Example: Analyzing #statstiktok • tiktokr

First, let’s load tiktokr and some tidyverse libraries.

library(tiktokr)
library(dplyr)
library(ggplot2)
library(lubridate)
library(stringr)

Make sure to use your preferred Python installation

library(reticulate)

use_python(py_config()$python)

The next two steps you only need to do once:

Install necessary Python libraries

tk_install()

Authentication

In November 2020, Tiktok increased its security protocol. They now frequently show a captcha, which is easily triggered after a few requests. This can be solved by specifying the cookie parameter. To get a cookie session:

Open a browser and go to “http://tiktok.com”
Scroll down a bit, to ensure, that you don’t get any captcha
Open the javascript console (in Chrome: View > Developer > Javascript Console)
Run document.cookie in the console. Copy the entire output (your cookie).
Run tk_auth() in R and paste the cookie.

Click on image below for screen recording of how to get your TikTok cookie:

The tk_auth function will save cookies (and user agent) as environment variable to your .Renviron file. You need to only run this once to use the tiktokr or whenever you want to update your cookie/user agent.

tk_auth(cookie = "<paste here the output from document.cookie>")

Getting #statstiktok posts

Once per script you need to run tk_init to initialize tiktokr

tk_init()

Let’s now get data on #statstiktok with tk_posts!

stats_tiktok <- tk_posts(scope = "hashtag", query = "statstiktok", n = 2000)

Great! Now we have a dataset with metadata on tiktoks mentioning the hashtag ‘statstiktok’!

