Human-Computer Interaction (HCI) research is quite interdisciplinary in nature and is valuable to readers from many fields. Unlike many academic fields the premier conferences in HCI are highly selective and archived. Moreover, these conferences exceed many HCI journals in selectivity and impact.
| Peer-Reviewed Journal Papers |
|---|
| Dunne, C., Shneiderman, B., Gove, R., Klavans, J. & Dorr, B. (2012), "Rapid understanding of scientific paper collections: integrating statistics, text analytics, and visualization", JASIST: Journal of the American Society for Information Science and Technology. |
| Abstract: Keeping up with rapidly growing research fields, especially when there are multiple interdisciplinary sources, requires substantial effort for researchers, program managers, or venture capital investors. Current theories and tools are directed at finding a paper or website, not gaining an understanding of the key papers, authors, controversies, and hypotheses. This report presents an effort to integrate statistics, text analysis, and visualization in a multiple coordinated window environment that supports exploration. Our prototype system, Action Science Explorer (ASE), provides an environment for demonstrating principles of coordination and conducting iterative usability tests of them with interested and knowledgeable users. We developed an understanding of the value of reference management, statistics, citation context extraction, natural language summarization for single and multiple documents, filters to interactively select key papers, and network visualization to see citation patterns and identify clusters. The three-phase usability study guided our revisions to ASE and led us to improve the testing methods. |
BibTeX:
@article{Dunne12Rapidunderstandingscientific,
author = {Cody Dunne and Ben Shneiderman and Robert Gove and Judith Klavans and Bonnie Dorr},
title = {Rapid understanding of scientific paper collections: integrating statistics, text analytics, and visualization},
journal = {JASIST: Journal of the American Society for Information Science and Technology},
year = {2012},
url = {http://www.cs.umd.edu/localphp/hcil/tech-reports-search.php?number=2011-16}
}
|
| Shneiderman, B., Dunne, C., Sharma, P. & Wang, P. (2011), "Innovation trajectories for information visualizations: Comparing treemaps, cone trees, and hyperbolic trees", Information Visualization. |
| Abstract: This paper reviews the trajectory of three information visualization innovations: treemaps, cone trees, and hyperbolic trees. These three ideas were first published around the same time in the early 1990s, so we are able to track academic publications, patents, and trade press articles over almost two decades. We describe the early history of each approach, problems with data collection from differing sources, appropriate metrics, and strategies for visualizing these longitudinal data sets. This paper makes two contributions: (1) it offers the information visualization community a history of how certain ideas evolved, influenced others, and were adopted for widespread use and (2) it provides an example of how such scientometric trajectories of innovations can be gathered and visualized. Guidance for designers is offered, but these conjectures may also be useful to researchers, research managers, science policy analysts, and venture capitalists. |
BibTeX:
@article{Shneiderman11Innovationtrajectoriesinformation,
author = {Ben Shneiderman and Cody Dunne and Puneet Sharma and Ping Wang},
title = {Innovation trajectories for information visualizations: Comparing treemaps, cone trees, and hyperbolic trees},
journal = {Information Visualization},
year = {2011},
url = {http://www.cs.umd.edu/localphp/hcil/tech-reports-search.php?number=2010-16}
}
|
| Peer-Reviewed Conference/Workshop Papers |
| Dunne, C., Riche, N.H., Lee, B., Metoyer, R.A. & Robertson, G.G. (2012), "GraphTrail: analyzing large multivariate and heterogeneous networks while supporting exploration history", In CHI '12: Proc. 2012 international conference on Human factors in computing systems. [Acceptance Rate: 23.5% (370/1577)] |
