| id |
caadria2018_158 |
| authors |
Koh, Immanuel |
| year |
2018 |
| title |
Learning Design Trends from Social Networks - Data Mining, Analysis & Visualization of Grasshopper® Online User Community |
| doi |
https://doi.org/10.52842/conf.caadria.2018.2.277
|
| source |
T. Fukuda, W. Huang, P. Janssen, K. Crolla, S. Alhadidi (eds.), Learning, Adapting and Prototyping - Proceedings of the 23rd CAADRIA Conference - Volume 2, Tsinghua University, Beijing, China, 17-19 May 2018, pp. 277-286 |
| summary |
The paper has demonstrated that the increasingly online relationship between designers and their digital tools can be quantitatively represented, described and analyzed through the data-mining of design-domain specific and tool-based social network (i.e. Grasshopper3D). It explores design trends' correlations based on network user groups' size, users' demographics, nodes' degree centrality and discussion threads' popularity. |
| keywords |
Social Networks; Design Trends; Big Data; Parametric Design Tools; Data Visualization |
| series |
CAADRIA |
| email |
|
| full text |
 file.pdf (12,586,379 bytes) |
| references |
Content-type: text/plain
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Ratti, C and Claudel, M (2015)
 Open Source Architecture
, Thames & Hudson, London
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Schumacher, P (2009)
Parametricism: A New Global Style for Architecture and Urban Design
, Architectural Design, 79(4), pp. 14-23
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Tversky, B. and Hard, B.M. (2009)
Embodied and disembodied cognition: Spatial perspective-taking
, Cognition, 110(1), pp. 124-129
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| last changed |
2022/06/07 07:51 |
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