library(stringr)
library(rtweet)
library(httpuv)
library(dplyr)
library(ggplot2)
library(pacman)
library(tidytext)
library(tidyverse)
library(textdata)
library(ggpubr)
library(ggwordcloud)
library(knitr) 
library(kableExtra)

Set up API authorization

my_token <- create_token(app = app,
                         consumer_key = consumer_key,
                         consumer_secret = consumer_secret,
                         access_token = access_token,
                         access_secret = access_secret)

Data Import from Twitter

I conducted a search of tweets utilizing the hashtag #covidvaccine. I include the 8,000 most recent tweets not including replies and removing retweets and limited to tweets in English.

I conducted this search to explore current discussions around the COVID-19 vaccine, including trust or distrust and overall sentiments about the impending implementation of a vaccine.

twts_vaccine <- search_tweets("#covidvaccine", 
                        n = 8000,
                        include_rts = FALSE,
                        `-filter` = "replies",
                        lang = "en")
## Warning: Rate limit exceeded - 88
## Warning: Rate limit exceeded

Summary Table

Summary table

twts_vaccine %>% 
  select(screen_name, text, favorite_count) %>%
  arrange(desc(favorite_count)) %>%
  top_n(20) %>% kable(caption = "Summary of tweets by most favorited", col.names = c('Screen Name', 'Tweet', 'Favorited Count')) %>% 
   kable_styling(bootstrap_options = c("striped", "hover", "condensed"))
Summary of tweets by most favorited
Screen Name Tweet Favorited Count
ISayPorter BREAKING: #CovidVaccine refrigerated-delivery contract worth £280 million awarded to ice cream man who once sold Matt Hancock a 99 with two Flakes. 3068
JenArnoldMD I am ready &amp; will get the #CovidVaccine as soon as I am eligible! As a high risk healthcare provider I am motivated to protect others &amp; myself. I understand the science, know it’s safe &amp; effective #COVID19 #besafe #CantWait #StopTheSpread https://t.co/srutSvZaP4 1493
sapiofoxy Funny how GPs couldn’t see you for months on end but now they’re willing to see you first thing in the morning for a vaccination 🙄❌❌❌ #GPs #NHS #Doctors #healthcare #CovidVaccine #COVID19 832
OliviaTroye #PeoplesVaccine Thank you #BidenHarris for caring about all Americans. And thank you @Alyssa_Milano for this thoughtful op-ed on the need to ensure access for all to the #CovidVaccine - https://t.co/lwG2UDzcJu https://t.co/4QFmu58e6U 491
PintSizedFarmer

Just been on the phone to my hero GP brother who is working out how to give the #CovidVaccine to 7.5k patients.

I said he needs a Sterimatic system plus sheep race. If he throws the empty vaccine bottles behind his head we reckon he could inject 100 people in one hour. #helpful https://t.co/wHb3jkiQCo 		489
SupriyaShrinate On @news24tvchannel at 7 pm #COVID19 #CovidVaccine 361
LNBDublin We are told constantly that the virus doesn’t respect borders, that it doesn’t discriminate. However, sadly for the Palestinians, the Israeli Government does discriminate. The Irish Government must ensure Palestinians are included in the rollout of the vaccine. #CovidVaccine https://t.co/UUiXNyc8WK 351
jhalcrojohnston

When you’re an SNP MP and actually sound a bit miffed that the UK is the first country to approve a #CovidVaccine

Bit petty, @neilgraysnp. #ThankYouUK https://t.co/NY3p9UnVX3 		329
ndtv "What Does PM Stand By’’: Rahul Gandhi On Centre’s Stand On #CovidVaccine https://t.co/mFqAaiJOkA https://t.co/gX96zQS1Yw 311
frankendodo So to the Leader of the House of Commons, and the Health Secretary we can now add the Universities Minister as lying about Brexit &amp; the vaccine - they have not apologised, or deleted their tweets. How hugely concerning. #Covid19UK #CovidVaccine #Brexit
https://t.co/SWOuynchzB https://t.co/cVATqiMJ6S 		310
amyismall Just booked my #CovidVaccine I for one don’t want to go through #covid hell all over again #longhaulers we are not immune to this - take it when offered 291
LVNancy

3 former Presidents are willing to get #CovidVaccine on camera, in order to raise public confidence….

