Investigating the efficacy of network visualizations for intelligence tasks
There is an increasing requirement for advanced analytical methodologies to help military intelligence analysts cope with the growing amount of data they are saturated with on a daily basis. Specifically, within the context of terror network analysis, one of the largest problems is the transformatio...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
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Institute of Electrical and Electronics Engineers (IEEE)
2013
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| Online Access: | http://hdl.handle.net/1721.1/81776 https://orcid.org/0000-0002-4284-272X |
| _version_ | 1826217908026474496 |
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| author | Berardi, Christopher Walter Solovey, Erin S. Cummings, M. L. |
| author2 | Massachusetts Institute of Technology. Department of Aeronautics and Astronautics |
| author_facet | Massachusetts Institute of Technology. Department of Aeronautics and Astronautics Berardi, Christopher Walter Solovey, Erin S. Cummings, M. L. |
| author_sort | Berardi, Christopher Walter |
| collection | MIT |
| description | There is an increasing requirement for advanced analytical methodologies to help military intelligence analysts cope with the growing amount of data they are saturated with on a daily basis. Specifically, within the context of terror network analysis, one of the largest problems is the transformation of raw tabular data into a visualization that is easily and effectively exploited by intelligence analysts. Currently, the primary method within the intelligence do-main is the node-link visualization, which encodes data sets by depicting the ties between nodes as lines between objects in a plane. This method, although useful, has limitations when the size and complexity of data grows. The matrix offers an alternate perspective because the two dimensions of the matrix are arrayed as an actors x actors matrix. This paper describes an experiment investigating node-link and matrix visualization techniques within social network analysis, and their effectiveness for the intelligence tasks of: 1) identifying leaders and 2) identifying clusters. The sixty participants in the experiment were all Air Force intelligence analysts and we provide recommendations for building visualization tools for this specialized group of users. |
| first_indexed | 2024-09-23T17:10:57Z |
| format | Article |
| id | mit-1721.1/81776 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T17:10:57Z |
| publishDate | 2013 |
| publisher | Institute of Electrical and Electronics Engineers (IEEE) |
| record_format | dspace |
| spelling | mit-1721.1/817762022-09-30T00:13:56Z Investigating the efficacy of network visualizations for intelligence tasks Berardi, Christopher Walter Solovey, Erin S. Cummings, M. L. Massachusetts Institute of Technology. Department of Aeronautics and Astronautics Massachusetts Institute of Technology. Humans and Automation Lab Berardi, Christopher Walter Solovey, Erin S. Cummings, M. L. There is an increasing requirement for advanced analytical methodologies to help military intelligence analysts cope with the growing amount of data they are saturated with on a daily basis. Specifically, within the context of terror network analysis, one of the largest problems is the transformation of raw tabular data into a visualization that is easily and effectively exploited by intelligence analysts. Currently, the primary method within the intelligence do-main is the node-link visualization, which encodes data sets by depicting the ties between nodes as lines between objects in a plane. This method, although useful, has limitations when the size and complexity of data grows. The matrix offers an alternate perspective because the two dimensions of the matrix are arrayed as an actors x actors matrix. This paper describes an experiment investigating node-link and matrix visualization techniques within social network analysis, and their effectiveness for the intelligence tasks of: 1) identifying leaders and 2) identifying clusters. The sixty participants in the experiment were all Air Force intelligence analysts and we provide recommendations for building visualization tools for this specialized group of users. Lincoln Laboratory National Science Foundation (U.S.) (Grant 1136996) 2013-10-25T14:51:50Z 2013-10-25T14:51:50Z 2013-06 Article http://purl.org/eprint/type/ConferencePaper 978-1-4673-6213-9 978-1-4673-6214-6 978-1-4673-6212-2 http://hdl.handle.net/1721.1/81776 Berardi, Christopher W., Erin T. Solovey, and Mary L. Cummings. “Investigating the efficacy of network visualizations for intelligence tasks.” In 2013 IEEE International Conference on Intelligence and Security Informatics, 278-283. Institute of Electrical and Electronics Engineers, 2013. https://orcid.org/0000-0002-4284-272X en_US http://dx.doi.org/10.1109/ISI.2013.6578843 Proceedings of the 2013 IEEE International Conference on Intelligence and Security Informatics Creative Commons Attribution-Noncommercial-Share Alike 3.0 http://creativecommons.org/licenses/by-nc-sa/3.0/ application/pdf Institute of Electrical and Electronics Engineers (IEEE) MIT web domain |
| spellingShingle | Berardi, Christopher Walter Solovey, Erin S. Cummings, M. L. Investigating the efficacy of network visualizations for intelligence tasks |
| title | Investigating the efficacy of network visualizations for intelligence tasks |
| title_full | Investigating the efficacy of network visualizations for intelligence tasks |
| title_fullStr | Investigating the efficacy of network visualizations for intelligence tasks |
| title_full_unstemmed | Investigating the efficacy of network visualizations for intelligence tasks |
| title_short | Investigating the efficacy of network visualizations for intelligence tasks |
| title_sort | investigating the efficacy of network visualizations for intelligence tasks |
| url | http://hdl.handle.net/1721.1/81776 https://orcid.org/0000-0002-4284-272X |
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