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Journal articles on the topic 'Social Network Visualization'

Author: Grafiati

Published: 4 June 2021

Last updated: 26 July 2025

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1

Sonderegger, Gabi, C. Oberlack, J.C. Llopis, PH Verburg, and A. Heinimann. "Telecoupling visualizations through a network lens: a systematic review." Ecology and Society 25, no. 4 (2021): 47. https://doi.org/10.5751/ES-11830-250447.

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Telecoupling is an integrative social-ecological framework that has made important contributions to understanding land change processes in a hyperconnected world. Visualizations are a powerful tool to communicate knowledge about telecoupling phenomena. However, little is known about current practices of telecoupling visualization and the challenges involved in visually displaying connections between multiple social-ecological systems. Our research takes stock of existing telecoupling visualizations and provides recommendations for improving current practices. We systematically review 118 visua

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Jason, Leonard A., Sikora AJ, Bobak T, and Wu D. "Visualization of Social Networks in a Recovery Home." Psychology & Psychological Research International Journal 9, no. 3 (2024): 1–4. http://dx.doi.org/10.23880/pprij-16000422.

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This study utilized the SNA and NDTV packages in R to model the social network behaviors of residents within an Oxford House recovery home, where one of the entering residents was on Medication for Opioid Use Disorder (MOUD). The social network dynamics of this person on MOUD over time showed positive transformative connections among residents for friendship, advice-seeking, and lending resources, as well as increases in recovery capital. We provide the script, code, and data to allow for replication and adaptation to other studies involving social networks.

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Gemici, Kurtuluş, and Anthony Vashevko. "Visualizing Hierarchical Social Networks." Socius: Sociological Research for a Dynamic World 4 (January 1, 2018): 237802311877298. http://dx.doi.org/10.1177/2378023118772982.

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The authors propose a novel technique for the visualization of networks that contain a hierarchical structure: networks in which certain nodes and groups of nodes can be classified through a relation of precedence. Networks with a hierarchical structure frequently arise in sociology and various other disciplines, but the existing methods for visualizing such networks leave much to be desired. The method developed in this work builds on the tradition of visualization in social network analysis; it aims to simultaneously represent the positions of different nodes and the relationships between gr

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Mayer, Katja. "Objectifying Social Structures. Network visualization as means of social optimization." Theory and Psychology 22, no. 2 (2012): 162–78. https://doi.org/10.5281/zenodo.49591.

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Social network analysis offers a broad range of formal and interpretative methodologies to deal with social structures, not only by discursive, but also by visual means. Sociograms, depicting social relations as nodes and lines, have played an important part in the reification of social structures since the beginnings of sociometry. This paper brings together two strands of analysis: first, a historical perspective on the development of social network visualization; and, second, exemplary stories of black-boxed technologies that inform not only the depiction, but also the interpretation of soc

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Brandes, Ulrik, Patrick Kenis, and Jörg Raab. "Explanation Through Network Visualization." Methodology 2, no. 1 (2006): 16–23. http://dx.doi.org/10.1027/1614-2241.2.1.16.

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Assessments of configurations, dynamics, and cause and effect are at the heart of our thinking and explanation. Although numerous methods for such assessments have been developed and are being used in daily scientific practice, visualization is usually not considered to be one of them. In this article we first argue that this is due to the common practice of visualizing data rather than the information contained in it; second, we address a number of principles for effective visualization; and third, we assess visualizations generated by the software tool visone in order to explain network outc

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Bingenheimer, M., J. J. Hung, and S. Wiles. "Social network visualization from TEI data." Literary and Linguistic Computing 26, no. 3 (2011): 271–78. http://dx.doi.org/10.1093/llc/fqr020.

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Xiang, Zhang. "Visual Dynamic Simulation Model of Unstructured Data in Social Networks." Security and Communication Networks 2022 (January 13, 2022): 1–10. http://dx.doi.org/10.1155/2022/9095330.

