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Journal articles on the topic 'Network analysis'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Kilkenny, Maureen, and Nerys Fuller Love. "Network analysis and business networks." International Journal of Entrepreneurship and Small Business 21, no. 3 (2014): 303. http://dx.doi.org/10.1504/ijesb.2014.060894.

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Jadhav, Pranavati, and Dr Burra Vijaya Babu. "Detection of Community within Social Networks with Diverse Features of Network Analysis." Journal of Advanced Research in Dynamical and Control Systems 11, no. 12-SPECIAL ISSUE (2019): 366–71. http://dx.doi.org/10.5373/jardcs/v11sp12/20193232.

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CVS, Rajesh, and Nadikoppula Pardhasaradhi. "Analysis of Artificial Neural-Network." International Journal of Trend in Scientific Research and Development Volume-2, Issue-6 (2018): 418–28. http://dx.doi.org/10.31142/ijtsrd18482.

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KalaiSelvi, Dr B., and Aruna K. "Network Traffic Analysis Using Wireshark." International Journal of Research Publication and Reviews 4, no. 12 (2023): 1960–65. http://dx.doi.org/10.55248/gengpi.4.1223.123506.

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Karimi, Faezeh, David Green, Petr Matous, Manos Varvarigos, and Kaveh R. Khalilpour. "Network of networks: A bibliometric analysis." Physica D: Nonlinear Phenomena 421 (July 2021): 132889. http://dx.doi.org/10.1016/j.physd.2021.132889.

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Ashlesha, S. Nagdive, Tugnayat Rajkishor, and Peshkar Atharva. "Social Network Analysis of Terrorist Networks." International Journal of Engineering and Advanced Technology (IJEAT) 9, no. 3 (2020): 2553–59. https://doi.org/10.35940/ijeat.C5431.029320.

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Terrorist Activities worldwide has led to the development of sophisticated methodologies for analyzing terrorist groups and networks. Ongoing and past research has found that Social Network Analysis (SNA) is most effective method for predictive counter-terrorism. Social Network Analysis (SNA) is an approach towards analyzing the terrorist networks to better understand the underlying structure of a network and to detect key players within the network and their links throughout the network. It is also need of the hour to convert available raw data into valuable information for the purpose of glo

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Lobastova, M., A. Matyukhin, and A. Muthanna. "Analysis of Network Reliability of Network Synchronization." Telecom IT 8, no. 4 (2020): 93–99. http://dx.doi.org/10.31854/2307-1303-2020-8-4-93-99.

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This article describes the challenges of modern communication networks reliability, analyses ITU-T recommendations and regulations governing the communication networks reliability in Russian Federation. The network clock network is an integral part of digital communication networks. Therefore, the issue of the synchronization network reliability should be given great attention. Research subject. In this article, we discussed the reliability of the clock synchronization network. Method. The main mathematical tools are graph theory and probability theory. To implement the proposed method for ass

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Hafner-Burton, Emilie M., Miles Kahler, and Alexander H. Montgomery. "Network Analysis for International Relations." International Organization 63, no. 3 (2009): 559–92. http://dx.doi.org/10.1017/s0020818309090195.

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International relations research has regarded networks as a particular mode of organization, distinguished from markets or state hierarchies. In contrast, network analysis permits the investigation and measurement of network structures—emergent properties of persistent patterns of relations among agents that can define, enable, and constrain those agents. Network analysis offers both a toolkit for identifying and measuring the structural properties of networks and a set of theories, typically drawn from contexts outside international relations, that relate structures to outcomes. Network analy

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PELLEGRINI, Lilla, Monica LEBA, and Alexandru IOVANOVICI. "CHARACTERIZATION OF URBAN TRANSPORTATION NETWORKS USING NETWORK MOTIFS." Acta Electrotechnica et Informatica 20, no. 4 (2020): 3–9. http://dx.doi.org/10.15546/aeei-2020-0019.