glimpse(stats_tiktok)
#> Rows: 123
#> Columns: 67
#> $ video_id                   <chr> "awesome", "awesome", "awesome", "awesome"…
#> $ video_height               <int> 1024, 1024, 1024, 1024, 1024, 544, 1024, 1…
#> $ video_width                <int> 576, 576, 576, 576, 576, 960, 576, 576, 54…
#> $ video_duration             <int> 9, 7, 19, 12, 15, 10, 11, 13, 44, 8, 6, 9,…
#> $ video_ratio                <chr> "720p", "720p", "720p", "720p", "720p", "7…
#> $ video_cover                <chr> "https://p16-sign-sg.tiktokcdn.com/obj/tos…
#> $ video_originCover          <chr> "https://p16-sign-sg.tiktokcdn.com/obj/tos…
#> $ video_dynamicCover         <chr> "https://p16-sign-sg.tiktokcdn.com/obj/tos…
#> $ video_playAddr             <chr> "https://v16-web.tiktok.com/video/tos/usea…
#> $ video_downloadAddr         <chr> "https://v16-web.tiktok.com/video/tos/usea…
#> $ video_shareCover           <chr> "c(\"\", \"https://p16-sign-sg.tiktokcdn.c…
#> $ video_reflowCover          <chr> "https://p16-sign-sg.tiktokcdn.com/obj/tos…
#> $ author_id                  <chr> "6815076321426326533", "681507632142632653…
#> $ author_uniqueId            <chr> "chelllarson", "chelllarson", "chelseaparl…
#> $ author_nickname            <chr> "Mitchell", "Mitchell", "Chelsea Parlett",…
#> $ author_avatarThumb         <chr> "https://p16-sign-va.tiktokcdn.com/musical…
#> $ author_avatarMedium        <chr> "https://p16-sign-va.tiktokcdn.com/musical…
#> $ author_avatarLarger        <chr> "https://p16-sign-va.tiktokcdn.com/musical…
#> $ author_signature           <chr> "#statstiktok", "#statstiktok", "Just real…
#> $ author_verified            <chr> "FALSE", "FALSE", "FALSE", "FALSE", "FALSE…
#> $ author_secUid              <chr> "MS4wLjABAAAARU9QzliiCVeZiuAx4r-JdbzhucGjg…
#> $ author_secret              <chr> "FALSE", "FALSE", "FALSE", "FALSE", "FALSE…
#> $ author_ftc                 <chr> "FALSE", "FALSE", "FALSE", "FALSE", "FALSE…
#> $ author_relation            <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
#> $ author_openFavorite        <chr> "FALSE", "FALSE", "FALSE", "FALSE", "FALSE…
#> $ author_commentSetting      <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
#> $ author_duetSetting         <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
#> $ author_stitchSetting       <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
#> $ author_privateAccount      <chr> "FALSE", "FALSE", "FALSE", "FALSE", "FALSE…
#> $ music_id                   <chr> "6886831115148036869", "689022456349447245…
#> $ music_title                <chr> "Ur appreciated ily", "original sound", "o…
#> $ music_playUrl              <chr> "https://sf16-sg.tiktokcdn.com/obj/musical…
#> $ music_coverThumb           <chr> "https://p16-sign-va.tiktokcdn.com/tos-mal…
#> $ music_coverMedium          <chr> "https://p16-sign-va.tiktokcdn.com/tos-mal…
#> $ music_coverLarge           <chr> "https://p16-sign-va.tiktokcdn.com/tos-mal…
#> $ music_authorName           <chr> "angela vasquez \U0001f49f", "carson", "Ra…
#> $ music_original             <chr> "TRUE", "TRUE", "TRUE", "TRUE", "FALSE", "…
#> $ stats_diggCount            <int> 42500, 2853, 2789, 1328, 1019, 638, 531, 2…
#> $ stats_shareCount           <int> 6136, 480, 355, 10, 44, 11, 46, 38, 0, 17,…
#> $ stats_commentCount         <int> 965, 75, 56, 27, 43, 2, 45, 16, 32, 10, 11…
#> $ stats_playCount            <int> 554100, 47200, 40100, 15200, 11500, 3386, …
#> $ authorStats_followingCount <int> 32, 32, 240, 240, 240, 24, 240, 240, 7790,…
#> $ authorStats_followerCount  <int> 259, 259, 1519, 1519, 1519, 2752, 1519, 15…
#> $ authorStats_heartCount     <int> 45500, 45500, 12000, 12000, 12000, 32100, …
#> $ authorStats_videoCount     <int> 5, 5, 69, 69, 69, 306, 69, 69, 490, 69, 69…
#> $ authorStats_diggCount      <int> 13800, 13800, 785, 785, 785, 8462, 785, 78…
#> $ authorStats_heart          <int> 45500, 45500, 12000, 12000, 12000, 32100, …
#> $ id                         <chr> "6895134839197011206", "689431916878766413…
#> $ desc                       <chr> "Where are all my fellow H0s at? No HAs al…
#> $ createTime                 <int> 1605398717, 1605208816, 1599615483, 159992…
#> $ challenges                 <chr> "list(id = \"1663286341999621\", title = \…
#> $ originalItem               <chr> "FALSE", "FALSE", "FALSE", "FALSE", "FALSE…
#> $ officalItem                <chr> "FALSE", "FALSE", "FALSE", "FALSE", "FALSE…
#> $ textExtra                  <chr> "list(awemeId = \"\", start = 47, end = 59…
#> $ secret                     <chr> "FALSE", "FALSE", "FALSE", "FALSE", "FALSE…
#> $ forFriend                  <chr> "FALSE", "FALSE", "FALSE", "FALSE", "FALSE…
#> $ digged                     <chr> "FALSE", "FALSE", "FALSE", "FALSE", "FALSE…
#> $ itemCommentStatus          <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
#> $ showNotPass                <chr> "FALSE", "FALSE", "FALSE", "FALSE", "FALSE…
#> $ vl1                        <chr> "FALSE", "FALSE", "FALSE", "FALSE", "FALSE…
#> $ itemMute                   <chr> "FALSE", "FALSE", "FALSE", "FALSE", "FALSE…
#> $ privateItem                <chr> "FALSE", "FALSE", "FALSE", "FALSE", "FALSE…
#> $ duetEnabled                <chr> "TRUE", "TRUE", "TRUE", "TRUE", "TRUE", "T…
#> $ stitchEnabled              <chr> "TRUE", "TRUE", "TRUE", "TRUE", "TRUE", "T…
#> $ shareEnabled               <chr> "TRUE", "TRUE", "TRUE", "TRUE", "TRUE", "T…
#> $ isAd                       <chr> "FALSE", "FALSE", "FALSE", "FALSE", "FALSE…
#> $ effectStickers             <chr> "NULL", "NULL", "NULL", "NULL", "NULL", "N…

