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Relevant bibliographies by topics / Network analysis and visualization

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Journal articles
Dissertations / Theses
Books
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Conference papers
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Academic literature on the topic 'Network analysis and visualization'

Author: Grafiati

Published: 25 January 2025

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Journal articles on the topic "Network analysis and visualization"

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Jeong, Dong Hyun, Bong-Keun Jeong, and Soo-Yeon Ji. "Multi-Resolution Analysis with Visualization to Determine Network Attack Patterns." Applied Sciences 13, no. 6 (2023): 3792. http://dx.doi.org/10.3390/app13063792.

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Analyzing network traffic activities is imperative in network security to detect attack patterns. Due to the complex nature of network traffic event activities caused by continuously changing computing environments and software applications, identifying the patterns is one of the challenging research topics. This study focuses on analyzing the effectiveness of integrating Multi-Resolution Analysis (MRA) and visualization in identifying the attack patterns of network traffic activities. In detail, a Discrete Wavelet Transform (DWT) is utilized to extract features from network traffic data and i

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Wang, Lidong. "Big Data and IT Network Data Visualization." International Journal of Mathematical, Engineering and Management Sciences 3, no. 1 (2018): 9–16. http://dx.doi.org/10.33889/ijmems.2018.3.1-002.

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Visualization with graphs is popular in the data analysis of Information Technology (IT) networks or computer networks. An IT network is often modelled as a graph with hosts being nodes and traffic being flows on many edges. General visualization methods are introduced in this paper. Applications and technology progress of visualization in IT network analysis and big data in IT network visualization are presented. The challenges of visualization and Big Data analytics in IT network visualization are also discussed. Big Data analytics with High Performance Computing (HPC) techniques, especially

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Gelernter, Judith, and Kathleen M. Carley. "Spatiotemporal Network Analysis and Visualization." International Journal of Applied Geospatial Research 6, no. 2 (2015): 77–97. http://dx.doi.org/10.4018/ijagr.2015040105.

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Spatiotemporal social network analysis shows relationships among people at a particular time and location. This paper presents an algorithm that mines text for person and location words and creates connections among words. It shows how this algorithm output, when chunked by time intervals, may be visualized by third-party social network analysis software in the form of standard network pin diagrams or geographic maps. Its data sample comes from newspaper articles concerning the 2006 Darfur crisis in Sudan. Given an immense data sample, it would be possible to use the algorithm to detect trends

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Xu, Jennifer, and Hsinchun Chen. "Criminal network analysis and visualization." Communications of the ACM 48, no. 6 (2005): 100–107. http://dx.doi.org/10.1145/1064830.1064834.

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Murugesan, Sugeerth, Kristofer Bouchard, Jesse Brown, et al. "State-based network similarity visualization." Information Visualization 19, no. 2 (2019): 96–113. http://dx.doi.org/10.1177/1473871619882019.

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We introduce an approach for the interactive visual analysis of weighted, dynamic networks. These networks arise in areas such as computational neuroscience, sociology, and biology. Network analysis remains challenging due to complex time-varying network behavior. For example, edges disappear/reappear, communities grow/vanish, or overall network topology changes. Our technique, TimeSum, detects the important topological changes in graph data to abstract the dynamic network and visualize one summary representation for each temporal phase, a state. We define a network state as a graph with simil

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Fitri, Marisa Meliana, Iswandi U, Nurhasan Syah, and Elsa Yuniarti. "Bibliometric Analysis of Spatial Stunting Using VOSviewer." Jurnal Penelitian Pendidikan IPA 9, no. 12 (2023): 1298–305. http://dx.doi.org/10.29303/jppipa.v9i12.5914.