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We use tools and techniques specific to the field of complex networks analysis for the identification and extraction of key parameters which define ”good” patterns and practices for designing public transportation networks. Using network motifs we analyze a set of 18 cities using public data sets regarding the topology of network and discuss each of the identified motifs using the concepts and tools of urban planning.

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Nasution, Mahyuddin K. M., Rahmad Syah, and Marischa Elveny. "Social Network Analysis: Towards Complexity Problem." Webology 18, no. 2 (2021): 449–61. http://dx.doi.org/10.14704/web/v18i2/web18332.

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Social network analysis is a advances from field of social networks. The structuring of social actors, with data models and involving intelligence abstracted in mathematics, and without analysis it will not present the function of social networks. However, graph theory inherits process and computational procedures for social network analysis, and it proves that social network analysis is mathematical and computational dependent on the degree of nodes in the graph or the degree of social actors in social networks. Of course, the process of acquiring social networks bequeathed the same complexit

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M., Shankar. "Social Network Analysis." Shanlax International Journal of Commerce 7, S1 (2019): 259–60. https://doi.org/10.5281/zenodo.3451720.

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Social Network analysis is an investigation made on social structures through the use of networks. The field of social network analysis is the dynamic and highly adaptable combination of techniques that let us quantify and recognize the complex structures and flows of relationships, thoughts, and things between people around the world.     Social network analysis has emerged as a critical technique in modern sociology. It has also gained an important following in economics, geography, history, information science, organizational studies, anthropology, biology, demography, commun

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Quinn, Darren, Liming Chen, and Maurice Mulvenna. "Social Network Analysis." International Journal of Ambient Computing and Intelligence 4, no. 3 (2012): 46–58. http://dx.doi.org/10.4018/jaci.2012070104.

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Social Network Analysis is attracting growing attention as social networking sites and their enabled applications transform and impact society. This paper aims to provide a comprehensive review of social network analysis state of the art research and practice. In the paper the authors’ first examine social networking and the core concepts and ingredients of social network analysis. Secondly, they review the trend of social networking and related research. The authors’ then consider modelling motivations, discussing models in line with tie formation approaches, where connections between nodes a

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Tran, Ngoc Tam L., Luke DeLuccia, Aidan F. McDonald, and Chun-Hsi Huang. "Cross-Disciplinary Detection and Analysis of Network Motifs." Bioinformatics and Biology Insights 9 (January 2015): BBI.S23619. http://dx.doi.org/10.4137/bbi.s23619.

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The detection of network motifs has recently become an important part of network analysis across all disciplines. In this work, we detected and analyzed network motifs from undirected and directed networks of several different disciplines, including biological network, social network, ecological network, as well as other networks such as airlines, power grid, and co-purchase of political books networks. Our analysis revealed that undirected networks are similar at the basic three and four nodes, while the analysis of directed networks revealed the distinction between networks of different disc

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Mills, E. J., K. Thorlund, and J. P. A. Ioannidis. "Demystifying trial networks and network meta-analysis." BMJ 346, may14 2 (2013): f2914. http://dx.doi.org/10.1136/bmj.f2914.

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Davel, Ronel, Adeline S. A. Du Toit, and Martie M. Mearns. "Understanding Knowledge Networks Through Social Network Analysis." International Journal of Knowledge Management 13, no. 2 (2017): 1–17. http://dx.doi.org/10.4018/ijkm.2017040101.

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Social network analysis (SNA) is being increasingly deployed as an instrument to plot knowledge and expertise as well as to confirm the character of connections in informal networks within organisations. This study investigated how the integration of networking into KM can produce significant advantages for organisations. The aim of the research was to examine how the interactions between SNA, Communities of Practice (CoPs) and knowledge maps could potentially influence knowledge networks. The researchers endeavour to illustrate via this question that cultivating synergies between SNA, CoPs an

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Robins, Garry, Jenny M. Lewis, and Peng Wang. "Statistical Network Analysis for Analyzing Policy Networks." Policy Studies Journal 40, no. 3 (2012): 375–401. http://dx.doi.org/10.1111/j.1541-0072.2012.00458.x.