First, the data needs to be cleaned. Many variables that TikTok returns are not relevant, so we focus on the most important ones and clean the variable names using janitor::clean_names().

stats_tk <- stats_tiktok %>% 
  select(id, createTime, 
         author_id:author_nickname, 
         author_signature, author_avatarLarger, 
         desc, music_id:authorStats_heart) %>% 
  janitor::clean_names() %>% 
  distinct(id, .keep_all = T)

glimpse(stats_tk)
#> Rows: 123
#> Columns: 26
#> $ id                           <chr> "6895134839197011206", "6894319168787664…
#> $ create_time                  <int> 1605398717, 1605208816, 1599615483, 1599…
#> $ author_id                    <chr> "6815076321426326533", "6815076321426326…
#> $ author_unique_id             <chr> "chelllarson", "chelllarson", "chelseapa…
#> $ author_nickname              <chr> "Mitchell", "Mitchell", "Chelsea Parlett…
#> $ author_signature             <chr> "#statstiktok", "#statstiktok", "Just re…
#> $ author_avatar_larger         <chr> "https://p16-sign-va.tiktokcdn.com/music…
#> $ desc                         <chr> "Where are all my fellow H0s at? No HAs …
#> $ music_id                     <chr> "6886831115148036869", "6890224563494472…
#> $ music_title                  <chr> "Ur appreciated ily", "original sound", …
#> $ music_play_url               <chr> "https://sf16-sg.tiktokcdn.com/obj/music…
#> $ music_cover_thumb            <chr> "https://p16-sign-va.tiktokcdn.com/tos-m…
#> $ music_cover_medium           <chr> "https://p16-sign-va.tiktokcdn.com/tos-m…
#> $ music_cover_large            <chr> "https://p16-sign-va.tiktokcdn.com/tos-m…
#> $ music_author_name            <chr> "angela vasquez \U0001f49f", "carson", "…
#> $ music_original               <chr> "TRUE", "TRUE", "TRUE", "TRUE", "FALSE",…
#> $ stats_digg_count             <int> 42500, 2853, 2789, 1328, 1019, 638, 531,…
#> $ stats_share_count            <int> 6136, 480, 355, 10, 44, 11, 46, 38, 0, 1…
#> $ stats_comment_count          <int> 965, 75, 56, 27, 43, 2, 45, 16, 32, 10, …
#> $ stats_play_count             <int> 554100, 47200, 40100, 15200, 11500, 3386…
#> $ author_stats_following_count <int> 32, 32, 240, 240, 240, 24, 240, 240, 779…
#> $ author_stats_follower_count  <int> 259, 259, 1519, 1519, 1519, 2752, 1519, …
#> $ author_stats_heart_count     <int> 45500, 45500, 12000, 12000, 12000, 32100…
#> $ author_stats_video_count     <int> 5, 5, 69, 69, 69, 306, 69, 69, 490, 69, …
#> $ author_stats_digg_count      <int> 13800, 13800, 785, 785, 785, 8462, 785, …
#> $ author_stats_heart           <int> 45500, 45500, 12000, 12000, 12000, 32100…

Now we have a cleaned sample of #statstiktok!