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Stunting, or stunted growth, is a serious global public health problem. The aim of this research is to investigate the dynamics of co-occurrence, trends and saturation of keywords in spatial studies related to stunting using the literature review method. This research uses bibliometric analysis with the help of Web Lens.org, Openrefine, and VOSviewer for data collection and analysis. VOSviewer can display bibliometric mapping in three different visualizations, including network visualization, overlay visualization, and density visualization. The findings of this research reveal seven topic clu

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Papadopoulou, Olga, Themistoklis Makedas, Lazaros Apostolidis, Francesco Poldi, Symeon Papadopoulos, and Ioannis Kompatsiaris. "MeVer NetworkX: Network Analysis and Visualization for Tracing Disinformation." Future Internet 14, no. 5 (2022): 147. http://dx.doi.org/10.3390/fi14050147.

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The proliferation of online news, especially during the “infodemic” that emerged along with the COVID-19 pandemic, has rapidly increased the risk of and, more importantly, the volume of online misinformation. Online Social Networks (OSNs), such as Facebook, Twitter, and YouTube, serve as fertile ground for disseminating misinformation, making the need for tools for analyzing the social web and gaining insights into communities that drive misinformation online vital. We introduce the MeVer NetworkX analysis and visualization tool, which helps users delve into social media conversations, helps u

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Selçuk, Mustafa, and Junior Hendri Wijaya. "Analysis of Agrarian Transformation Research." GOVERNABILITAS (Jurnal Ilmu Pemerintahan Semesta) 5, no. 1 (2024): 68–79. http://dx.doi.org/10.47431/governabilitas.v5i1.426.

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Research on Agrarian Transformation is important because it touches on how a change or transformation occurs in the agricultural sector, which will also affect the condition of society. This research focuses on bibliometric analysis that seeks to analyze how research related to agrarian transformation is carried out. In this study, VOSviewer and Publish or Perish are used to facilitate data search and depiction. Data from the Scopus database is searched through Publish or Perish, with the keyword Agrarian Transformation. Furthermore, to visualize the data, VOSviewer version 1.6.19 is used to v

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Benito Amat, Carlos. "Network analysis and visualization with Gephi." Redes. Revista hispana para el análisis de redes sociales 25, no. 1 (2014): 201. http://dx.doi.org/10.5565/rev/redes.499.

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Lan, Wang Sen, Guo Hao Zhao, and Li Jun Hou. "Stocks Network Analysis Based on Visualization." Applied Mechanics and Materials 50-51 (February 2011): 323–27. http://dx.doi.org/10.4028/www.scientific.net/amm.50-51.323.

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In order to explore interactions among stocks, a weighted complex network was modeled, whose nodes were stocks, connection between nodes was established by their correlation, and the weight on corresponding edge was their correlation coefficient. The article analyzed some influence behaves among stocks by using visualization method, and gave some algorithms to find out network maximum spanning tree and core network. The result shows that the network is scale-free, nodes coupling are of homology, and some nodes are of strong influence on others.

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Dissertations / Theses on the topic "Network analysis and visualization"

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Köstinger, Harald. "ViNCent – Visualization of NetworkCentralities." Thesis, Linnéuniversitetet, Institutionen för datavetenskap, fysik och matematik, DFM, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-10793.

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In the area of information visualization social or biological networks are visualized ina way so that they can be explored easily and one can get more information about thestructure of the network out of it. The use of network centralities in the field of network analysis plays an importantrole when it comes to the rating of the relative importance of vertices within the networkstructure based on the neighborhood of them. Such a single network can be renderedeasily by the use of standard graph drawing algorithms. But it is not only the explorationof one centrality which is important. Furthermo

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Yu, En. "Social Network Analysis Applied to Ontology 3D Visualization." Miami University / OhioLINK, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=miami1206497854.

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Catanese, Salvatore Amato. "New perspectives in criminal network analysis: multilayer networks, time evolution, and visualization." Doctoral thesis, Università di Catania, 2017. http://hdl.handle.net/10761/3793.