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Fang, Yimeng. "Robustness analysis of highway network based on complex network." Highlights in Science, Engineering and Technology 42 (April 7, 2023): 291–97. http://dx.doi.org/10.54097/hset.v42i.7108.

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Taking Chongqing, Hunan, Shandong, Shaanxi and Sichuan as examples, this paper conducts a comparative study on the robustness of their highway networks, which is helpful for the subsequent construction of China's highway networks. The topology structure of highway networks is studied by complex network theory. The degree distribution, average degree, average clustering coefficient, average path length, network diameter and other parameters of the network were calculated, and the robustness of the highway network in five provinces and cities was compared from four aspects: connectivity, network

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Rahat Naseem, Rahat Naseem, and Jungmann Lee. "IT Policy Analysis using Keyword Network Analysis: Pakistan Case Study." Dongguk Business Research Institute 47, no. 1 (2025): 21–52. https://doi.org/10.55685/bcr.2025.47.1.21.

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Pakistan's socio-economic landscape through digital technology, with digital infrastructure as the foundation for economic growth, social inclusion, and governance reform. Keyword network analysis was employed to analyze Pakistan's digital policy, and based on this, cognitive map analysis was conducted to analyze policy implications and policy directions. A keyword network analysis using the R program identified key themes such as “digital transformation,” “e-governance,” “AI,” and “blockchain” to highlight their importance within the policy framework, which focuses on innovation, global compe

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Liu, Yaoxuan. "Analysis of network resilienceon global air transportation." Applied and Computational Engineering 6, no. 1 (2023): 67–75. http://dx.doi.org/10.54254/2755-2721/6/20230678.

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Small-world network is a very common network structure, which is characterized by low average degree, small average path length and high centrality. At the same time, small-world networks have high resilience to random errors and low resilience to targeted attacks. In this study, the importance of nodes is represented by attributes such as degree and centrality, and attacks refer to the removal of important nodes. The network is attacked according to the degree, betweenness and closeness centrality to observe the power distribution. The data is mainly obtained from the open source OpenFlight.

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Löblich, Maria, and Senta Pfaff-Rüdiger. "Network analysis." International Communication Gazette 73, no. 7 (2011): 630–47. http://dx.doi.org/10.1177/1748048511417159.

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Structures of interest, influence and power in communication policy are shifting due to increasing digitization, economization and globalization. Against this background it is necessary to reflect more than before upon methods to study the relations between actors and their potential influences on regulation processes. The article explains qualitative network analysis as a research strategy for communication policy research and discusses qualitative interviews and network cards as research tools to put network analysis into practice. The theoretical basis consists of governance and network the

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Fath, Brian D., Ursula M. Scharler, Robert E. Ulanowicz, and Bruce Hannon. "Ecological network analysis: network construction." Ecological Modelling 208, no. 1 (2007): 49–55. http://dx.doi.org/10.1016/j.ecolmodel.2007.04.029.

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Yang, Hong Mei, Chun Ying Zhang, Rui Tao Liang, and Fang Tian. "Set Pair Social Network Analysis Model." Applied Mechanics and Materials 50-51 (February 2011): 63–67. http://dx.doi.org/10.4028/www.scientific.net/amm.50-51.63.

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Through the study on social network information, this paper explore that there exists the certain and uncertain phenomena in the process of finding the relationship between individuals by using social networks, and the social networks are constantly changing. In light of there are some uncertainty and dynamic problems for the network, this paper put forward the set pair social network analysis model and set pair social network analysis model and its properties.

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KC, Birendra, Duarte B. Morais, M. Nils Peterson, Erin Seekamp, and Jordan W. Smith. "Social network analysis of wildlife tourism microentrepreneurial network." Tourism and Hospitality Research 19, no. 2 (2017): 158–69. http://dx.doi.org/10.1177/1467358417715679.