Stats about tiktokers

Let`s first find out who the top posters are in the data. Chelsea Parlett-Pelleriti is the most prolific poster, when it comes to #statstiktok. This actually makes sense, considering that she is one of the pioneers of #statstiktok.

stats_tk %>% 
  count(author_unique_id, sort = T) %>% 
  filter(n >= 2) %>% 
  mutate(authr_url = paste0("https://www.tiktok.com/@", author_unique_id)) %>% 
  knitr::kable() %>%
  kableExtra::kable_styling()

author_unique_id	n	authr_url
chelseaparlettpelleriti	61	https://www.tiktok.com/@chelseaparlettpelleriti
baboutunt	5	https://www.tiktok.com/@baboutunt
dsquintana	5	https://www.tiktok.com/@dsquintana
lakens	4	https://www.tiktok.com/@lakens
epiellie	3	https://www.tiktok.com/@epiellie
morgane_fevrier	3	https://www.tiktok.com/@morgane_fevrier
statprof	3	https://www.tiktok.com/@statprof
bookmatter	2	https://www.tiktok.com/@bookmatter
chelllarson	2	https://www.tiktok.com/@chelllarson
dataislife	2	https://www.tiktok.com/@dataislife
ladykelp	2	https://www.tiktok.com/@ladykelp
rismyfavouriteletter	2	https://www.tiktok.com/@rismyfavouriteletter
ryansscience	2	https://www.tiktok.com/@ryansscience
sam_d_parsons	2	https://www.tiktok.com/@sam_d_parsons

Metadata includes author data, such as the unique handle of the author (author_unique_id), the text of their bio (author_signature) and some author stats (like the follower count: author_stats_follower_count). In addition to classical social media metrics (number of accounts followed, posts, likes), Tiktok also includes ‘diggs’. Unfortunately, there is no documentation on how this metric is computed. The author_stats_heart shows how many likes a user has received in total.

tiktokers <- stats_tk %>% 
  select(contains("author")) %>% 
  add_count(author_unique_id, name = "vids_in_sample") %>% 
  distinct(author_id, .keep_all = T)

glimpse(tiktokers)
#> Rows: 39
#> Columns: 13
#> $ author_id                    <chr> "6815076321426326533", "6736543492652696…
#> $ author_unique_id             <chr> "chelllarson", "chelseaparlettpelleriti"…
#> $ author_nickname              <chr> "Mitchell", "Chelsea Parlett", "mr Akram…
#> $ author_signature             <chr> "#statstiktok", "Just really bad #statsT…
#> $ author_avatar_larger         <chr> "https://p16-sign-va.tiktokcdn.com/music…
#> $ music_author_name            <chr> "angela vasquez \U0001f49f", "Rachel Mar…
#> $ author_stats_following_count <int> 32, 240, 24, 7790, 33, 3130, 2691, 42, 9…
#> $ author_stats_follower_count  <int> 259, 1519, 2752, 12100, 13100, 13700, 29…
#> $ author_stats_heart_count     <int> 45500, 12000, 32100, 122800, 119900, 195…
#> $ author_stats_video_count     <int> 5, 69, 306, 490, 124, 416, 108, 83, 178,…
#> $ author_stats_digg_count      <int> 13800, 785, 8462, 11800, 34000, 284, 149…
#> $ author_stats_heart           <int> 45500, 12000, 32100, 122800, 119900, 195…
#> $ vids_in_sample               <int> 2, 61, 1, 1, 1, 3, 1, 2, 1, 1, 4, 5, 1, …

Any famous tiktoker using #statstiktok?

