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Zarco C, Santos E, Cordón O. Advanced visualization
of Twitter data for its analysis as a communication channel in traditional companies. PROGRESS IN ARTIFICIAL INTELLIGENCE 2019. [DOI: 10.1007/s13748-019-00181-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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N. S, B. A, Bhattacharya S. Social network pruning for building optimal social network: A user perspective. Knowl Based Syst 2017. [DOI: 10.1016/j.knosys.2016.10.020] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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Doboli A, Umbarkar A, Doboli S, Betz J. Modeling semantic knowledge structures for creative problem solving: Studies on expressing concepts, categories, associations, goals and context. Knowl Based Syst 2015. [DOI: 10.1016/j.knosys.2015.01.014] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
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Minguillo D, Thelwall M. Research excellence and university-industry collaboration in UK science parks. RESEARCH EVALUATION 2014. [DOI: 10.1093/reseval/rvu032] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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Pancho D, Alonso J, Magdalena L. Quest for Interpretability-Accuracy Trade-off Supported by Fingrams into the Fuzzy Modeling Tool GUAJE. INT J COMPUT INT SYS 2013. [DOI: 10.1080/18756891.2013.818189] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022] Open
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Cobo M, López-Herrera A, Herrera-Viedma E, Herrera F. SciMAT: A new science mapping analysis software tool. ACTA ACUST UNITED AC 2012. [DOI: 10.1002/asi.22688] [Citation(s) in RCA: 429] [Impact Index Per Article: 35.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Affiliation(s)
- M.J. Cobo
- Department of Computer Science and Artificial Intelligence; CITIC-UGR (Research Center on Information and Communications Technology); University of Granada; E-18071; Granada; Spain
| | - A.G. López-Herrera
- Department of Computer Science and Artificial Intelligence; CITIC-UGR (Research Center on Information and Communications Technology); University of Granada; E-18071; Granada; Spain
| | - E. Herrera-Viedma
- Department of Computer Science and Artificial Intelligence; CITIC-UGR (Research Center on Information and Communications Technology); University of Granada; E-18071; Granada; Spain
| | - F. Herrera
- Department of Computer Science and Artificial Intelligence; CITIC-UGR (Research Center on Information and Communications Technology); University of Granada; E-18071; Granada; Spain
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Zhou F, Mahler S, Toivonen H. Simplification of Networks by Edge Pruning. BISOCIATIVE KNOWLEDGE DISCOVERY 2012. [DOI: 10.1007/978-3-642-31830-6_13] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/04/2022]
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Cobo M, López-Herrera A, Herrera-Viedma E, Herrera F. Science mapping software tools: Review, analysis, and cooperative study among tools. ACTA ACUST UNITED AC 2011. [DOI: 10.1002/asi.21525] [Citation(s) in RCA: 983] [Impact Index Per Article: 75.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
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Quirin A, Cordón O, Vargas-Quesada B, de Moya-Anegón F. Graph-based data mining: A new tool for the analysis and comparison of scientific domains represented as scientograms. J Informetr 2010. [DOI: 10.1016/j.joi.2010.01.004] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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Serrano E, Quirin A, Botia J, Cordón O. Debugging complex software systems by means of pathfinder networks. Inf Sci (N Y) 2010. [DOI: 10.1016/j.ins.2009.11.007] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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Abstract
Social network visualization has drawn significant attention over recent years. It creates images of social networks that provide investigators with new insights about network structures and helps them to communicate those insights to others. Visualization facilitates the social network analysis. It supports the investigators to discover patterns of interactions among the social actors including detecting subgroups, identifying central actors and their roles, and discovering patterns of interactions among social actors. However, visualizing a large heterogeneous social network has several challenges. The large size of networks, complex relations among social actors and limited number of available pixels on a screen make it difficult to present important information clearly to investigators and hence reduce the capability of investigators to explore the networks. In this work, we propose the fractal views to construct a visual abstraction of a large and complex social network with users selected social actors as focuses. The fractal views are focus and context visualization techniques using an information reduction approach. It controls the amount of information displayed by focusing on the syntactic structure of information. It is useful in discovering knowledge from terrorist social networks for combating the war on terrorism. Such application has formed an important research topic, known as intelligence and security informatics, in recent years due to the terrorist attacks of September 11 2001 (9/11) and several other terror attacks that have occurred within the last decade. We present several case studies to demonstrate the capability of the proposed technique on analyzing the Global Salafi Jihad terrorist social network. It extracts the hidden relationships among terrorists through user interactions. In addition, we have conducted a user evaluation to assess the efficiency and effectiveness of fractal views. It shows that fractal views outperform fisheye views and zoom-in windows to support users in visualizing and analyzing terrorist social networks.
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Quirin A, Cordón O, Guerrero-Bote VP, Vargas-Quesada B, Moya-Anegón F. A quick MST-based algorithm to obtain Pathfinder networks (∞,n− 1). ACTA ACUST UNITED AC 2008. [DOI: 10.1002/asi.20904] [Citation(s) in RCA: 28] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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