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Social networks are an important element of entrepreneurship. Entrepreneurs rely on social networks to access ideas, information, and resources to facilitate their entrepreneurial process. Strong and weak ties influence the entrepreneurial process in unique ways. This study utilized social network analysis approach to examine wildlife tourism microentrepreneurship through in-person structured interviews with 37 microentrepreneurs from North Carolina’s Pamlico Sound Region. Specifically, this study examined the extent of network ties, the type of support received from those network ties, and th

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AYDIN, Nursen. "Social Network Analysis: Literature Review." AJIT-e Online Academic Journal of Information Technology 9, no. 34 (2018): 73–80. http://dx.doi.org/10.5824/1309-1581.2018.4.005.x.

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In this article, social network analysis SNA is defined and historical development process is explained. A comprehensive literature search has been conducted for this purpose. SAA is a powerful method that centralizes individuals and their relations, in that the effect of the individual on the social network can be uncovered and the network of individual groups can be evaluated holistically. SNA shows the structural gaps and social capital in institutions, and focuses managers' attention on critical informal networks. Evaluating strategically important networks within an organization, make "in

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KOVACIK, Cyril Filip, and Gabriel BUGAR. "ANALYSIS OF OPERATIONAL PROPERTIES OF VOIP NETWORK." Acta Electrotechnica et Informatica 1335-8243, no. 1338-3957 (2021): 30–34. http://dx.doi.org/10.15546/aeei-2021-0005.

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Voice transmission over the Internet network is now taken for granted. Many end-user applications address this issue. However, this paper focuses on the specific use of the SCCP protocol created by Cisco, its implementation in a computer network and end devices, determination of the operational properties of this implementation, and their comparison in different conditions. VoIP traffic is compared at different bandwidths and implemented by different configurations of IP protocols. By investigated implementations of IP protocols are meant IPv4, IPv6, and IPv4 protocol with applied NAT. As part

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Kamiyama, Noriaki. "DESIGNING NETWORK TOPOLOGY USING DATA ENVELOPMENT ANALYSIS." Journal of the Operations Research Society of Japan 56, no. 3 (2013): 199–220. http://dx.doi.org/10.15807/jorsj.56.199.

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Chen, Wei-Yu, Shing-Han Li, Mann-Jung Hsiao, Chung-Chiang Hu, and Kuo-Ching Tu. "Network Security Analysis by Using Business Intelligence." International Journal of Machine Learning and Computing 5, no. 6 (2015): 431–38. http://dx.doi.org/10.18178/ijmlc.2015.5.6.547.

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Ganesh, V. Dilli, and G. Vadivu. "Ego Network Analysis for Predicting Students Performance." International Journal of Trend in Scientific Research and Development Volume-1, Issue-5 (2017): 722–35. http://dx.doi.org/10.31142/ijtsrd2364.

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Shcherbakov, V. S., and I. A. Karpov. "Regional Inflation Analysis Using Social Network Data." Economy of Regions 20, no. 3 (2024): 930–46. http://dx.doi.org/10.17059/ekon.reg.2024-3-21.

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Inflation is one of the most important macroeconomic indicators that have a great impact on the population of any country and region. Inflation is influenced by a range of factors, including inflation expectations. Many central banks take this factor into consideration while implementing monetary policy within the inflation targeting regime. Nowadays, a lot of people are active users of the Internet, especially social networks. It is hypothesised that people search, read, and discuss mainly only those issues that are of particular interest to them. It is logical to assume that the dynamics of

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ELAGIN, V. S., and A. S. VASIN. "ANALYSIS OF NETWORK RESOURCE SCALING MODELS IN 5G NETWORK." T-Comm 17, no. 5 (2023): 32–41. http://dx.doi.org/10.36724/2072-8735-2023-17-5-32-41.