tiktokers %>% 
  select(author_unique_id, contains("count")) %>% 
  arrange(desc(author_stats_following_count)) %>% 
  rename_all(stringr::str_remove_all, "(author_stats_)") %>%
  arrange(desc(follower_count)) %>%
  slice(1:10) %>%
  mutate(authr_url = paste0("https://www.tiktok.com/@", author_unique_id)) %>% 
  knitr::kable()  %>%
  kableExtra::kable_styling()

author_unique_id	following_count	follower_count	heart_count	video_count	digg_count	authr_url
morgane_fevrier	3130	13700	195900	416	284	https://www.tiktok.com/@morgane_fevrier
easyworkgaming	33	13100	119900	124	34000	https://www.tiktok.com/@easyworkgaming
claredoe	7790	12100	122800	490	11800	https://www.tiktok.com/@claredoe
dimplisimply81	4	9677	150600	471	5296	https://www.tiktok.com/@dimplisimply81
office305	9	3562	35200	178	978	https://www.tiktok.com/@office305
bellasunrae	2691	2907	26300	108	14900	https://www.tiktok.com/@bellasunrae
akrampathan4545	24	2752	32100	306	8462	https://www.tiktok.com/@akrampathan4545
chelseaparlettpelleriti	240	1519	12000	69	785	https://www.tiktok.com/@chelseaparlettpelleriti
ryansscience	42	1464	39200	83	1298	https://www.tiktok.com/@ryansscience
mahdikhdiri	24	1059	14100	753	1429	https://www.tiktok.com/@mahdikhdiri

Some of the tiktokers who used #statstiktok at least once seem to be pretty successful with more than 13700 followers. Maybe their one post post mentioning #statstiktok could have been be responsible for their success (…but most likely not :P). You can also see the strangeness of the digg count. It seems somehow uncorrelated to the other metrics.

Posts over time

When looking at frequency of posts over time, we see a continuous increase in the number of tiktoks mentioning #statstiktok since April 2020 (coinciding with the start of lockdowns in many countries!).

The function ´from_unix´ converts the timestamp in ´create_time´ to actual datetime.

stats_tk %>% 
  mutate(create_date = from_unix(create_time) %>% lubridate::floor_date("day")) %>% 
  count(create_date) %>% 
  mutate(cumsum_n = cumsum(n)) %>% 
  ggplot(aes(create_date, cumsum_n)) + 
  geom_line() +
  theme_minimal() +
  scale_x_datetime(date_labels = "%B %Y")  +
  labs(y = "Number of Posts", x = "")

Check out the most played tiktoks

stats_tk %>% 
  arrange(desc(stats_play_count)) %>% 
  select(id, author_unique_id, stats_play_count) %>% 
  slice(1:10) %>%
  mutate(video_url = paste0("https://www.tiktok.com/@", author_unique_id, "/video/", id)) %>% 
  knitr::kable()  %>%
  kableExtra::kable_styling()

id	author_unique_id	stats_play_count	video_url
6895134839197011206	chelllarson	554100	https://www.tiktok.com/@chelllarson/video/6895134839197011206
6894319168787664133	chelllarson	47200	https://www.tiktok.com/@chelllarson/video/6894319168787664133
6870296141569871109	chelseaparlettpelleriti	40100	https://www.tiktok.com/@chelseaparlettpelleriti/video/6870296141569871109
6871608918494252294	chelseaparlettpelleriti	15200	https://www.tiktok.com/@chelseaparlettpelleriti/video/6871608918494252294
6854302480956673285	chelseaparlettpelleriti	12600	https://www.tiktok.com/@chelseaparlettpelleriti/video/6854302480956673285
6871246394531876102	chelseaparlettpelleriti	11500	https://www.tiktok.com/@chelseaparlettpelleriti/video/6871246394531876102
6818031944715062533	chelseaparlettpelleriti	3755	https://www.tiktok.com/@chelseaparlettpelleriti/video/6818031944715062533
6827002877089697025	akrampathan4545	3386	https://www.tiktok.com/@akrampathan4545/video/6827002877089697025
6854389075894455558	chelseaparlettpelleriti	2603	https://www.tiktok.com/@chelseaparlettpelleriti/video/6854389075894455558
6870863330244840709	chelseaparlettpelleriti	2487	https://www.tiktok.com/@chelseaparlettpelleriti/video/6870863330244840709

Chelsea makes a lot of appearances again!

TikToks description

Each tiktok is usually accompanied with a brief text description. In this description, users typically use hashtags to increase the visibility of their posts.