| Abstract: Exploring large network datasets, such as scientific collaboration networks, is challenging because they often contain a large number of nodes and edges in several types and with multiple attributes. Analyses of such networks are often long and complex, and may require several sessions by multiple users. Therefore, it is often difficult for users to recall their own exploration history or share it with others. We introduce GraphTrail, an interactive visualization for analyzing networks through exploration of node and edge aggregates that captures users’ interactions and integrates this history directly in the exploration workspace. To facilitate large network analysis, GraphTrail integrates aggregation with familiar charts, drag-and-drop interaction on a canvas, and a novel pivoting mechanism for transitioning between aggregates. Through a three-month field study with a team of archeologists and a qualitative lab study with ten users, we demonstrate the effectiveness of our design and the benefits of integrated exploration history, including analysis comprehension, insight discovery, and exploration recall. |
BibTeX:
@inproceedings{Dunne12GraphTrail_analyzinglarge,
author = {Cody Dunne and Nathalie~Henry Riche and Bongshin Lee and Ronald~A. Metoyer and George~G. Robertson},
title = {GraphTrail: analyzing large multivariate and heterogeneous networks while supporting exploration history},
booktitle = {CHI '12: Proc. 2012 international conference on Human factors in computing systems},
year = {2012}
}
|
| Gove, R., Gramsky, N., Kirby, R., Sefer, E., Sopan, A., Dunne, C., Shneiderman, B. & Taieb-Maimon, M. (2011), "NetVisia: heat map & matrix visualization of dynamic social network statistics & content", In SocialCom '11: Proc. 2011 IEEE 3rd International Conference on Social Computing., pp. 19-26. |
| Abstract: Visualizations of static networks in the form of node-link diagrams have evolved rapidly, though researchers are still grappling with how best to show evolution of nodes over time in these diagrams. This paper introduces NetVisia, a social network visualization system designed to support users in exploring temporal evolution in networks by using heat maps to display node attribute changes over time. NetVisia's novel contributions to network visualizations are to (1) cluster nodes in the heat map by similar metric values instead of by topological similarity, and (2) align nodes in the heat map by events. We compare NetVisia to existing systems and describe a formative user evaluation of a NetVisia prototype with four participants that emphasized the need for tooltips and coordinated views. Despite the presence of some usability issues, in 30-40 minutes the user evaluation participants discovered new insights about the data set which had not been discovered using other systems. We discuss implemented improvements to NetVisia, and analyze a co-occurrence network of 228 business intelligence concepts and entities. This analysis confirms the utility of a clustered heat map to discover outlier nodes and time periods. |
BibTeX:
@inproceedings{Gove11NetVisia_HeatMap,
author = {Robert Gove and Nick Gramsky and Rose Kirby and Emre Sefer and Awalin Sopan and Cody Dunne and Ben Shneiderman and Meirav Taieb-Maimon},
title = {NetVisia: heat map & matrix visualization of dynamic social network statistics & content},
booktitle = {SocialCom '11: Proc. 2011 IEEE 3rd International Conference on Social Computing},
year = {2011},
pages = {19--26},
url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6113090},
doi = {http://dx.doi.org/10.1109/PASSAT/SocialCom.2011.216}
}
|
| Gove, R., Dunne, C., Shneiderman, B., Klavans, J. & Dorr, B. (2011), "Evaluating visual and statistical exploration of scientific literature networks", In VL/HCC '11: Proc. 2011 IEEE Symposium on Visual Languages and Human-Centric Computing., pp. 217-224.