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Social networks contain a large amount of unstructured data. To ensure the stability of unstructured big data, this study proposes a method for visual dynamic simulation model of unstructured data in social networks. This study uses the Hadoop platform and data visualization technology to establish a univariate linear regression model according to the time correlation between data, estimates and approximates perceptual data, and collects unstructured data of social networks. Then, the unstructured data collected from the original social network are processed, and an adaptive threshold is desig

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Lestari, Diana Wahyu, and Rita Ambarwati. "Social Network Analysis: Understanding User Behavior in Threads." Kontigensi : Jurnal Ilmiah Manajemen 12, no. 1 (2024): 115–24. http://dx.doi.org/10.56457/jimk.v12i1.505.

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The presence of threads has enhanced users' ability to share stories, information and views in greater detail and effectively in the online world. Social media platforms allow users to interact, share content, and connect online. Therefore, the purpose of this research is to create a Social Network Analysis (SNA) network visualization and categorize the data to contribute to the understanding of user interaction on this platform. The research method in this study is the Social Network Analysis (SNA) approach to analyze the relationship between individuals in social networks. The results show t

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Akula, Ramya, and Ivan Garibay. "VizTract: Visualization of Complex Social Networks for Easy User Perception." Big Data and Cognitive Computing 3, no. 1 (2019): 17. http://dx.doi.org/10.3390/bdcc3010017.

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Social networking platforms connect people from all around the world. Because of their user-friendliness and easy accessibility, their traffic is increasing drastically. Such active participation has caught the attention of many research groups that are focusing on understanding human behavior to study the dynamics of these social networks. Oftentimes, perceiving these networks is hard, mainly due to either the large size of the data involved or the ineffective use of visualization strategies. This work introduces VizTract to ease the visual perception of complex social networks. VizTract is a

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Brandes, Ulrik. "Social network analysis and visualization [Applications Corner]." IEEE Signal Processing Magazine 25, no. 6 (2008): 147–51. http://dx.doi.org/10.1109/msp.2008.929814.

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Song, Meesun, Wonkyu Lee, and Junghwan Kim. "Extraction and Visualization of Implicit Social Relations on Social Networking Services." Proceedings of the AAAI Conference on Artificial Intelligence 24, no. 1 (2010): 1425–30. http://dx.doi.org/10.1609/aaai.v24i1.7513.

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Today social network services like blogs, communities, and social networking sites dominate the web. As Web 2.0 has evolved this way, analyzing social networks has become a promising research issue. There have already been several researches on social network analysis based on users' activities in social services. Most of them focus on the links among the users such as citation, trackback, and comment. However, few studies have analyzed the relations within message threads. In general, they considered the one-way relationship from a comment writer to a post writer. Since users communicate with

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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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Armitage, Neil. "The Biographical Network Method." Sociological Research Online 21, no. 2 (2016): 165–79. http://dx.doi.org/10.5153/sro.3827.

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This article introduces a network visualization method that enables a thorough analysis of the link between life history and social networks. Network visualizations are generally static, and as such they tend to disguise rather than uncover change and continuity within networks, and the influence that certain events may have on someone's sociability. The Biographical Network (BN) is a mixed method approach combining life story interviews with formal SNA that attempts to overcome the consequences of this lack of dynamism in network visualizations. In the first part of the article the underpinni

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McCarty, Christopher, José Luis Molina, Claudia Aguilar, and Laura Rota. "A Comparison of Social Network Mapping and Personal Network Visualization." Field Methods 19, no. 2 (2007): 145–62. http://dx.doi.org/10.1177/1525822x06298592.

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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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Zolkepli, Maslina, Fangyan Dong, and Kaoru Hirota. "Visualizing Fuzzy Relationship in Bibliographic Big Data Using Hybrid Approach Combining Fuzzyc-Means and Newman-Girvan Algorithm." Journal of Advanced Computational Intelligence and Intelligent Informatics 18, no. 6 (2014): 896–907. http://dx.doi.org/10.20965/jaciii.2014.p0896.

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Bibliographic big data visualization method is proposed by incorporating a combination of fuzzyc-means clustering and the Newman-Girvan clustering algorithm, where clustered results are displayed in a network view by grouping objects with similar cluster memberships. As current bibliographic visualizations focus on the crisp relationship among data, fuzzy analysis and visualization may offer insights to bibliographic big data, enabling faster decision making by improving displayed information precision. The proposed method is applied to the DBLP citation network dataset. Results show that merg

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Wang, Eric Ke, and Futai Zou. "A New Graph Drawing Scheme for Social Network." Scientific World Journal 2014 (2014): 1–9. http://dx.doi.org/10.1155/2014/930314.