Unsurprisingly, stats and academia related hashtags are used quite often combination with #statstiktok. We can now use these new hashtags to explore further stats tiktoks.


stats_tiktok %>%
  select(desc) %>%
  mutate(hashtags = stringr::str_extract_all(desc, "#\\w+")) %>%
  tidyr::unnest(hashtags) %>%
  mutate(hashtags = str_to_lower(hashtags)) %>% 
  count(hashtags, sort = T) %>% 
  slice(1:10) %>%
  mutate(hashtag_url = paste0("https://www.tiktok.com/tag/", str_remove(hashtags, "#"))) %>% 
  knitr::kable()  %>%
  kableExtra::kable_styling()

hashtags	n	hashtag_url
#statstiktok	123	https://www.tiktok.com/tag/statstiktok
#statistics	18	https://www.tiktok.com/tag/statistics
#fyp	17	https://www.tiktok.com/tag/fyp
#phdlife	15	https://www.tiktok.com/tag/phdlife
#rstats	13	https://www.tiktok.com/tag/rstats
#academia	8	https://www.tiktok.com/tag/academia
#datascience	7	https://www.tiktok.com/tag/datascience
#science	7	https://www.tiktok.com/tag/science
#bayesian	6	https://www.tiktok.com/tag/bayesian
#duet	6	https://www.tiktok.com/tag/duet

Expanding the data using hashtags


larger_stats_tiktok <- c("statsTikTok", "statistics", "rstats", "datascience") %>%
  purrr::map_dfr(~tk_posts("hashtag", .x, n = 2000)) %>%
  bind_rows(stats_tiktok) %>% # bind_rows the #statstiktok data
  distinct(id, .keep_all = T)

Hashtags

Using the hashtags we discovered earlier, we can now get data for other hashtags (statsTikTok, statistics, rstats, datascience). We obtain metadata on 3474 tiktoks, which can be further analyzed or used for further expansion.

larger_stats_tk <- larger_stats_tiktok %>% 
  select(id, createTime, 
         author_id:author_nickname, 
         author_signature, author_avatarLarger, 
         desc, music_id:authorStats_heart) %>% 
  janitor::clean_names() %>% 
  distinct(id, .keep_all = T)

glimpse(larger_stats_tk)
#> Rows: 3,474
#> Columns: 26
#> $ id                           <chr> "6895134839197011206", "6894319168787664…
#> $ create_time                  <int> 1605398717, 1605208816, 1599615483, 1599…
#> $ author_id                    <chr> "6815076321426326533", "6815076321426326…
#> $ author_unique_id             <chr> "chelllarson", "chelllarson", "chelseapa…
#> $ author_nickname              <chr> "Mitchell", "Mitchell", "Chelsea Parlett…
#> $ author_signature             <chr> "#statstiktok", "#statstiktok", "Just re…
#> $ author_avatar_larger         <chr> "https://p16-sign-va.tiktokcdn.com/music…
#> $ desc                         <chr> "Where are all my fellow H0s at? No HAs …
#> $ music_id                     <chr> "6886831115148036869", "6890224563494472…
#> $ music_title                  <chr> "Ur appreciated ily", "original sound", …
#> $ music_play_url               <chr> "https://sf16-va.tiktokcdn.com/obj/music…
#> $ music_cover_thumb            <chr> "https://p16-sign-va.tiktokcdn.com/tos-m…
#> $ music_cover_medium           <chr> "https://p16-sign-va.tiktokcdn.com/tos-m…
#> $ music_cover_large            <chr> "https://p16-sign-va.tiktokcdn.com/tos-m…
#> $ music_author_name            <chr> "angela vasquez \U0001f49f", "carson", "…
#> $ music_original               <chr> "TRUE", "TRUE", "TRUE", "TRUE", "FALSE",…
#> $ stats_digg_count             <int> 42600, 2869, 2789, 1328, 1019, 638, 531,…
#> $ stats_share_count            <int> 6152, 483, 355, 10, 44, 11, 46, 38, 0, 1…
#> $ stats_comment_count          <int> 965, 75, 56, 27, 43, 2, 45, 16, 32, 10, …
#> $ stats_play_count             <int> 555300, 47400, 40100, 15200, 11500, 3391…
#> $ author_stats_following_count <int> 33, 33, 240, 240, 240, 24, 240, 240, 778…
#> $ author_stats_follower_count  <int> 259, 259, 1519, 1519, 1519, 2752, 1519, …
#> $ author_stats_heart_count     <int> 45600, 45600, 12100, 12100, 12100, 32100…
#> $ author_stats_video_count     <int> 5, 5, 69, 69, 69, 306, 69, 69, 490, 69, …
#> $ author_stats_digg_count      <int> 13800, 13800, 788, 788, 788, 8462, 788, …
#> $ author_stats_heart           <int> 45600, 45600, 12100, 12100, 12100, 32100…