[Abstract] [BibTeX] [DOI] [URL] [PDF] [PowerPoint] [Homepage] [Demo] |
| Abstract: Action Science Explorer (ASE) is a tool designed to support users in rapidly generating readily consumable summaries of academic literature. It uses citation network visualization, ranking and filtering papers by network statistics, and automatic clustering and summarization techniques. We describe how early formative evaluations of ASE led to a mature system evaluation, consisting of an in-depth empirical evaluation with four domain experts. The evaluation tasks were of two types: predefined tasks to test system performance in common scenarios, and user-defined tasks to test the system's usefulness for custom exploration goals. The primary contribution of this paper is a validation of the ASE design and recommendations to provide: easy-to-understand metrics for ranking and filtering documents, user control over which document sets to explore, and overviews of the document set in coordinated views along with details-on-demand of specific papers. We contribute a taxonomy of features for literature search and exploration tools and describe exploration goals identified by our participants. |
BibTeX:
@inproceedings{Gove11Evaluatingvisualand,
author = {Robert Gove and Cody Dunne and Ben Shneiderman and Judith Klavans and Bonnie Dorr},
title = {Evaluating visual and statistical exploration of scientific literature networks},
booktitle = {VL/HCC '11: Proc. 2011 IEEE Symposium on Visual Languages and Human-Centric Computing},
year = {2011},
pages = {217--224},
url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6070403},
doi = {http://dx.doi.org/10.1109/VLHCC.2011.6070403}
}
|
| Mohammad, S., Dunne, C. & Dorr, B. (2009), "Generating high-coverage semantic orientation lexicons from overtly marked words and a thesaurus", In EMNLP '09: Proc. 2009 conference on Empirical Methods in Natural Language Processing. Morristown, NJ, USA. August 2009., pp. 599-608. Association for Computational Linguistics. |
| Abstract: Sentiment analysis often relies on a semantic orientation lexicon of positive and negative words. A number of approaches have been proposed for creating such lexicons, but they tend to be computationally expensive, and usually rely on significant manual annotation and large corpora. Most of these methods use WordNet. In contrast, we propose a simple approach to generate a high-coverage semantic orientation lexicon, which includes both individual words and multi-word expressions, using only a Roget-like thesaurus and a handful of affixes. Further, the lexicon has properties that support the Polyanna Hypothesis. Using the General Inquirer as gold standard, we show that our lexicon has 14 percentage points more correct entries than the leading WordNet-based high-coverage lexicon (SentiWordNet). In an extrinsic evaluation, we obtain significantly higher performance in determining phrase polarity using our thesaurus-based lexicon than with any other. Additionally, we explore the use of visualization techniques to gain insight into the our algorithm beyond the evaluations mentioned above. |
BibTeX:
@inproceedings{Mohammad09Generatinghigh-coveragesemantic,
author = {Saif Mohammad and Cody Dunne and Bonnie Dorr},
title = {Generating high-coverage semantic orientation lexicons from overtly marked words and a thesaurus},
booktitle = {EMNLP '09: Proc. 2009 conference on Empirical Methods in Natural Language Processing},
publisher = {Association for Computational Linguistics},
year = {2009},
pages = {599-608},
url = {http://portal.acm.org/citation.cfm?id=1699571.1699591}
}
|
| Bonsignore, E.M., Dunne, C., Rotman, D., Smith, M., Capone, T., Hansen, D.L. & Shneiderman, B. (2009), "First steps to NetViz Nirvana: Evaluating social network analysis with NodeXL", In CSE '09: Proc. 2009 international conference on computational science and engineering. Volume 4, pp. 332-339. IEEE Computer Society Press. [Acceptance Rate: 20.0% (40/204)]
[Abstract] [BibTeX] [DOI] [URL] [PDF] [PowerPoint] [Homepage] [Demo 1] [Demo 2] |
| Abstract: Social Network Analysis (SNA) has evolved as a popular, standard method for modeling meaningful, often hidden structural relationships in communities. Existing SNA tools often involve extensive pre-processing or intensive programming skills that can challenge practitioners and students alike. NodeXL, an open-source template for Microsoft Excel, integrates a library of common network metrics and graph layout algorithms within the familiar spreadsheet format, offering a potentially low-barrier-to-entry framework for teaching and learning SNA. We present the preliminary findings of 2 user studies of 21 graduate students who engaged in SNA using NodeXL. The majority of students, while information professionals, had little technical background or experience with SNA techniques. Six of the participants had more technical backgrounds and were chosen specifically for their experience with graph drawing and information visualization. Our primary objectives were (1) to evaluate NodeXL as an SNA tool for a broad base of users and (2) to explore methods for teaching SNA. Our complementary dual case-study format demonstrates the usability of NodeXL for a diverse set of users, and significantly, the power of a tightly integrated metrics/visualization tool to spark insight and facilitate sense-making for students of SNA. |
BibTeX:
@inproceedings{Bonsignore09Firststepsto,
author = {Elizabeth M. Bonsignore and Cody Dunne and Dana Rotman and Marc Smith and Tony Capone and Derek L. Hansen and Ben Shneiderman},
title = {First steps to NetViz Nirvana: Evaluating social network analysis with NodeXL},
booktitle = {CSE '09: Proc. 2009 international conference on computational science and engineering},
publisher = {IEEE Computer Society Press},
year = {2009},
volume = {4},
pages = {332--339},
url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5284040},
doi = {http://dx.doi.org/10.1109/CSE.2009.120}
}
|
| Smith, M., Shneiderman, B., Milic-Frayling, N., Rodrigues, E.M., Barash, V., Dunne, C., Capone, T., Perer, A. & Gleave, E. (2009), "Analyzing (social media) networks with NodeXL", In C&T '09: Proc. fourth international conference on Communities and Technologies. New York, NY, USA., pp. 255-264. ACM.
