Analysis of @ikashnitsky tweets -- https://twitter.com/ikashnitsky/status/1265570413997953024

my-tweets.R

#===============================================================================
# 2020-05-27 -- twitter
# explore the timing of my twitter activity
# Ilya Kashnitsky, ilya.kashnitsky@gmail.com
#===============================================================================

library(tidyverse)
library(rtweet)
library(lubridate)
library(ggdark)
library(ggtext)
library(rcartocolor)
library(rcartocolor)

# get data -- luckily I have 3108 tweets
df_tweets <- get_timeline(user = "ikashnitsky", n = 3200)
save(df_tweets, file = "200527-my-tweets//ik-tweets.rda")

load("200527-my-tweets//ik-tweets.rda")

df_time <- 
    df_tweets %>% 
    transmute(
        created_at,
        date = created_at %>% as_date() %>% ymd,
        year = created_at %>% year(), 
        month = created_at %>% month(label = T), 
        week = created_at %>% week(),
        weekday = created_at %>% wday(label = T, abbr = T, week_start = 1),
        hour = created_at %>% hour()
    )

# calendar plot of my tweets created between 2 and 6 am
df_time %>%
    mutate(night_like = hour %in% 2:6) %>% 
    group_by(date, year, month, week, weekday) %>%
    summarise(n = night_like %>% sum) %>% 
    ungroup() %>% 
    ggplot(aes(week, weekday, fill = !n==0))+
    geom_tile()+
    scale_fill_manual(values = c("grey", "cyan"), guide = NULL)+
    scale_x_continuous(breaks = c(1:9, 20, 30, 52))+
    facet_grid(year~month, scales = "free")+
    dark_theme_minimal(base_family = "mono") +
    theme(
        text = element_text(face = 2),
        panel.grid = element_blank(),
        panel.spacing = unit(.5, "lines"),
        plot.title = element_markdown(size = 20)
    )+
    labs(
        x = "week of the year", y = "week day",
        title = "On which days I <span style='color:#00FFFF'>tweeted between 2 and 6 am</span>",
        caption = "@ikashnitsky"
    )

ggsave("my-tweets-night.png", width = 8, height = 5)


# number of tweets by day
df_time %>%
    group_by(date, year, month, week, weekday) %>%
    summarise(n = n()) %>% 
    ungroup() %>% 
    ggplot(aes(week, weekday, fill = n))+
    geom_tile()+
    scale_fill_carto_c(palette = "Sunset", direction = -1,
                       guide = guide_colorbar(barwidth = 30, barheight = .5))+
    scale_x_continuous(breaks = c(1:9, 20, 30, 52))+
    facet_grid(year~month, scales = "free")+
    dark_theme_minimal(base_family = "mono") +
    theme(
        text = element_text(face = 2),
        panel.grid = element_blank(),
        panel.spacing = unit(.5, "lines"),
        plot.title = element_markdown(size = 22),
        legend.position = "top"
    )+
    labs(
        x = "week of the year", 
        y = "week day",
        title = "My days on Twitter: <span style='color:#F3E79BFF'>more</span> and <span style='color:#5C53A5FF'>less</span> active",
        caption = "@ikashnitsky",
        
        fill = NULL
    )

ggsave("my-tweets-n.png", width = 8, height = 5)


# just timing
df_time %>%
    group_by(hour) %>%
    summarise(n = n()) %>% 
    ungroup() %>% 
    mutate(prop = n / sum(n)) %>% 
    ggplot(aes(x = hour, y = prop, fill = prop)) + 
    geom_col(position = position_nudge(x = .5)) +
    scale_x_continuous(breaks = c(6, 12, 18))+
    scale_y_percent()+
    scale_fill_carto_c(palette = "Mint", direction = -1, guide = NULL)+
    dark_theme_minimal(base_family = "mono") +
    theme(
        text = element_text(face = 2),
        panel.grid.minor = element_blank(),
        plot.title = element_markdown(size = 22)
        )+
    labs(
        title = "My tweets by hour",
        x = "hour of the day",
        y = "proportion of tweets",
        caption = "@ikashnitsky"
    )

ggsave("my-tweets-by-hour.png", width = 8, height = 5)