⚖️ How Fair Use Cases Evolved: from Text ✍️(1998) to Internet 💻 (2018)

Data Preprocess

The categories column contains multiple categories, and some of them are not clean. It took some time to clean them. You can check the code below.

library(GWalkR)
library(tidyr)

cases_df <- read.csv("fair_use_cases.csv")
cases_cate_df <- separate_rows(cases_df, categories, sep = ";|,")
cases_cate_df$categories <- tolower(cases_cate_df$categories)
cases_cate_df$categories <- trimws(cases_cate_df$categories, "left")

cases_cate_df <- subset(cases_cate_df, !grepl("circuit", categories, ignore.case = TRUE))

Data Viz: case year vs. category

The length of a bar represents row count and the color represents the median year of the case. The unpublished and textual work are the two oldest categories with median years of 1998 and 1999.5, while photograph and internet/digitalization are the two latest categories with median years of 2015 and 2018.

Data Viz empowered by (It’s on CRAN now!!)

gwalkr(data=cases_cate_df, visConfigFile="./test_config.json")