[Abstract] [BibTeX] [DOI] [URL] [PDF] [Homepage] [Demo 1] [Demo 2] |
| Abstract: In this paper we present NodeXL, an extendible toolkit for network data analysis and visualization, implemented as an add-in to the Microsoft Excel 2007 spreadsheet software. We demonstrate NodeXL features through analysis of a data sample drawn from an enterprise intranet social network, discussion, and wiki. Through a sequence of steps we show how NodeXL leverages and extends the broadly used spreadsheet paradigm to support common operations in network analysis. This ranges from data import to computation of network statistics and refinement of network visualization through a selection of ready-to-use sorting, filtering, and clustering functions. |
BibTeX:
@inproceedings{Smith09Analyzing(socialmedia),
author = {Marc Smith and Ben Shneiderman and Natasa Milic-Frayling and Eduarda Mendes Rodrigues and Vladimir Barash and Cody Dunne and Tony Capone and Adam Perer and Eric Gleave},
title = {Analyzing (social media) networks with NodeXL},
booktitle = {C&T '09: Proc. fourth international conference on Communities and Technologies},
publisher = {ACM},
year = {2009},
pages = {255--264},
url = {http://portal.acm.org/citation.cfm?doid=1556460.1556497},
doi = {http://dx.doi.org/10.1145/1556460.1556497}
}
|
| Blue, R., Dunne, C., Fuchs, A., King, K. & Schulman, A. (2008), "Visualizing real-time network resource usage", In VizSec '08: Proc. 5th international workshop on Visualization for Computer Security. Berlin, Heidelberg. Volume 5210, pp. 119-135. Springer-Verlag. [Acceptance Rate: 66.7% (18/27)]
[Abstract] [BibTeX] [DOI] [URL] [PDF] [PowerPoint] [Homepage] [Demo] |
| Abstract: We present NetGrok, a tool for visualizing computer network usage in real-time. NetGrok combines well-known information visualization techniques—overview, zoom & filter, details on demand—with network graph and treemap visualizations. NetGrok integrates these tools with a shared data store that can read PCAP-formatted network traces, capture traces from a live interface, and filter the data set dynamically by bandwidth, number of connections, and time. We performed an expert user case study that demonstrates the benefits of applying these techniques to static and real-time streaming packet data. Our user study shows NetGrok serves as an “excellent real-time diagnostic,” enabling fast understanding of network resource usage and rapid anomaly detection. |
BibTeX:
@inproceedings{Blue08VisualizingReal-TimeNetwork,
author = {Ryan Blue and Cody Dunne and Adam Fuchs and Kyle King and Aaron Schulman},
title = {Visualizing real-time network resource usage},
booktitle = {VizSec '08: Proc. 5th international workshop on Visualization for Computer Security},
publisher = {Springer-Verlag},
year = {2008},
volume = {5210},
pages = {119-135},
url = {http://www.springerlink.com/content/p183420g43212p44},
doi = {http://dx.doi.org/10.1007/978-3-540-85933-8_12}
}
|
| Technical Reports |
| Dunne, C., Shneiderman, B., Gove, R., Klavans, J. & Dorr, B. (2011), "Rapid understanding of scientific paper collections: integrating statistics, text analysis, and visualization". University of Maryland, 2011. |
| Abstract: Keeping up with rapidly growing research fields, especially when there are multiple interdisciplinary sources, requires substantial effort for researchers, program managers, or venture capital investors. Current theories and tools are directed at finding a paper or website, not gaining an understanding of the key papers, authors, controversies, and hypotheses. This report presents an effort to integrate statistics, text analysis, and visualization in a multiple coordinated window environment that supports exploration. Our prototype system, Action Science Explorer (ASE), provides an environment for demonstrating principles of coordination and conducting iterative usability tests of them with interested and knowledgeable users. We developed an understanding of the value of reference management, statistics, citation context extraction, natural language summarization for single and multiple documents, filters to interactively select key papers, and network visualization to see citation patterns and identify clusters. The three-phase usability study guided our revisions to ASE and led us to improve the testing methods. |