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The work presented in this Dissertation reflects a long-term human, professional and cultural path started some years ago when I first developed LogAnalysis, a tool for the analysis and visualization of criminal and social networks. Since then, I devoted myself to the development of frameworks, algorithms and techniques for supporting intelligence and law enforcement agencies in the task of unveiling the CN structure hidden in communication data, identifying the target offenders for their removal or selecting effective strategies to disrupt a criminal organization. In a natural way, I successi

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Eiesland, Jon Wostryck. "Communities in a large social network : visualization and analysis." Thesis, Norwegian University of Science and Technology, Department of Physics, 2009. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-6409.

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<p>Communities have been a hot topic in complex network research the last years. Several algorithms for detecting communities have been developed, and in this thesis we use the sequential clique percolation algorithm to detect communities in a large social network. Our network consists of 5.3 million mobile phone users, with mutual communication data aggregated over 18 weeks.</p><p>In this thesis we do a visual study of the communities, and we clearly see the nested community structure when we do clique percolation for dierent clique sizes. When we threshold the edge weights we see that the st

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El-Shehaly, Mai Hassan. "A Visualization Framework for SiLK Data exploration and Scan Detection." Thesis, Virginia Tech, 2009. http://hdl.handle.net/10919/34606.

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Network packet traces, despite having a lot of noise, contain priceless information, especially for investigating security incidents or troubleshooting performance problems. However, given the gigabytes of flow crossing a typical medium sized enterprise network every day, spotting malicious activity and analyzing trends in network behavior becomes a tedious task. Further, computational mechanisms for analyzing such data usually take substantial time to reach interesting patterns and often mislead the analyst into reaching false positives, benign traffic being identified as malicious, or false

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Kasemsri, Rawiroj Robert. "A Survey, Taxonomy, and Analysis of Network Security Visualization Techniques." Digital Archive @ GSU, 2006. http://digitalarchive.gsu.edu/cs_theses/17.

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Network security visualization is a relatively new field and is quickly gaining momentum. Network security visualization allows the display and projection of the network or system data, in hope to efficiently monitor and protect the system from any intrusions or possible attacks. Intrusions and attacks are constantly continuing to increase in number, size, and complexity. Textually reading through log files or other textual sources is currently insufficient to secure a network or system. Using graphical visualization, security information is presented visually, and not only by text. Without ne

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Perer, Adam Nathaniel. "Integrating statistics and visualization to improve exploratory social network analysis." College Park, Md.: University of Maryland, 2008. http://hdl.handle.net/1903/8502.

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Thesis (Ph. D.) -- University of Maryland, College Park, 2008.<br>Thesis research directed by: Dept. of Computer Science. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.

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Freet, David Nathan. "A Security Visualization Analysis Methodology for Improving Network Intrusion Detection Efficiency." Thesis, Indiana State University, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10261868.

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<p> The flood of raw data generated by intrusion detection and other network monitoring devices can be so overwhelming that it causes great difficulty in detecting patterns that might indicate malicious traffic. In order to more effectively monitor and process network and forensic data within a virtualized environment, Security Visualization (SecViz) provides software-based visual interfaces to analyze live and logged network data within the domains of network security, network and cloud forensics, attack prevention, compliance management, wireless security, secure coding, and penetration test

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Anantachai, Arnond. "A New Mobile Network Simulation And Analysis System And The Use Of Network Visualizations Through An End-User Graphics Package." OpenSIUC, 2010. https://opensiuc.lib.siu.edu/theses/243.

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Network simulations often output a log file, which must be parsed to understand the details of the simulation. Visualizations of these simulations are used to make debugging and analysis easier, and there are many visualizers that will display the simulation in 2D. Those in 3D do not fully utilize 3D graphics operations to visualize asimulation. This thesis explores the ways 3D graphics can be used to further enhance a visualization. To do this, it introduces a new network simulator and a visualizer, consisting of an analyzer, which collects statistics about a simulation, and a renderer, which

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Dalton, Andrew R. "Analysis, instrumentation, and visualization of embedded network systems a testbed-based approach /." Connect to this title online, 2008. http://etd.lib.clemson.edu/documents/1219849076/.