Before closing up, we take a look at the popularity of the considered hashtags. To do so, we filter the 6 queried hashtags and look at the distributions of plays depending on the hashtag. We find out that - in our small and not-at-all random sample -, #statistics is associated with the most viewed, while #rstats is (for now) the least popular hashtag.

larger_stats_tk %>%
  select(desc, matches("^stats")) %>%
  mutate(hashtags = stringr::str_extract_all(desc, "#\\w+")) %>%
  tidyr::unnest(hashtags) %>%
  filter(hashtags %in% c("#statsTikTok", "#statstiktok", "#statistics", "#rstats", "#datascience")) %>%
  mutate(hashtags = forcats::fct_reorder(hashtags, stats_play_count)) %>%
  ggplot(aes(x = hashtags, y = stats_play_count)) + 
  geom_boxplot() + 
  ylim(c(0, 12e3)) +
  theme_minimal() +
  labs(x = "Hashtag", y = "Number of Plays")

Check out the most common music titles usedd

larger_stats_tk %>% 
  count(music_title, music_play_url, sort = T) %>% 
  filter(!str_detect(music_title, "original")) %>% 
  slice(1:10) %>%
  knitr::kable()  %>%
  kableExtra::kable_styling()

music_title	music_play_url	n
Classical Music	https://sf16-sg.tiktokcdn.com/obj/tiktok-obj/ea66fa0925e62cdcbdfbecdd7e30d636.m4a	14
She Share Story (for Vlog)	https://sf16-sg.tiktokcdn.com/obj/tiktok-obj/1641273466152961.mp3	14
The Banjo Beat, Pt. 1	https://sf16-sg.tiktokcdn.com/obj/tiktok-obj/0f584cb7892da90cb0f1ff1b18a9d821.mp3	12
What If (I Told You I Like You)	https://sf16-sg.tiktokcdn.com/obj/tiktok-obj/651c09ce5b9d0d496f78870030dd1459.mp3	10
Banana (feat. Shaggy) [DJ FLe - Minisiren Remix]	https://sf16-sg.tiktokcdn.com/obj/tiktok-obj/f404dd8ad7ef4181d8cbb8a64704c9c0.mp3	8
Renee	https://sf16-sg.tiktokcdn.com/obj/tiktok-obj/e4763633ecd930af26a37bafffe2c6df.mp3	8
Stranger	https://sf16-sg.tiktokcdn.com/obj/tiktok-obj/1630587050952706.mp3	8
Monkeys Spinning Monkeys	https://sf16-sg.tiktokcdn.com/obj/tiktok-obj/a7c68545b238686d79179e25ee990183.m4a	7
Mystery of Love (From the Original Motion Picture “Call Me by Your Name”)		7
Play Date	https://sf16-sg.tiktokcdn.com/obj/tiktok-obj/ee5b572c266d37b749725c708f3a0212.mp3	7

Looks like Classical Music is quite popular with stats tiktok!