BibTeX:
@techreport{Dunne11Rapidunderstandingof,
author = {Cody Dunne and Ben Shneiderman and Robert Gove and Judith Klavans and Bonnie Dorr},
title = {Rapid understanding of scientific paper collections: integrating statistics, text analysis, and visualization},
year = {2011},
url = {http://www.cs.umd.edu/localphp/hcil/tech-reports-search.php?number=2011-16}
}
|
| Dunne, C. & Shneiderman, B. (2009), "Improving graph drawing readability by incorporating readability metrics: a software tool for network analysts". University of Maryland, Technical Report HCIL-2009-13, May, 2009. |
| Abstract: Designing graph drawings that effectively communicate the underlying network is challenging as for every network there are many potential unintelligible or even misleading drawings. Automated graph layout algorithms have helped, but frequently generate ineffective drawings. In order to build awareness of effective graph drawing strategies, we detail readability metrics on a [0,1] continuous scale for node occlusion, edge crossing, edge crossing angle, and edge tunneling and summarize many more. Additionally, we define new node & edge readability metrics to provide more localized identification of where improvement is needed. These are implemented in SocialAction, a tool for social network analysis, in order to direct users towards poor areas of the drawing and provide real-time readability metric feedback as users manipulate it. These contributions are aimed at heightening the awareness of network analysts that the images they share or publish could be of higher quality, so that readers could extract relevant information. |
BibTeX:
@techreport{Dunne09Improvinggraphdrawing,
author = {Cody Dunne and Ben Shneiderman},
title = {Improving graph drawing readability by incorporating readability metrics: a software tool for network analysts},
year = {2009},
number = {HCIL-2009-13},
url = {http://www.cs.umd.edu/localphp/hcil/tech-reports-search.php?number=2009-13}
}
|
| Talks, Symposiums, Workshops, Posters, & Demos |
| Dunne, C. (2011), "Visual analytic tools for monitoring and understanding the emergence and evolution of innovations in science & technology", Talk at OECD-KNOWINNO workshop on measuring the use and impact of knowledge exchange mechanisms. November, 2011. |
| Abstract: The internet and other ICTs have had an important role in promoting the use of datamining tools for assembling, interlinking and analysing information from diverse sources. In this session we will explore how advanced data analytics tools can be used for identifying and measuring knowledge flows between different parties and to what extent they can complement more traditional data sources such as patents, publications and surveys. |
BibTeX:
@misc{Dunne11Visualanalytictools,
author = {Cody Dunne},
title = {Visual analytic tools for monitoring and understanding the emergence and evolution of innovations in science & technology},
howpublished = {Talk at OECD-KNOWINNO workshop on measuring the use and impact of knowledge exchange mechanisms},
year = {2011},
url = {http://www.oecd.org/sti/knowledge}
}
|
| Dunne, C. (2011), "What researchers want", Talk at STM 3rd Master Class on Developing Leadership and Innovation. November, 2011. |