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With the development of social networks, people have started to use social network tools to record their life and work more and more frequently. How to analyze social networks to explore potential characteristics and trend of social events has been a hot research topic. In order to analyze it effectively, a kind of techniques called information visualization is employed to extract the potential information from the large scale of social network data and present the information briefly as visualized graphs. In the process of information visualization, graph drawing is a crucial part. In this pa

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Wibisono, Eristian. "Discovering Key Actors and Opinion Leaders on Twitter’s Start-Up and Entrepreneurship Topics Trending: A Social Network Analysis Approach." JURNAL IPTEKKOM Jurnal Ilmu Pengetahuan & Teknologi Informasi 25, no. 1 (2023): 37–56. http://dx.doi.org/10.17933/iptekkom.25.1.2023.37-56.

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The topic of start-ups and entrepreneurship has been widely discussed on social media to disseminate information while serving as a digital marketing platform. Unfortunately, researchers and practitioners interested in analyzing social networks to gain business advantage through digital platforms still need to be expanded. This paper analyzes networks on social media to find important actors and opinion leaders on trending start-up and entrepreneurship topics. Data analytics is performed using one of the most extensive social media, Twitter. Several visualizations of the social network of thes

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Mayer, Katja. "Objectifying social structures: Network visualization as means of social optimization." Theory & Psychology 22, no. 2 (2012): 162–78. http://dx.doi.org/10.1177/0959354311427488.

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Soja, Rani S*1 &. Tinu N. S. 2. "SOCIAL NETWORK ANALYSIS – SURVEY ON DATA COLLECTION METHODS, DATA FORMATS AND ANALYSIS TOOLS." GLOBAL JOURNAL OF ENGINEERING SCIENCE AND RESEARCHES 5, no. 7 (2018): 34–40. https://doi.org/10.5281/zenodo.1305005.

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Now days, social network analysis has a great theoretical and practical significance. It is an interdisciplinary subject which spreads over various areas such as, social psychology, anthropology, economics, demography, communication studies, geography, biology, history, sociolinguistics, information science, organizational studies, political science, development studies, and computer science. The popular online social networks like Twitter, Facebook, etc hold big amounts of data about the people and their likes, dislikes, behaviors, relations etc. Graph based mining tools are required to analy

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Chandel,, Aditya. "Real-time Graph Visualization with JavaFX: Exploring Large-scale Network Structures." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 04 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem31221.

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The ability to visualize and comprehend complex network structures is crucial in various domains, including social media analysis, computer networks, and transportation systems. However, visualizing large-scale graphs poses significant challenges due to computational limitations and rendering performance constraints. This research paper presents a novel approach to real-time graph visualization using JavaFX, a powerful Java-based framework for developing rich client applications. By leveraging efficient data structures, rendering optimizations, and multithreading techniques, our proposed syste

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Andriotis, Panagiotis, Zacharias Tzermias, Anthi Mparmpaki, Sotiris Ioannidis, and George Oikonomou. "Multilevel Visualization Using Enhanced Social Network Analysis with Smartphone Data." International Journal of Digital Crime and Forensics 5, no. 4 (2013): 34–54. http://dx.doi.org/10.4018/ijdcf.2013100103.

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While technology matures and becomes more productive, mobile devices can be affordable and, consequently, fully integrated in people's lives. After their unexpected bloom and acceptance, Online Social Networks are now sources of valuable information. The authors therefore use them for tasks varying from direct marketing to forensic analysis. The authors have already seen Social Network Forensics techniques focused on particular networks implementing methods that collect data from user accounts. During the forensic analysis it is common to aggregate information from different sources but, usual

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Shepherd, Patrick, Isaac Batts, Judy Goldsmith, Emory Hufbauer, Mia Weaver, and Angela Zhang. "Software for Agent-based Network Simulation and Visualization." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 18 (2021): 16103–5. http://dx.doi.org/10.1609/aaai.v35i18.18025.

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We present a network software suite that can model contagions or opinion manipulation in social networks, that combines features from the standard packages and extends them to allow complex, interacting, dynamic topologies, and dynamic heterogeneous agent types, with individual interaction policies. The framework allows for the easy implementation of new agent types, and provides flexible visualization tools to elucidate network behavior over time.

