An open API service providing mapping between scientific papers and software projects that are mentioned in them.

Papers: 10.3390/ijerph15020250

https://doi.org/10.3390/ijerph15020250

Using Twitter to Better Understand the Spatiotemporal Patterns of Public Sentiment: A Case Study in Massachusetts, USA

Cited by: 32
Author(s): Xiaodong Cao, Piers MacNaughton, Zhengyi Deng, Jie Yin, Xi Zhang, Joseph G. Allen
Published: over 7 years ago

Software Mentions 7

cran: ggplot2
Create Elegant Data Visualisations Using the Grammar of Graphics
Papers that mentioned: 11,441
Very Likely Science (100)
cran: ggthemes
Extra Themes, Scales and Geoms for 'ggplot2'
Papers that mentioned: 69
Very Likely Science (100)
cran: nlme
Linear and Nonlinear Mixed Effects Models
Papers that mentioned: 3,265
Very Likely Science (100)
cran: scales
Scale Functions for Visualization
Papers that mentioned: 104
Very Likely Science (100)
cran: viridis
Colorblind-Friendly Color Maps for R
Papers that mentioned: 92
Very Likely Science (100)
pypi: scales
Stats for Python processes
Papers that mentioned: 104
Very Likely Science (65)
pypi: viridis
Tree data structures and algorithms
Papers that mentioned: 92
Very Likely Science (100)