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This article analyzes the existing models of virtual network embedding and dynamic scaling of virtual network resources for Network Slices. These models make it possible to provide services with the required QoS while respecting the concept of efficient network resource usage. Dynamic virtual network embedding models allow virtual networks to be efficiently mapped on a substrate network and reconfigured on demand. But for more flexible dynamic scaling, Holt-Winters, Bi-LSTM and etc. models are additionally used, which are built according algorithms for predicting future resource utilization in

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Tusher, Chandra Ghosh, and Ismail Jabiullah Md. "Analysis of Network Security Issues and Threats Analysis on 5G Wireless Networks." Recent Trends in Information Technology and its Application 4, no. 3 (2021): 1–11. https://doi.org/10.5281/zenodo.5573669.

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We are going to enter the world of the 5G network. There are many advanced features in the 5G network. The newer features come, the more security will be required, for all these new features. This paper is a survey for 5 generations of wireless network security, complete and thorough our current cellular network. This paper starts with a rethink of 5G wireless networks circumstantial as well as on the new pretension and motivations of 5G wireless security. The effective offensive and security services with the thought of new service necessity and latest use-cases in 5G Wireless Network securit

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Arul, Sharmila Mary, Gowri Senthil, S. Jayasudha, Ahmed Alkhayyat, Khalikov Azam, and R. Elangovan. "Graph Theory and Algorithms for Network Analysis." E3S Web of Conferences 399 (2023): 08002. http://dx.doi.org/10.1051/e3sconf/202339908002.

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In network analysis, the study and comprehension of complex systems in numerous fields, such as social networks, transportation networks, and biological networks, are made possible by the crucial role played by graph theory and algorithms. In order to give a comprehensive review of the graph theory and network analysis methods, this abstract will focus on their significance, practical uses, and most recent developments. With items represented as nodes or vertices and links between them as edges, graph theory offers a mathematical framework for modeling and evaluating relationships between obje

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Scherbakova, N. G., and S. V. Bredikhin. "Co-authorship network structure analysis." Journal of Physics: Conference Series 2099, no. 1 (2021): 012055. http://dx.doi.org/10.1088/1742-6596/2099/1/012055.

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Abstract The analysis of networks of collaboration between scientists reveals features of academic communities that help in understanding the specifics of collaborative scientific work and identifying the notable researchers. In these networks, the set of nodes consists of authors and there exists a link between two authors if they have coauthored one or more papers. This article presents an analysis of the co-authorship network based on bibliometric data retrieved from the distributed economic database. Here we use the simple network model without taking into account the strength of collabora

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Khan, Faiz M., Shailendra K. Gupta, and Olaf Wolkenhauer. "Integrative workflows for network analysis." Essays in Biochemistry 62, no. 4 (2018): 549–61. http://dx.doi.org/10.1042/ebc20180005.

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Due to genetic heterogeneity across patients, the identification of effective disease signatures and therapeutic targets is challenging. Addressing this challenge, we have previously developed a network-based approach, which integrates heterogeneous sources of biological information to identify disease specific core-regulatory networks. In particular, our workflow uses a multi-objective optimization function to calculate a ranking score for network components (e.g. feedback/feedforward loops) based on network properties, biomedical and high-throughput expression data. High ranked network compo

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Eremeev, Igor, Maxim Tatarka, Fedor Shuvaev, and Andrey Tsyganov. "Comparative Analysis of Centrality Measures of Network Nodes based on Principal Component Analysis." Informatics and Automation 19, no. 6 (2020): 1307–31. http://dx.doi.org/10.15622/ia.2020.19.6.7.

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. The analysis of networks of a diverse nature, which are citation networks, social networks or information and communication networks, includes the study of topological properties that allow one to assess the relationships between network nodes and evaluate various characteristics, such as the density and diameter of the network, related subgroups of nodes, etc. For this, the network is represented as a graph – a set of vertices and edges between them. One of the most important tasks of network analysis is to estimate the significance of a node (or in terms of graph theory – a vertex). For th

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Zhang, Haomiao, and Qing Liu. "Optimization Algorithm of Communication Resource Allocation in a Complex Network Based on an Improved Neural Network." Journal of Function Spaces 2022 (July 28, 2022): 1–8. http://dx.doi.org/10.1155/2022/7309612.