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Ren, Donghao, Laura R. Marusich, John O’Donovan, et al. "Understanding node-link and matrix visualizations of networks: A large-scale online experiment." Network Science 7, no. 2 (2019): 242–64. http://dx.doi.org/10.1017/nws.2019.6.

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AbstractWe investigated human understanding of different network visualizations in a large-scale online experiment. Three types of network visualizations were examined: node-link and two different sorting variants of matrix representations on a representative social network of either 20 or 50 nodes. Understanding of the network was quantified using task time and accuracy metrics on questions that were derived from an established task taxonomy. The sample size in our experiment was more than an order of magnitude larger (N = 600) than in previous research, leading to high statistical power and

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Muharam, Riki Satia, Budiman Rusli, Heru Nurasa, and Entang Adhy Muhtar. "Seven clusters of data visualization articles in Scopus using social network analysis." International Journal of Data and Network Science 7, no. 3 (2023): 1333–40. http://dx.doi.org/10.5267/j.ijdns.2023.4.005.

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The aim of this study was to analyse the bibliographic characteristics and content of articles on Data Visualization published in journals indexed by Scopus written by researchers from throughout the world. We conducted a bibliometric and content analysis of publication in the Scopus database. We only retrieved articles written in English. We conducted content analysis using the VOSviewer software and visualized the co-occurrence of keywords and bibliographic coupling of sources and countries. Following the study protocol, we found 862 articles on Data Visualization over the past 30 years. The

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Ballestar, María Teresa, Miguel Cuerdo-Mir, and María Teresa Freire-Rubio. "The Concept of Sustainability on Social Media: A Social Listening Approach." Sustainability 12, no. 5 (2020): 2122. http://dx.doi.org/10.3390/su12052122.

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The concept of sustainability has gone far beyond the issues of the sustainable management of natural and environmental resources. Nowadays, sustainability is part of the social sciences in a different way. The aim of this research was dual. Firstly, we analyzed the different contexts and areas of knowledge where this concept is used in society by using social listening on Twitter, one of the most popular social networks today. The sentiments of these conversations were rated to assess whether the feelings and perceptions of these conversations on the social network were positive or negative r

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Umapathy, Kumaran, and Neelu Khare. "An Efficient & Secure Content Contribution and Retrieval content in Online Social Networks using Level-level Security Optimization & Content Visualization Algorithm." Indonesian Journal of Electrical Engineering and Computer Science 10, no. 2 (2018): 807. http://dx.doi.org/10.11591/ijeecs.v10.i2.pp807-816.

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<span lang="EN-US">Online Social Networks (OSNs) is currently popular interactive media to establish the communication, share and disseminate a considerable amount of human life data. Daily and continuous communications imply the exchange of several types of content, including free text, image, audio, and video data. Security is one of the friction points that emerge when communications get mediated in Online Social Networks (OSNs). However, there are no content-based preferences supported, and therefore it is not possible to prevent undesired messages. Providing the service is not only

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Kumaran, Umapathy, and Khare Neelu. "An Efficient & Secure Content Contribution and Retrieval Content in Online Social Networks Using Level-level Security Optimization & Content Visualization Algorithm." Indonesian Journal of Electrical Engineering and Computer Science 10, no. 2 (2018): 807–16. https://doi.org/10.11591/ijeecs.v10.i2.pp807-816.

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Online Social Networks (OSNs) is currently popular interactive media to establish the communication, share and disseminate a considerable amount of human life data. Daily and continuous communications imply the exchange of several types of content, including free text, image, audio, and video data. Security is one of the friction points that emerge when communications get mediated in Online Social Networks (OSNs). However, there are no contentbased preferences supported, and therefore it is not possible to prevent undesired messages. Providing the service is not only a matter of using previous

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Baytur, Buşra, and Eren Özceylan. "Identifying influential individuals in social networks: An example of a location-based online social network." Journal of Turkish Operations Management 8, no. 2 (2024): 397–408. https://doi.org/10.56554/jtom.1475874.

