Visualized Analysis of Neuroaesthetics Research: A Review Based on CiteSpace

Published: 15 Jun 2019 | Version 1 | DOI: 10.17632/hvjw6x92sn.1
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Description of this data

1.Full record and cited references from all articles and reviews published in Neuroaesthetics journals between 1991 and 2018 were exported as text files. We used the keyword“neuroaesthetics”to search the literatures. The information we choose including author data, keywords, citation data and abstract.

2.We imported the data from Web of Science Core Collection into a plain text, sent the text to the new created project named“Neuroaesthetics”in the CiteSpace. After the data was imported into CiteSpace, the network of neuroaesthetics core literatures was visually analyzed. For some related variable analysis, due to too many links, it is impossible to directly understand the visualization process. Thus, we made the cluster.
 
3.Co-Cited References Analysis
reflect the dynamic changes in neuroaesthetics research fields

Dual-Map Overlay Analysis
The dual-map overlays can identifies the dynamics of previous study on the basis of the data set with cross-discilines.

Burst Detection Analysis
The function of burst detection searches for scientific features that have high intensities over limited temporal durations and capture the sharp increases in interest in a specific research field. Burst detection can present some topics which were actively discussed in neuroaesthetics for a time. The analysis of burst detection can find the emerging trends in the area of neuroaesthetics.

Experiment data files

Latest version

  • Version 1

    2019-06-15

    Published: 2019-06-15

    DOI: 10.17632/hvjw6x92sn.1

    Cite this dataset

    Wang, Xiaoyu (2019), “Visualized Analysis of Neuroaesthetics Research: A Review Based on CiteSpace”, Mendeley Data, v1 http://dx.doi.org/10.17632/hvjw6x92sn.1

Statistics

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Downloads: 32

Institutions

Dalian University of Technology

Categories

Neuroscience, Aesthetics

Licence

CC BY 4.0 Learn more

The files associated with this dataset are licensed under a Creative Commons Attribution 4.0 International licence.

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This dataset is licensed under a Creative Commons Attribution 4.0 International licence. What does this mean? You can share, copy and modify this dataset so long as you give appropriate credit, provide a link to the CC BY license, and indicate if changes were made, but you may not do so in a way that suggests the rights holder has endorsed you or your use of the dataset. Note that further permission may be required for any content within the dataset that is identified as belonging to a third party.

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