibraheem, I. (2022). Enhancing Intrusion Detection Systems Using Ensemble Machine Learning Techniques. Data and Metadata, 1, 33. https://doi.org/10.56294/dm202271

Khalil, M., Prinsloo, P., & Slade, S. (2023). The use and application of learning theory in learning analytics: a scoping review. Journal of Computing in Higher Education, 35, 573–594. https://doi.org/10.1007/s12528-022-09340-3

Kosvyra, A., Ntzioni, E., & Chouvarda, I. (2021). Network analysis with biological data of cancer patients: A scoping review. Journal of Biomedical Informatics, 120, 103873. https://doi.org/10.1016/j.jbi.2021.103873

Kumar, S., Mallik, A., Khetarpal, A., & Panda, B. S. (2022). Influence maximization in social networks using graph embedding and graph neural network. Information Sciences, 607, 1617-1636. https://doi.org/10.1016/j.ins.2022.06.075

Kurt, Y., & Kurt, M. (2020). Social network analysis in international business research: An assessment of the current state of play and future research directions. International Business Review, 29(2), 101633. https://doi.org/10.1016/j.ibusrev.2019.101633

Kyrimi, E., McLachlan, S., Dube, K., Neves, M. R., Fahmi, A., & Fenton, N. (2021). A comprehensive scoping review of Bayesian networks in healthcare: Past, present and future. Artificial Intelligence in Medicine, 117, 102108. https://doi.org/10.1016/j.artmed.2021.102108

Ledesma, F., & Malave González, B. E. (2022). Patrones de comunicación científica sobre E-commerce: un estudio bibliométrico en la base de datos Scopus. Región Científica, 1(1). https://doi.org/10.58763/rc202214

Lepez, C. O., & Simeoni, I. A. (2023). Pedagogical experience with Public Health campaigns from the design of socio-educational projects with insertion in the local territory. Community and Interculturality in Dialogue, 3, 74. https://doi.org/10.56294/cid202374

Li, Y., Chu, T., Che, K., Dong, F., Shi, Y., Ma, H., Zhao, F., Mao, N., & Xie, H. (2021). Altered gray matter structural covariance networks in postpartum depression: a graph theoretical analysis. Journal of Affective Disorders, 293, 159-167. https://doi.org/10.1016/j.jad.2021.05.018

Linares Giraldo, M., Rozo Carvajal, K. J., & Sáenz López, J. T. (2023). Impacto de la pandemia en el comportamiento del comercio B2C en Colombia. Región Científica, 2(1), 202320. https://doi.org/10.58763/rc202320

López-Belmonte, J., Pozo-Sánchez, S., Moreno-Guerrero, A.-J., & Marín-Marín, J.-A. (2023). We’ve reached the GOAL. Teaching Methodology for Transforming Learning in the METAVERSE. A teaching innovation project. Metaverse Basic and Applied Research, 2. https://doi.org/10.56294/mr202330

Luo, W., Greene, A. S., & Constable, R. T. (2021). Within node connectivity changes, not simply edge changes, influence graph theory measures in functional connectivity studies of the brain. NeuroImage, 240, 118332. https://doi.org/10.1016/j.neuroimage.2021.118332

Mogrovejo Andrade, J. M. (2022). Estrategias resilientes y mecanismos de las organizaciones para mitigar los efectos ocasionados por la pandemia a nivel internacional. Región Científica, 1(1), 202211. https://doi.org/10.58763/rc202211

Molan, G., & Molan, M. (2021). Theoretical Model for Accident Prevention Based on Root Cause Analysis With Graph Theory. Safety and Health at Work, 12(1), 42-50. https://doi.org/10.1016/j.shaw.2020.09.004

Molinero, X., & Riquelme, F. (2021). Influence decision models: From cooperative game theory to social network analysis. Computer Science Review, 39, 100343. https://doi.org/10.1016/j.cosrev.2020.100343

Mora Pontiluis, D. J., Muñoz Estrada, E. S., & Mora Atencio, E. J. (2023). Aplicación del proyecto pedagógico de aula “Gestores de convivencia y paz” como estrategia para la formación de la cultura de la paz en los niños en el departamento de La Guajira. Región Científica, 2(1). https://doi.org/10.58763/rc202355

Ortiz-Leon, C., Yupanqui-Allcca, F., & Meneses-Claudio, B. (2023). Uso de la Inteligencia Artificial para la traducción de lenguajes de señas: Una revisión sistemática de literatura. Salud, Ciencia y Tecnología - Serie de Conferencias, 2, 446. https://doi.org/10.56294/sctconf2023446

Pérez Gamboa, A. J., Gómez Cano, C. A., & Sánchez Castillo, V. (2022). Decision making in university contexts based on knowledge management systems. Data & Metadata, 1. https://doi.org/10.56294/dm202292

Prakash, A., Haque, A., Islam, F., & Sonal, D. (2023). Exploring the Potential of Metaverse for Higher Education: Opportunities, Challenges, and Implications. Metaverse Basic and Applied Research, 2. https://doi.org/: 10.56294/mr202340

Priego Morales, R. A. (2024). El liderazgo directivo en la Nueva Escuela Mexicana y la revalorización docente desde el reconocimiento del talento humano: a scoping review. Región Científica, 3(1), 2024197. https://doi.org/10.58763/rc2024197