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The landscape of information access has evolved significantly over time, with the advent of search engines, social media platforms, and the widespread use of the internet. These developments have fostered a global communication network, resulting in intricate connections between individuals. Online social networks have emerged as key facilitators of social interaction, expediting the exchange of information and playing a pivotal role in content dissemination. Within these networks, certain individuals, termed as Key Players, wield considerable influence, profoundly impacting information diffus

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Allegri, Stephen A., Kevin McCoy, and Cassie S. Mitchell. "CompositeView: A Network-Based Visualization Tool." Big Data and Cognitive Computing 6, no. 2 (2022): 66. http://dx.doi.org/10.3390/bdcc6020066.

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Large networks are quintessential to bioinformatics, knowledge graphs, social network analysis, and graph-based learning. CompositeView is a Python-based open-source application that improves interactive complex network visualization and extraction of actionable insight. CompositeView utilizes specifically formatted input data to calculate composite scores and display them using the Cytoscape component of Dash. Composite scores are defined representations of smaller sets of conceptually similar data that, when combined, generate a single score to reduce information overload. Visualized interac

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Brandes, Ulrik, and Christian Pich. "Explorative Visualization of Citation Patterns in Social Network Research." Journal of Social Structure 12, no. 1 (2020): 1–19. http://dx.doi.org/10.21307/joss-2019-037.

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Jia, Yuntao, Michael Garland, and John C. Hart. "Social Network Clustering and Visualization using Hierarchical Edge Bundles." Computer Graphics Forum 30, no. 8 (2011): 2314–27. http://dx.doi.org/10.1111/j.1467-8659.2011.02037.x.

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Du, Xiaolin, Yunming Ye, Yueping Li, and Ge Song. "A Fast Multi-level Layout for Social Network Visualization." International Journal of Multimedia and Ubiquitous Engineering 9, no. 12 (2014): 167–80. http://dx.doi.org/10.14257/ijmue.2014.9.12.16.

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Verspoor, Karin, Bahadorreza Ofoghi, and Marlene Robles Granda. "CommViz: Visualization of semantic patterns in large social communication networks." Information Visualization 17, no. 1 (2017): 66–88. http://dx.doi.org/10.1177/1473871617693039.

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We introduce CommViz, an information visualization tool that enables complex communication networks to be explored, exposing trends and patterns in the data at a glance. We adapt a visualization approach known as hive plots to reflect the semantic structure of the networks, a generalization we call semantic hive plots. The method efficiently organizes and provides insight into complex, high-dimensional communication data such as email and messages on social media. We present the architecture of the CommViz tool and its application to the Enron email corpus as a case study, demonstrating how th

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Luckhardt, Courtney. "Visualizing the Social Networks of Early Medieval Pilgrims." Medieval People: Social Bonds, Kinship, and Networks 36, no. 1 (2022): 263–80. http://dx.doi.org/10.32773/pcrc5208.

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Digital Humanities as a subfield is best understood as a collection of methods, and within that methodology, network analysis and visualization are important tools to conceptualize relationships and the transmission of ideas in historical communities. For medievalists with fragmentary evidence, social network analysis can reveal outlines of networks long vanished. Social network analysis enables medievalists to visualize both people and the social structures and networks they are embedded within. The case study of the social networks of sixth-century pilgrims to Jerusalem in Gregory of Tours’

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Kim, Aryuna. "Qualitative social network analysis in practice: comparison of methods for network maps construction." Sociology: methodology, methods, mathematical modeling (Sociology: 4M) 29, no. 56 (2024): 113–42. http://dx.doi.org/10.19181/4m.2023.32.1.3.

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This article is devoted to the application of qualitative network analysis on the example of studying the social interactions of young parents in migration. A conceptual description of qualitative network analysis, network visualization features, design of qualitative network research, comparison of two approaches to building network maps and an example of their analysis are presented. Qualitative network analysis is aimed at studying relationships in the network and consists of interpretative and structural components, which are implemented through interviews and building a network map. The t

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Widiastiana Vista Wijaya, Citra Puspa Maulidina, Shilvy Andini Sunarto, and Siti Zulzilah. "ANALISIS BIBLIOMETRIK TERHADAP TREND RISET “HALAL TOURISM” MENGGUNAKAN VOSVIEWER." Jurnal Sosial Humaniora dan Pendidikan 2, no. 3 (2023): 127–38. http://dx.doi.org/10.56127/jushpen.v2i3.1168.