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Books on the topic "Network analysis and visualization"

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De Domenico, Manlio. Multilayer Networks: Analysis and Visualization. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-75718-2.

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Zhao, Dangzhi, and Andreas Strotmann. Analysis and Visualization of Citation Networks. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-031-02291-3.

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Manavis, T. D. Visualization of graph networks for the analysis ofpiecewiselinear systems. UMIST, 1994.

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Turdukulov, Ulanbek Duyshokovich. Visualizing the evolution of image features in time-series: Supporting the exploration of sensor data = Visualisatie van veranderende objecten in multitemporele beelden : ondersteuning van de exploratie van sensor gegevens. Universiteit Utrecht, 2007.

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Schich, Maximilian. Rezeption und Tradierung als komplexes Netzwerk: Der CENSUS und visuelle Dokumente zu den Thermen in Rom. Biering & Brinkmann, 2009.

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Kerren, Andreas, Helen C. Purchase, and Matthew O. Ward, eds. Multivariate Network Visualization. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-06793-3.

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Brandes, Ulrik, and Thomas Erlebach, eds. Network Analysis. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/b106453.

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Combined Higher Education Software Team., Environmental Systems Research Institute, and Manchester Computing Centre, eds. Network analysis. Manchester Computing Centre, 1993.

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Bailey, David H., Naomi Simone Borwein, Richard P. Brent, et al., eds. From Analysis to Visualization. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-36568-4.

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Lee, Eun Young, Johannes Novotny, and Michael Wagreich. Subsidence Analysis and Visualization. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-76424-5.

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Book chapters on the topic "Network analysis and visualization"

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Pretorius, Johannes, Helen C. Purchase, and John T. Stasko. "Tasks for Multivariate Network Analysis." In Multivariate Network Visualization. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-06793-3_5.

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Tan, Yuanru, Cesar Hinojosa, Cody Marquart, Andrew R. Ruis, and David Williamson Shaffer. "Epistemic Network Analysis Visualization." In Communications in Computer and Information Science. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-93859-8_9.

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Desai, Rishi M., William J. R. Longabaugh, and Wayne B. Hayes. "BioFabric Visualization of Network Alignments." In Recent Advances in Biological Network Analysis. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-57173-3_4.

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Zhao, Dangzhi, and Andreas Strotmann. "Disambiguation in Citation Network Analysis." In Analysis and Visualization of Citation Networks. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-031-02291-3_4.

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Hu, Yifan. "Visualization of Large Networks." In Encyclopedia of Social Network Analysis and Mining. Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4614-7163-9_44-1.

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Hu, Yifan. "Visualization of Large Networks." In Encyclopedia of Social Network Analysis and Mining. Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4614-6170-8_44.

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Hu, Yifan. "Visualization of Large Networks." In Encyclopedia of Social Network Analysis and Mining. Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4939-7131-2_44.

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Tripathi, Shailesh, Salissou Moutari, Matthias Dehmer, and Frank Emmert-Streib. "Visualization of Biological Networks Using NetBioV." In Computational Network Analysis with R. Wiley-VCH Verlag GmbH & Co. KGaA, 2016. http://dx.doi.org/10.1002/9783527694365.ch11.

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Zaidi, Faraz, Chris Muelder, and Arnaud Sallaberry. "Analysis and Visualization of Dynamic Networks." In Encyclopedia of Social Network Analysis and Mining. Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4614-7163-9_382-1.

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Zaidi, Faraz, Chris Muelder, and Arnaud Sallaberry. "Analysis and Visualization of Dynamic Networks." In Encyclopedia of Social Network Analysis and Mining. Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4614-6170-8_382.

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Conference papers on the topic "Network analysis and visualization"

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Baharudin, Shahidatul Arfah, Nurul Iman Muhammad Taufik, Sri Banu Munisamy, and Adidah Lajis. "Network Performance Analysis Of SCTP Protocol In Multihoming Transmission Through 5G Network." In 2024 International Visualization, Informatics and Technology Conference (IVIT). IEEE, 2024. http://dx.doi.org/10.1109/ivit62102.2024.10692896.