BibTeX:
@misc{Dunne11Whatresearcherswant,
author = {Cody Dunne},
title = {What researchers want},
howpublished = {Talk at STM 3rd Master Class on Developing Leadership and Innovation},
year = {2011},
url = {http://www.stm-assoc.org/events/3rd-master-class-usa-2011/}
}
|
| Dunne, C. (2011), "Action Science Explorer: interactive data visualization for rapid understanding of scientific literature", Talk at STM Annual Spring Conference. April, 2011. |
| Abstract: We developed Action Science Explorer (ASE), a tool designed to support users in rapidly generating easily consumable summaries of academic literature. ASE uses bibliometric lexical link mining to create a citation network for a field and context for each citation, automatic clustering and multi-document summarization techniques to extract key points, and potent network analysis and visualization tools to aid in the exploration task. These techniques provide several coordinated views of the underlying data. |
BibTeX:
@misc{Dunne11ActionScienceExplorer_a,
author = {Cody Dunne},
title = {Action Science Explorer: interactive data visualization for rapid understanding of scientific literature},
howpublished = {Talk at STM Annual Spring Conference},
year = {2011},
url = {http://www.stm-assoc.org/events/stm-annual-spring-conference-2011/}
}
|
| Dunne, C., Zhang, P., Huang, C., Sun, J., Shneiderman, B., Wang, P. & Qu, Y. (2011), "Analyzing trends in science & technology innovation", In Proc. 28th Annual Human-Computer Interaction Lab Symposium. College Park, MD. May 2011. |
BibTeX:
@inproceedings{Dunne11Analyzingtrendsin,
author = {Cody Dunne and Pengyi Zhang and Chen Huang and Jia Sun and Ben Shneiderman and Ping Wang and Yan Qu},
title = {Analyzing trends in science & technology innovation},
booktitle = {Proc. 28th Annual Human-Computer Interaction Lab Symposium},
year = {2011},
url = {http://www.cs.umd.edu/hcil/soh/symposium.shtml}
}
|
| Dunne, C. (2011), "Interactive data visualization for rapid understanding of scientific literature", Poster at VAC '11: Visual Analytics Consortium Meeting. May, 2011. |
| Abstract: We developed Action Science Explorer (ASE), a tool designed to support users in rapidly generating easily consumable summaries of academic literature. ASE uses bibliometric lexical link mining to create a citation network for a field and context for each citation, automatic clustering and multi-document summarization techniques to extract key points, and potent network analysis and visualization tools to aid in the exploration task. These techniques provide several coordinated views of the underlying data. |
BibTeX:
@misc{Dunne11Interactivedatavisualization,
author = {Cody Dunne},
title = {Interactive data visualization for rapid understanding of scientific literature},
howpublished = {Poster at VAC '11: Visual Analytics Consortium Meeting},
year = {2011},
url = {http://vacommunity.org/VAC+Consortium+2011+Meeting}
}
|
| Dunne, C., Shneiderman, B., Dorr, B. & Klavans, J. (2010), "iOpener Workbench: tools for rapid understanding of scientific literature", In Proc. 27th Annual Human-Computer Interaction Lab Symposium. College Park, MD. May 2010. |
BibTeX:
@inproceedings{Dunne10iOpenerWorkbench_tools,
author = {Cody Dunne and Ben Shneiderman and Bonnie Dorr and Judith Klavans},
title = {iOpener Workbench: tools for rapid understanding of scientific literature},
booktitle = {Proc. 27th Annual Human-Computer Interaction Lab Symposium},
year = {2010},
url = {http://www.cs.umd.edu/hcil/about/events/symposium2010}
}
|
| Hansen, D., Dunne, C. & Shneiderman, B. (2010), "Analyzing social media networks with NodeXL", In Proc. 27th Annual Human-Computer Interaction Lab Symposium. College Park, MD. May 2010.