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The traditional optimization algorithm of communication resource allocation in a complex network has the disadvantage of weak antijamming ability, and the communication quality decreases obviously when the number of users is large. In China’s large urban network applications, mobile phones and other networks can have problems such as reduced network efficiency when there are more access users at some communication base stations, thus affecting user network usage. An optimization algorithm of communication resource allocation in the complex network based on an improved neural network is propose

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Nie, Chun-Xiao. "Hurst analysis of dynamic networks." Chaos: An Interdisciplinary Journal of Nonlinear Science 32, no. 2 (2022): 023130. http://dx.doi.org/10.1063/5.0070170.

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The sequence of network snapshots with time stamps is an effective tool for describing system dynamics. First, this article constructs a multifractal analysis of a snapshot network, in which the Hurst integral is used to describe the fractal structure hidden in structural dynamics. Second, we adjusted the network model and conducted comparative analysis to clarify the meaning of the Hurst exponent and found that the snapshot network usually includes multiple fractal structures, such as local and global fractal structures. Finally, we discussed the fractal structure of two real network datasets

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Ye, Cheng, Richard Wilson, Luca Rossi, Andrea Torsello, and Edwin Hancock. "Thermodynamic Analysis of Time Evolving Networks." Entropy 20, no. 10 (2018): 759. http://dx.doi.org/10.3390/e20100759.

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The problem of how to represent networks, and from this representation, derive succinct characterizations of network structure and in particular how this structure evolves with time, is of central importance in complex network analysis. This paper tackles the problem by proposing a thermodynamic framework to represent the structure of time-varying complex networks. More importantly, such a framework provides a powerful tool for better understanding the network time evolution. Specifically, the method uses a recently-developed approximation of the network von Neumann entropy and interprets it a

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Parise, Francesca, and Asuman Ozdaglar. "Analysis and Interventions in Large Network Games." Annual Review of Control, Robotics, and Autonomous Systems 4, no. 1 (2021): 455–86. http://dx.doi.org/10.1146/annurev-control-072020-084434.

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We review classic results and recent progress on equilibrium analysis, dynamics, and optimal interventions in network games with both continuous and discrete strategy sets. We study strategic interactions in deterministic networks as well as networks generated from a stochastic network formation model. For the former case, we review a unifying framework for analysis based on the theory of variational inequalities. For the latter case, we highlight how knowledge of the stochastic network formation model can be used by a central planner to design interventions for large networks in a computation

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MISS, SUPRIYA KUMARI BISWAL, and MRS. PRADNYA MULEY PROF. "DATA MINING IN SOCIAL NETWORK ANALYSIS." IJIERT - International Journal of Innovations in Engineering Research and Technology 5, no. 5 (2018): 9–12. https://doi.org/10.5281/zenodo.1445979.

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<strong>online communities and social software we can communicate with the web. Analysis of interactions happening is complex. Social network analysis (SNA) is a useful way to analyse . Data mining uses different type of statistical,machine learning and graphic al methods and differentiates into a form of knowledge that is useful for most real - world applications. Analysis of social networks is now a popular field for research because it is useful for most applications. In this paper we have discussed the various data mining techniques used for social network analysis.</strong> <strong>https:

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Himelboim, Itai, Marc A. Smith, Lee Rainie, Ben Shneiderman, and Camila Espina. "Classifying Twitter Topic-Networks Using Social Network Analysis." Social Media + Society 3, no. 1 (2017): 205630511769154. http://dx.doi.org/10.1177/2056305117691545.

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As users interact via social media spaces, like Twitter, they form connections that emerge into complex social network structures. These connections are indicators of content sharing, and network structures reflect patterns of information flow. This article proposes a conceptual and practical model for the classification of topical Twitter networks, based on their network-level structures. As current literature focuses on the classification of users to key positions, this study utilizes the overall network structures in order to classify Twitter conversation based on their patterns of informat

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Blair, Alan D., and Jordan B. Pollack. "Analysis of Dynamical Recognizers." Neural Computation 9, no. 5 (1997): 1127–42. http://dx.doi.org/10.1162/neco.1997.9.5.1127.