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The aim of bibliometric analysis is mapping research trends by processing metadata from Google Scholar. This research also wants to know the research trend on "Halal Tourism" which uses the Social Network Analysis method. Research through searching the Google Scholar database with the keywords "Halal Tourism". Retrieval of metadata using the Publish or Perish (POP) application. The resulting data from PoP is then analyzed descriptively based on the year the publication was published, publisher name, researcher productivity and journal ranking. To obtain an accurate research development map, Po

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Haider, Johanna Doppler, Patrick Seidler, Margit Pohl, Neesha Kodagoda, Rick Adderley, and B. L. William Wong. "How Analysts Think: Sense-making Strategies in the Analysis of Temporal Evolution and Criminal Network Structures and Activities." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 61, no. 1 (2017): 193–97. http://dx.doi.org/10.1177/1541931213601532.

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Analysis of criminal activity based on offenders’ social networks is an established procedure in intelligence analysis. The complexity of the data poses an obstacle for analysts to gauge network developments, e.g. detect emerging problems. Visualization is a powerful tool to achieve this, but it is essential to know how the analysts’ sense-making strategies can be supported most efficiently. Based on a think aloud study we identified ten cognitive strategies on a general level to be useful for designers. We also provide some examples how these strategies can be supported through appropriate vi

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Apostolato, Ioana-Alexandra. "An overview of Software Applications for Social Network Analysis." International Review of Social Research 3, no. 3 (2013): 71–77. http://dx.doi.org/10.1515/irsr-2013-0023.

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Abstract There is a great variety of software tools that has been developed within the last 20 years, as to facilitate and support the qualitative and quantitative analysis of social networks. This paper gives a brief overview of some of the most popular software packages for social network analysis: Pajek, UCINET 6, NetDraw, Gephi, E-Net, KeyPlayer 1, StOCNET and Automap. Pajek has efficient algorithms for the analysis of large networks, while UCINET 6 includes multiple analytical tools highly efficient for exploring and measuring social network structures. NetDraw, nested in UCINET 6, and Ge

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Roth, Adam R. "Social Network Theory and Comedy: Insights from NBC’s The Office." Socius: Sociological Research for a Dynamic World 8 (January 2022): 237802312211415. http://dx.doi.org/10.1177/23780231221141524.

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Television sitcoms frequently invoke social network concepts to highlight specific jokes or scenes. In this visualization, the author draws on data from NBC’s The Office to explore how show creator Greg Daniels and his writing staff leveraged a well-known social network concept in the overall development of their show. By identifying the presence of structural holes (i.e., the absence of ties between two or more network members), The Office produced multiple novel storylines in which different sets of characters who did not routinely interact were jointly forced into comedic situations. As evi

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Klamma, Ralf. "Emerging Research Topics in Social Learning." Proceedings of the International Conference on Networked Learning 7 (May 3, 2010): 224–31. http://dx.doi.org/10.54337/nlc.v7.9177.

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Despite the fact, that an uncountable crowd of technology affine learners has entered the Internet with fast connections lines, little support exists for scalable learning support technologies. In this paper, we explore research topics which address the new needs of long tail learning and technologies which may help to overcome the current situation. Especially, we investigated the concepts of connectivism. Key theorists state that (a) learning is a process of connecting entities, (b) nurturing and maintaining connections is needed to continual learning, (c) learners need the ability to see co

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Kim, Min-Soo, and Min-Koo Kim. "Developing Protégé Plug-in: OWL Ontology Visualization using Social Network." Journal of Information Processing Systems 4, no. 2 (2008): 61–66. http://dx.doi.org/10.3745/jips.2008.4.2.061.

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Park, Sun, Yong-Il Kim, and Seong Ro Lee. "Hierarchical Visualization of Cloud-Based Social Network Service Using Fuzzy." Journal of Korea Information and Communications Society 38B, no. 7 (2013): 501–11. http://dx.doi.org/10.7840/kics.2013.38b.7.501.

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Stepaniuk, Krzysztof. "Visualization of expressing culinary experience in social network, memetic approach." Entrepreneurship and Sustainability Issues 5, no. 3 (2018): 693–702. http://dx.doi.org/10.9770/jesi.2018.5.3(21).