Rincon Soto, I. B., & Sanchez Leon, N. S. (2022). How artificial intelligence will shape the future of metaverse. A qualitative perspective. Metaverse Basic and Applied Research, 1. https://doi.org/10.56294/mr202212

Ripoll Rivaldo, M. (2023). El emprendimiento social universitario como estrategia de desarrollo en personas, comunidades y territorios. Región Científica, 2(2). https://doi.org/10.58763/rc202379

Rodríguez Torres, E., Gómez Cano, C. A., & Sánchez Castillo, V. (2022). Management information systems and their impact on business decision making. Data and Metadata, 1, 21. https://doi.org/10.56294/dm202221

Rodriguez, M. D. V. (2022). Gender, gender-based violence and training on the Micaela Law. Community and Interculturality in Dialogue, 2, 29. https://doi.org/10.56294/cid202229

Ron, M., & Escalona, E. (2023). The dynamic nature of scientific knowledge: An epistemological look at the research activity of human hand anthropometry. Community and Interculturality in Dialogue, 3, 72. https://doi.org/10.56294/cid202372

Samanta, S., Dubey, V. K., & Sarkar, B. (2021). Measure of influences in social networks. Applied Soft Computing, 99, 106858. https://doi.org/10.1016/j.asoc.2020.106858

Sánchez Suárez, Y., Pérez Gamboa, A. J., Hernández Nariño, A., Díaz-Chieng, L. Y., Marqués León, M., Pancorbo Sandoval, J. A., & Rodríguez Torres, E. (2023). Hospital culture and social responsibility: a mixed study of the main lines for its development. Salud, Ciencia Y Tecnología - Serie De Conferencias, 2, 451. https://doi.org/10.56294/sctconf2023451

Singh, S. S., Srivastva, D., Verma, M., & Singh, J. (2022). Influence maximization frameworks, performance, challenges and directions on social network: A theoretical study. Journal of King Saud University - Computer and Information Sciences, 34(9), 7570-7603. https://doi.org/10.1016/j.jksuci.2021.08.009

Sonke, J., Sams, K., Morgan-Daniel, J., Schaefer, N., Pesata, V., Golden, T., & Stuckey, H. (2021). Health Communication and the Arts in the United States: A Scoping Review. American Journal of Health Promotion, 35(1), 106-115. https://doi.org/10.1177/0890117120931710

Thomas-Acaro, R., & Meneses-Claudio, B. (2024). Technological assistance in highly competitive sports for referee decision making: A systematic literature review. Data and Metadata, 3, 188. https://doi.org/10.56294/dm2024188

Torres Barreto, M. L. (2023). Estudio de casos de éxito y fracaso de emprendedores a raíz del COVID-19 en Bucaramanga y su área metropolitana. Región Científica, 2(1), 202332. https://doi.org/10.58763/rc202332

Varghese, E. B., & Thampi, S. M. (2021). A multimodal deep fusion graph framework to detect social distancing violations and FCGs in pandemic surveillance. Engineering Applications of Artificial Intelligence, 103, 104305. https://doi.org/10.1016/j.engappai.2021.104305

Vieira, R., Faria, A. R., Ribeiro, D., Picó-Pérez, M., & Bessa, J. M. (2023). Structural and functional brain correlates of suicidal ideation and behaviors in depression: A scoping review of MRI studies. Progress in Neuro-Psychopharmacology and Biological Psychiatry, 126, 110799. https://doi.org/10.1016/j.pnpbp.2023.110799

Wang, X., Xing, Y., Wei, Y., Zheng, Q., & Xing, G. (2020). Public opinion information dissemination in mobile social networks – taking Sina Weibo as an example. Information Discovery and Delivery, 48(4), 213-224. https://doi.org/10.1108/IDD-10-2019-0075

Yang, S., Li, T., Gong, X., Peng, B., & Hu, J. (2020). A review on crowd simulation and modeling. Graphical Models, 111, 101081. https://doi.org/10.1016/j.gmod.2020.101081

Yu, Y., Moore, M., & Chapman, L. P. (2021). Social network analysis of an emerging innovation: direct-to-garment printing technology. Journal of Fashion Marketing and Management, 25(2), 274-289. https://doi.org/10.1108/JFMM-03-2020-0053

Zhang, J., Wang, W., Xia, F., Lin, Y.-R., & Tong, H. (2020). Data-Driven Computational Social Science: A Survey. Big Data Research, 21, 100145. https://doi.org/10.1016/j.bdr.2020.100145

Zheng, S., Punia, D., Wu, H., & Liu, Q. (2021). Graph Theoretic Analysis Reveals Intranasal Oxytocin Induced Network Changes Over Frontal Regions. Neuroscience, 459, 153-165. https://doi.org/10.1016/j.neuroscience.2021.01.018

Zimmern, V. (2020). Why Brain Criticality Is Clinically Relevant: A Scoping Review. Frontiers in Neural Circuits, 14, 54. https://doi.org/10.3389/fncir.2020.00054

Downloads

Published

18-08-2023

How to Cite

Gamboa, A. J. P. (2023). Contribution of graph theory to the understanding of social dynamics. AWARI, 4. https://doi.org/10.47909/awari.51

Issue

Vol. 4 (2023): AWARI

Section

Review articles

License

Copyright (c) 2023 Alfredo Javier Pérez Gamboa

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.