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Pollack (1991) demonstrated that second-order recurrent neural networks can act as dynamical recognizers for formal languages when trained on positive and negative examples, and observed both phase transitions in learning and interacted function system-like fractal state sets. Follow on work focused mainly on the extraction and minimization of a finite state automaton (FSA) from the trained network. However, such networks are capable of inducing languages that are not regular and therefore not equivalent to any FSA. Indeed, it may be simpler for a small network to fit its training data by indu

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Song, Yuning, Liping Ding, Mengying Dong, Xuehua Liu, and Xiao Wang. "Multi-mode Network Analysis under Differential Privacy." Journal of Physics: Conference Series 2082, no. 1 (2021): 012010. http://dx.doi.org/10.1088/1742-6596/2082/1/012010.

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Abstract With the advent of the big data era and the advancement of social network analysis, the public is increasingly concerned about the privacy protection in today’s complex social networks. For the past few years, the rapid development of differential privacy (DP) technology, as a method with a reliable theoretical basis, can effectively solve the key problem of how to “disassociate” personal information in social networks. This paper focuses on the multi-mode heterogeneous network model which has attracted a lot of attention in the field of network research. It introduces differential pr

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Ren, Xiaolong, Zhenyu Zhang, and Zixvan Yu. "Analysis of the Complex Characteristics of the New York City Subway Network." Highlights in Science, Engineering and Technology 64 (August 21, 2023): 99–106. http://dx.doi.org/10.54097/hset.v64i.11252.

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Complex networks are important to the real world. Complex networks are instructive for the study of real networks such as metro networks, social networks and information networks. This paper study the New York City subway network and use complex network theory to research the static properties of subway complex network. Conclude that 79% of the nodes in the New York City subway network have degree 2, the network diameter is 59, more than 90% of the network nodes have a clustering coefficient of 0, the standard robustness of the network is 0.326, and the average shortest path length of the netw

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Skvoretz, John. "Pas de Deux: Social Networks and Network Analysis." Contemporary Sociology: A Journal of Reviews 37, no. 5 (2008): 423–26. http://dx.doi.org/10.1177/009430610803700511.

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Kyriakopoulos, F., S. Thurner, C. Puhr, and S. W. Schmitz. "Network and eigenvalue analysis of financial transaction networks." European Physical Journal B 71, no. 4 (2009): 523–31. http://dx.doi.org/10.1140/epjb/e2009-00255-7.

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Madhavi M. Kulkarni. "Enhancing Social Network Analysis using Graph Neural Networks." Advances in Nonlinear Variational Inequalities 27, no. 4 (2024): 213–30. http://dx.doi.org/10.52783/anvi.v27.1502.

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Abstract:

Social Network Analysis (SNA) may be a key apparatus for figuring out how individuals in social systems interface and relate to each other. Most of the time, chart hypothesis, factual models, and machine learning are utilized in conventional SNA strategies. Be that as it may, these strategies have inconvenience finding complex designs in huge, changing, and assorted systems. Chart Neural Systems (GNNs) are a modern and solid way to progress SNA. They learn models straight from graph-structured information, which makes them exceptionally great at assignments like finding communities, classifyin

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Pe'er, D. "Bayesian Network Analysis of Signaling Networks: A Primer." Science Signaling 2005, no. 281 (2005): pl4. http://dx.doi.org/10.1126/stke.2812005pl4.

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Chan, Wai Kin Victor, and Cheng Hsu. "How Hyper-Network Analysis Helps Understand Human Networks?" Service Science 2, no. 4 (2010): 270–80. http://dx.doi.org/10.1287/serv.2.4.270.

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Cárdenas, Julián. "Varieties of corporate networks: Network analysis and fsQCA." International Journal of Comparative Sociology 53, no. 4 (2012): 298–322. http://dx.doi.org/10.1177/0020715212460257.

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