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Campos Filho, Amadeu S., Magdala A. Novaes, and Alex S. Gomes. "A 3D visualization framework to social network monitoring and analysis." Computers in Human Behavior 49 (August 2015): 623–34. http://dx.doi.org/10.1016/j.chb.2015.03.053.

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Mussiraliyeva, Sh Zh, G. B. Baispay, and A. K. Beketova. "Research and creation ofamethod for identifying influential spreaders of criminal information in a social network." Bulletin of the National Engineering Academy of the Republic of Kazakhstan 86, no. 4 (2022): 82–90. http://dx.doi.org/10.47533/2020.1606-146x.198.

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The article provides for the development of algorithms and software for graphical visualization of the interconnection of criminal information networks. The use of various social network analysis techniques to identify key and influential spreaders in an online community has been explored. During the analysis of the graph, an analysis of various metrics of social network analysis methods was carried out and a comparison was made of the effectiveness of the method with ready-made data.

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Golędzinowski, Wojciech, and Władysław Błocki. "SOCIAL NETWORK ANALYSIS: FROM GRAPH THEORY TO APPLICATIONS." Social Communication 24, no. 1 (2024): 151–64. https://doi.org/10.57656/sc-2023-0012.

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Social Network Analysis (SNA) is a powerful interdisciplinary field that explores the patterns and dynamics of relationships between individuals, groups, organizations, and even entire societies. This article provides an overview of SNA, tracing its roots in graph theory and highlighting its various applications in fields such as sociology, computer science, business, and epidemiology. By examining the theoretical foundations of SNA and its practical implementations, this article aims to demonstrate the importance of SNA in understanding social structures, information diffusion, impact dynamic

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Vahed, Nafiseh, Vahideh Zarea Gavgani, Rashid Jafarzadeh, Ziba Tusi, and Mohammadamin Erfanmanesh. "Visualization of the Scholarly Output on Evidence Based Librarianship: A Social Network Analysis." Evidence Based Library and Information Practice 13, no. 4 (2018): 50–69. http://dx.doi.org/10.18438/eblip29396.

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Abstract Objective – This paper aimed to analyze worldwide research on evidence based librarianship (EBL) using Social Network Analysis (SNA). Methods – This descriptive study has been conducted using scientometrics and a SNA approach. The researchers identified 523 publications on EBL, as indexed by Scopus and Web of Science with no date limitation. A range of software tools (Ravar PreMap, Netdraw, UCINet and VOSviewer) were utilized for data visualization and analysis. Results – Results of the study revealed that the United Kingdom (UK) and the United States (US) occupied t

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Widya, Paramitha Puspa, Rita Ambarwati, Dedy Dedy, and Mashhura Toirхonovna Alimova. "Leveraging Social Network Analysis for Enhancing Safety Reporting in the Workplace." Jurnal Teknik Industri 26, no. 1 (2024): 9–24. http://dx.doi.org/10.9744/jti.26.1.9-24.

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Unsafe Condition Reporting is an important source of information for companies to determine whether the reporting can be identified effectively as the key to reducing work accidents. This research aims to ascertain the Social Network Analysis visualization network in the context of reporting unsafe conditions in the IZAT application and categorizing data processing outcomes. The findings revealed that the data collection process yielded 26,658 data items. The Unsafe Condition content comprised 79,667 words, with 2,388 unique words identified. The average number of occurrences per word was 33.3

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Yamini, T., P. Venkatesan, V. Jyothi, M. R. Devy, V. S. Rao, and K. Suseela. "Social network analysis approach to identify agricultural key communicators." Journal of Environmental Biology 45, no. 6 (2024): 788–97. http://dx.doi.org/10.22438/jeb/45/6/mrn-5366.

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Aim: This paper employed Social Network Analysis approach to visualize and calculate different social network metrics. It identifies key communicators who play pivotal roles in information flow. Methodology: Research was conducted at Jammulapalem and Perali villages of Bapatla district, Andhra Pradesh, India, during 2022-23 using an exploratory research design. A total of 120 farmers Eigen vector were selected using simple random technique, and data was collected using a well-developed interview schedule. Network metrics such as Degree centrality, betweenness centrality, and eigen vector centr

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