Analysis of @ikashnitsky Twitter likes -- https://twitter.com/ikashnitsky/status/1265363605110902786

my-twitter-likes.R

#===============================================================================
# 2020-05-26 -- twitter
# who I like
# Ilya Kashnitsky, ilya.kashnitsky@gmail.com
#===============================================================================

library(tidyverse)
library(rtweet)
library(ggdark)
library(rcartocolor)
library(hrbrthemes); import_roboto_condensed()
library(showtext)
showtext_auto()

# data processing adapted from: 
# https://gist.github.com/fernandobarbalho/189c1f8d62f1e6c396a7c5e22e8f9a2c
df_likes <- rtweet::get_favorites("ikashnitsky", n = 3000)

users_favorite<-
    df_likes %>% 
    group_by(screen_name, user_id) %>%
    summarise(
        quant_fav= n()
    )

users_favorite %>%
    ungroup() %>%
    top_n(15,quant_fav) %>%
    mutate(screen_name = reorder(screen_name,quant_fav)) %>%
    ggplot(aes(y = screen_name, x = quant_fav, fill = quant_fav)) + 
    geom_col() +
    dark_theme_minimal(base_family = font_rc, base_size = 16) +
    scale_fill_carto_c(palette = "Mint", direction = -1, guide = NULL)+
    labs(
        title = "Top 15 accounts I like more often",
        y = "@ user names",
        x= "# of tweets liked by @ikashnitsky" 
    )

ggsave("my-twitter-likes.png", width = 7, height = 5)



# analyse the number of likes in time -------------------------------------

library(lubridate)

df_days <- 
    df_likes %>% 
    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)
    )

df_days %>%
    mutate(year_week = paste0(year, "-", week)) %>% 
    group_by(year, week, year_week) %>%
    summarise(
        quant_fav= n()
    ) %>% 
    ungroup() %>% 
    arrange(year, week) %>% 
    mutate(week = week %>% as_factor %>% fct_inorder()) %>% 
    ggplot(aes(x = week, y = quant_fav, fill = quant_fav)) + 
    annotate(geom = "rect", xmin = -Inf, xmax = 4.5, ymin = -Inf, ymax = Inf,
             color = NA, fill = "yellow", alpha = .05)+
    geom_col() +
    dark_theme_minimal(base_family = font_rc, base_size = 16) +
    scale_fill_carto_c(palette = "Mint", direction = -1, guide = NULL)+
    labs(
        title = "My recent liking activity on Twitter",
        x = "week of the year",
        y = "# of likes by @ikashnitsky" 
    )+
    annotate(geom = "text", x = c("50", "1"), y = 250,
             size = 6, hjust = 0, family = font_rc,
             label = c("2019", "2020"))

ggsave("my-twitter-likes-by-week.png", width = 7, height = 5)


# by week day -------------------------------------------------------------

# calendar plot of likes tolls by day
df_days %>%
    group_by(date, year, month, week, weekday) %>%
    summarise(
        quant_fav= n()
    ) %>% 
    ungroup() %>% 
    ggplot(aes(week, weekday, fill = quant_fav))+
    geom_tile()+
    # scale_fill_viridis_c("#likes")+
    scale_fill_carto_c("#likes", palette = "PurpOr", direction = -1)+
    scale_x_continuous(breaks = c(1:9, 20, 30, 52))+
    facet_grid(~year+month, scales = "free")+
    dark_theme_minimal(base_family = font_rc, base_size = 16) +
    theme(panel.grid = element_blank())+
    labs(x = "week of the year", y = "week day",
         title = "My recent liking activity on Twitter")

ggsave("my-twitter-likes-calendar.png", width = 7, height = 5)


# by hour -----------------------------------------------------------------
df_likes %>% 
    transmute(
        created_at,
        hour = created_at %>% hour(),
        year = created_at %>% year(), 
        month = created_at %>% month(label = T), 
        weekday = created_at %>% wday(label = T, abbr = T, week_start = 1)
    ) %>%
    group_by(hour) %>%
    summarise(
        quant_fav= n()
    ) %>% 
    ungroup() %>% 
    mutate(prop = quant_fav / sum(quant_fav)) %>% 
    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 = font_rc, base_size = 16) +
    theme(panel.grid.minor = element_blank())+
    labs(
        title = "My recent liking activity on Twitter",
        x = "hour of the day",
        y = "proportion of likes",
        caption = "@ikashnitsky"
    )

ggsave("my-twitter-likes-by-hour.png", width = 7, height = 5)

# also facet by week day
df_likes %>% 
    transmute(
        created_at,
        hour = created_at %>% hour(),
        year = created_at %>% year(), 
        month = created_at %>% month(label = T), 
        weekday = created_at %>% wday(label = T, abbr = T, week_start = 1)
    ) %>%
    group_by(weekday, hour) %>%
    summarise(
        quant_fav= n()
    ) %>% 
    ungroup() %>% 
    group_by(weekday) %>% 
    mutate(prop = quant_fav / sum(quant_fav)) %>% 
    ungroup() %>%
    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)+
    facet_wrap(~weekday, ncol = 5)+
    dark_theme_minimal(base_family = font_rc, base_size = 16) +
    theme(panel.grid.minor = element_blank())+
    labs(
        title = "My recent liking activity on Twitter",
        x = "hour of the day",
        y = "proportion of likes",
        caption = "@ikashnitsky"
    )

ggsave("my-twitter-likes-by-hour-weekday.png", width = 7, height = 5)