Visualization

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Last edited Jan 4, 2018

Created on Jan 4, 2018

This visualization displays a principal component analysis of citation data from 2,000 philosophy articles, projecting each article into a 2D scatterplot where points are colored by K-Means cluster assignment. The chart, built with D3 v3 and rendered as SVG, supports zooming and panning through the d3.behavior.zoom API. Each dot represents an article, with mouseover tooltips provided by the d3-tip library. The visualization includes an interactive button that switches the x-axis to display carbohydrate values, demonstrating a data-viewing alternative, though the primary dataset remains the citation components.

AI-generated description

A Principle Component Analysis of the Citation-Data of 2000 Philosophy-Articles from the 90s. Clusters are generated with K-Means.

PerformanceVector: Avg. within cluster similarity: 22.989 Avg. within cluster similarity for cluster 0: 29.944 Avg. within cluster similarity for cluster 1: 39.114 Avg. within cluster similarity for cluster 2: 15.005 Avg. within cluster similarity for cluster 3: 20.072 Avg. within cluster similarity for cluster 4: 31.659 Avg. within cluster similarity for cluster 5: 13.399 Avg. within cluster similarity for cluster 6: 17.724

The Scatterplot is forked from <a href='http://bl.ocks.org/peterssonjonas/'>peterssonjonas</a>'s block: <a href='http://bl.ocks.org/peterssonjonas/4a0e7cb8d23231243e0e'>D3 Zoomable Scatterplot</a>

forked from <a href='http://bl.ocks.org/MNoichl/'>MNoichl</a>'s block: <a href='http://bl.ocks.org/MNoichl/ab5a637122ee56e422168fd6c8db0cbf'>PCA Philososophy-Articles</a>

mit Licensed

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