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Choe, Kiroong, Eunhye Kim, Sangwon Park, and Jinwook Seo. "Fields, Bridges, and Foundations: How Researchers Browse Citation Network Visualizations." In 2024 IEEE Visualization and Visual Analytics (VIS). IEEE, 2024. https://doi.org/10.1109/vis55277.2024.00037.

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Oggier, Frederique, Silivanxay Phetsouvanh, and Anwitaman Datta. "BiVA: Bitcoin Network Visualization & Analysis." In 2018 IEEE International Conference on Data Mining Workshops (ICDMW). IEEE, 2018. http://dx.doi.org/10.1109/icdmw.2018.00210.

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Kang, Seung-hoon, and Juho Kim. "Network Forensic Analysis Using Visualization Effect." In 2008 International Conference on Convergence and Hybrid Information Technology. IEEE, 2008. http://dx.doi.org/10.1109/ichit.2008.165.

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Gino, Henrique L. S., Diogenes S. Pedro, Jean R. Ponciano, Claudio D. G. Linhares, and Agma J. M. Traina. "Exploratory Analysis on Market Basket Data using Network Visualization." In Brazilian Workshop on Social Network Analysis and Mining. Sociedade Brasileira de Computação - SBC, 2023. http://dx.doi.org/10.5753/brasnam.2023.229505.

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Market basket analysis is a powerful technique for understanding customer behavior and optimizing business strategies based on that understanding. Market-based analysis over time using visualization techniques can provide insights into market trends and relations, simplify complex data, and communicate insights effectively, which can help organizations make more informed decisions. This paper leverages a dataset focused on the users’ incomes and temporal aspects of market purchases. We modeled this dataset as three distinct temporal networks and performed an exploratory evaluation identifying

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Wei, Yingmei, and Xiaolei Du. "Two-Layer Network Visualization for Comprehensive Analysis." In 2017 IEEE Second International Conference on Data Science in Cyberspace (DSC). IEEE, 2017. http://dx.doi.org/10.1109/dsc.2017.99.

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Kim, Hoin, Inyong Lee, Jaeik Cho, and Jongsub Moon. "Visualization of network components for attack analysis." In 2009 IEEE Symposium on Computational Intelligence in Cyber Security (CICS). IEEE, 2009. http://dx.doi.org/10.1109/cicybs.2009.4925082.

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Kucher, Kostiantyn, Masoud Fatemi, and Mikko Laitinen. "Towards Visual Sociolinguistic Network Analysis." In 12th International Conference on Information Visualization Theory and Applications. SCITEPRESS - Science and Technology Publications, 2021. http://dx.doi.org/10.5220/0010328202480255.

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Wu, Tongshuang, Yuan Yao, Yuqing Duan, Xinzhi Fan, and Huamin Qu. "NetworkSeer: Visual analysis for social network in MOOCs." In 2016 IEEE Pacific Visualization Symposium (PacificVis). IEEE, 2016. http://dx.doi.org/10.1109/pacificvis.2016.7465269.

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Zhao, Ying, Ralucca Gera, Quinn Halpin, and Jesse Zhou. "Visualization Techniques for Network Analysis and Link Analysis Algorithms." In 11th International Conference on Knowledge Discovery and Information Retrieval. SCITEPRESS - Science and Technology Publications, 2019. http://dx.doi.org/10.5220/0008377805610568.

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Reports on the topic "Network analysis and visualization"

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Bethel, E. Wes. Query-Driven Network Flow Data Analysis and Visualization. Office of Scientific and Technical Information (OSTI), 2006. http://dx.doi.org/10.2172/888963.

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Kahn, Russell L. Attack Analyzer: A Network Analysis and Visualization Tool. Defense Technical Information Center, 2007. http://dx.doi.org/10.21236/ada464353.