[BibTeX] [URL] [PDF] [PowerPoint] [Homepage] [Demo 1] [Demo 2] |
BibTeX:
@inproceedings{Hansen10Analyzingsocialmedia,
author = {Derek Hansen and Cody Dunne and Ben Shneiderman},
title = {Analyzing social media networks with NodeXL},
booktitle = {Proc. 27th Annual Human-Computer Interaction Lab Symposium},
year = {2010},
url = {http://www.cs.umd.edu/hcil/about/events/symposium2010}
}
|
| Shneiderman, B., Wang, P., Qu, Y. & Dunne, C. (2010), "Analyzing trends in science & technology innovation", In Proc. 27th Annual Human-Computer Interaction Lab Symposium. College Park, MD. May 2010. |
BibTeX:
@inproceedings{Shneiderman10Analyzingtrendsin,
author = {Ben Shneiderman and Ping Wang and Yan Qu and Cody Dunne},
title = {Analyzing trends in science & technology innovation},
booktitle = {Proc. 27th Annual Human-Computer Interaction Lab Symposium},
year = {2010},
url = {http://www.cs.umd.edu/hcil/about/events/symposium2010}
}
|
| Bonsignore, E.M. & Dunne, C. (2009), "First steps to NetViz Nirvana: evaluating social network analysis with NodeXL", Talk at Microsoft Research. Aug, 2009.
[Abstract] [BibTeX] [URL/Video] [PowerPoint] [Homepage] [Demo 1] [Demo 2] |
| Abstract: Social Network Analysis (SNA) has evolved as a popular, standard method for modeling meaningful, often hidden structural relationships in communities. Existing SNA tools often involve extensive pre-processing or intensive programming skills that can challenge practitioners and students alike. NodeXL, an open-source template for Microsoft Excel, offers a potentially low-barrier-to-entry framework for teaching and learning SNA. We present the findings of 2 user studies of 21 graduate students who engaged in SNA using NodeXL. We found NodeXL to be an effective tool for a diverse set of users, and significantly, a tightly integrated metrics/visualization tool that can spark insight and facilitate sense-making for students of SNA. Our presentation will focus on the unique features that made NodeXL learnable and usable. After a brief overview of the NodeXL tool, we will describe our research methodology, based on Multi-dimensional In-depth Long-term Case studies (MILCs), an approach that enables effective evaluations of complex visual analytics tools. We will discuss NetViz Nirvana, layout principles that can increase the readability and interpretative power of social network visualizations, and present a sample of visualizations produced by the students. Finally, we will offer lessons learned for educators, researchers, and developers of SNA tools such as NodeXL. |
BibTeX:
@misc{Bonsignore09Firststepstoa,
author = {Elizabeth M. Bonsignore and Cody Dunne},
title = {First steps to NetViz Nirvana: evaluating social network analysis with NodeXL},
howpublished = {Talk at Microsoft Research},
year = {2009},
url = {http://research.microsoft.com/apps/video/default.aspx?id=103362}
}
|
| Dunne, C. & Shneiderman, B. (2009), "Readability metrics for network visualization", In Proc. 26th Annual Human-Computer Interaction Lab Symposium. College Park, MD. May 2009.
[BibTeX] [URL] [PDF] [PowerPoint] [Demo Video--AVI, No Audio] |
BibTeX:
@inproceedings{Dunne09Readabilitymetricsnetwork,
author = {Cody Dunne and Ben Shneiderman},
title = {Readability metrics for network visualization},
booktitle = {Proc. 26th Annual Human-Computer Interaction Lab Symposium},
year = {2009},
url = {http://www.cs.umd.edu/hcil/about/events/symposium2009}
}
|
Cody Dunne
Email:
cdunne at cs.umd.edu
Address:
Department of Computer Science
Human-Computer Interaction Lab (HCIL)
2117 Hornbake Libary, S. wing
University of Maryland
College Park, MD 20742