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Aris, A.; Shneiderman, B.; Qazvinian, V.; Radev, D.: Visual overviews for discovering key papers and influences across research fronts (2009)
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- Abstract
- Gaining a rapid overview of an emerging scientific topic, sometimes called research fronts, is an increasingly common task due to the growing amount of interdisciplinary collaboration. Visual overviews that show temporal patterns of paper publication and citation links among papers can help researchers and analysts to see the rate of growth of topics, identify key papers, and understand influences across subdisciplines. This article applies a novel network-visualization tool based on meaningful layouts of nodes to present research fronts and show citation links that indicate influences across research fronts. To demonstrate the value of two-dimensional layouts with multiple regions and user control of link visibility, we conducted a design-oriented, preliminary case study with 6 domain experts over a 4-month period. The main benefits were being able (a) to easily identify key papers and see the increasing number of papers within a research front, and (b) to quickly see the strength and direction of influence across related research fronts.
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Chen, C.: CiteSpace II : detecting and visualizing emerging trends and transient patterns in scientific literature (2006)
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- Date
- 22. 7.2006 16:11:05
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Zhang, Y.; Zhang, G.; Zhu, D.; Lu, J.: Scientific evolutionary pathways : identifying and visualizing relationships for scientific topics (2017)
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- Abstract
- Whereas traditional science maps emphasize citation statistics and static relationships, this paper presents a term-based method to identify and visualize the evolutionary pathways of scientific topics in a series of time slices. First, we create a data preprocessing model for accurate term cleaning, consolidating, and clustering. Then we construct a simulated data streaming function and introduce a learning process to train a relationship identification function to adapt to changing environments in real time, where relationships of topic evolution, fusion, death, and novelty are identified. The main result of the method is a map of scientific evolutionary pathways. The visual routines provide a way to indicate the interactions among scientific subjects and a version in a series of time slices helps further illustrate such evolutionary pathways in detail. The detailed outline offers sufficient statistical information to delve into scientific topics and routines and then helps address meaningful insights with the assistance of expert knowledge. This empirical study focuses on scientific proposals granted by the United States National Science Foundation, and demonstrates the feasibility and reliability. Our method could be widely applied to a range of science, technology, and innovation policy research, and offer insight into the evolutionary pathways of scientific activities.
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Samoylenko, I.; Chao, T.-C.; Liu, W.-C.; Chen, C.-M.: Visualizing the scientific world and its evolution (2006)
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Chen, R.H.-G.; Chen, C.-M.: Visualizing the world's scientific publications (2016)
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