AS#04 yt-comment visualization

The data

Preparing data

yt_comment_demo

library(tidyverse)
library(lubridate)
options(stringsAsFactors = F)

Loading data

data_url <- "https://github.com/P4CSS/R4CSSData/raw/main/newswawawa_yt_comments.rds"
raw <- read_rds(url(data_url))

1. Data Coverage: density plot

2. Data Converage: weekly or monthly

• Hint: using floor_date()

3. Demographic

• Add more demographic features here, at least more 2 features

## Number of videos: 3737

4. Number of comment distribution per video: density plot

Hint: using ggplot2 xlab() to label the x-axis

5. Number of comments distribution

Hint: Using scale_y_log10() and scale_x_log10() to adjust y-axis scale

6. Comment patterns each month

• Filter comments after 2019-09-30, before 2020-02-01

• density plot per month

• subplot by facet_wrap() with argument scales = "free"

7. Comments pattern by week

• Filter comments after 2019-12-01, before 2020-02-01

8. Comments pattern by hour per day

• Filter comments after 2019-12-30, before 2020-01-20

• may using ifelse() ternary operation to divide plot into two parts: after and before 2020-01-11

9. Challenge: Growth of unique member