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Bethel, E. Wes, Scott Campbell, Eli Dart, et al. Interactive Analysis of Large Network Data Collections UsingQuery-Driven Visualization. Office of Scientific and Technical Information (OSTI), 2005. http://dx.doi.org/10.2172/891627.

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Xu, Ran. Introduction to Social Network Analysis (Free Seminar). Instats Inc., 2024. https://doi.org/10.61700/zud3mrhp34b2l1910.

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This seminar provides an introduction to social network analysis (SNA), equipping researchers in social sciences, population health science, and systems science with essential tools to examine relationships and behaviors in varied contexts, including mHealth and social media. Attendees will gain a practical understanding of the basics of network theory, data analysis, visualization methods, and real-world applications of SNA.

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Etoty, Renee E., Robert F. Erbacher, and Christopher Garneau. Evaluation of the Presentation of Network Data via Visualization Tools for Network Analysts. Defense Technical Information Center, 2014. http://dx.doi.org/10.21236/ada601647.

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Lu, Dengwei, Enjie Tang, Supeng Yin, et al. Intraoperative strategies in identification and functional protection of parathyroid gland for patients with thyroidectomy: A network meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2022. http://dx.doi.org/10.37766/inplasy2022.11.0109.

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Review question / Objective: To assess the roles of intraoperative visualization of parathyroid glands (IVPG) strategies including autofluorescence (AF), indocyanine green (ICG) fluorescence and carbon nanoparticles (CN) in identification and functional protection of parathyroid glands (PGs). Condition being studied: The IVPG strategy is essential for intraoperative identification and functional protection of PGs in patients undergoing thyroid surgery. Recent studies have revealed that autofluorescence (AF), indocyanine green (ICG) fluorescence, and carbon nanoparticles (CN) contribute to redu

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Rehrer, Sarah, Andrew Griffin, and Matthew Renner. Cross country mobility (CCM) modeling using triangulated irregular networks (TIN). Engineer Research and Development Center (U.S.), 2022. http://dx.doi.org/10.21079/11681/46082.

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Cross country mobility (CCM) models terrain that has insufficient or unavailable infrastructure for crossing. This historically has been done with either hand-drawn and estimated maps or with raster-based terrain analysis, both of which have their own strengths and weaknesses. In this report the authors explore the possibility of using triangulated irregular networks (TINs) as a means of representing terrain characteristics used in CCM and discuss the possibilities of using such networks for routing capabilities in lieu of a traditional road-based network. The factors used to calculate CCM are

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Kennedy, Meaghan, Michaela Bonnett, and Teri Garstka. A Model for Technology-Enabled Community Resilience. Orange Sparkle Ball, 2024. http://dx.doi.org/10.61152/plcr9111.

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Introduction Tech-Enabled Community Resilience is an innovative model designed to enhance resilience and optimize impact in complex systems such as communities and ecosystems. The model leverages social network analysis and technology to visualize network dynamics, measure interactions, and implement targeted interventions. Model Structure The approach consists of two key stages: a Startup Phase focused on assembling champions and co-creating a shared vision, and a Steady-state Phase involving iterative measurement and intervention. By utilizing technology platforms for data collection and vis

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Balyk, Nadiia, Yaroslav Vasylenko, Vasyl Oleksiuk, and Galina Shmyger. Designing of Virtual Cloud Labs for the Learning Cisco CyberSecurity Operations Course. [б. в.], 2019. http://dx.doi.org/10.31812/123456789/3177.

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The article is devoted to the study of the problem of the cybersecurity basics teaching. The training of the ICT-specialties students using the course “CCNA Cyber Operations” of the network academy Cisco is considered. At present, many universities have similar academies, while others can open them. On the basis of free software platforms Apache CloudStack and EVE-NG Community authors designed and implemented a virtual cloud laboratory. It operates according to the “IaaS” model. Thanks to the technology of embedded virtualization, the work of many virtual machines, storing of their status, tra

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Neiderer, Andrew M. Network Visualization Using Xj3D. Defense Technical Information Center, 2010. http://dx.doi.org/10.21236/ada532062.

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