The same 3 responsible for Empowering #China 80% of active ingredients in medicines come from #China

https://t.co/MkKoJMjKNk

https://t.co/W01t9UKbPo

https://t.co/9mHqwJPHCF https://t.co/sCLXepUWEn 		266
oCCultRebel

NONE OF THEM Will take the Real #CovidVaccine

All for show https://t.co/hYaHU9qibK 		263
OffGuardian0 Are you willing to risk “unknown fertility impacts” for a vaccine against a virus with 99.8% survival rate? #CovidVaccine #coronavirus https://t.co/6NRbsenpVM 258
mat_schmaltz O’Toole and Sloan, making sure Canadians are confused as possible on #CovidVaccine. https://t.co/je6b4qtAJm 255
NicoleB_MD

You know that moment when you’re so proud of your child you could just burst…I had one of those moments today 🥰

#CovidVaccine #VaccinesSaveLives @CincyChildrens @DrPaulOffit @DrToddWo https://t.co/M5uPZGFGeY 		240
KrutikaKuppalli I not only love that @BarackObama @BillClinton &amp; #GeorgeBush said they will get the #CovidVaccine (on camera) when deemed safe BUT will do so AFTER administered to priority populations - emphasizing fair &amp; equitable distribution of #vaccine. #leadership https://t.co/Q4ZlLjV1m4 224
KiranKS

Karnataka has identified 29,431 #CovidVaccine distribution centers. 10,008 staff identified. 2,855 cold storage centers established.

About 1800 people getting vaccine for test purposes. Bengaluru, Shivamogga and Ballari districts will get test vaccines first.

Fantastic prep! 		219
arbab_jahangir Discussion with Dr. Faisal Sultan on #Coronaviruspakistan #CovidVaccine #COVIDー19 #mdcat2020errors #Mdcatwasoutofsyllabus in #busbohathogaya with @arbab_jahangir https://t.co/790ej9LXIZ 204
mekarentaylor Hairdresser telling me how she won’t be having the covid vaccine because you don’t know what’s in it with lips full of filler and a forehead full of Botox. #CovidVaccine 185

Concurrent Hashtags

Display table of top 30 hastags used in conjunction with #CovidVaccine

twts_vaccine %>% 
  unnest_tokens(hashtag, text, "tweets", to_lower = FALSE) %>%
  filter(str_detect(hashtag, "^#"),
         hashtag != "#covidvaccine") %>%
  count(hashtag, sort = TRUE) %>%
  top_n(30) %>% kable(col.names = c('Hashtag', 'Number of Uses')) %>%
  kable_styling()
Hashtag Number of Uses
#CovidVaccine 4589
#COVID19 1016
#COVIDー19 691
#vaccine 322
#coronavirus 252
#COVID 200
#Pfizer 163
#Covid19 159
#vaccination 87
#COVIDvaccine 83
#COVIDVaccine 80
#CoronavirusVaccine 78
#Pfizervaccine 69
#pandemic 66
#vaccines 66
#VaccinesWork 66
#covid 63
#covid19 60
#UK 60
#cdnpoli 59
#COVIDSecondWave 59
#antivaxxers 50
#CoronaVirusUpdates 49
#FightBack 49
#WearAMask 47
#Covidvaccine 46
#COVIDIOTS 44
#Canada 42
#Coronavirus 39
#Covid19UK 39

This shows many concurrent uses of other COVID-19 or vaccine hashtags, but additionally there is the use of named vaccine distributors such as Moderna or Pfizer. There is also some language around anti-vaccination and the efficacy of vaccines.

Hashtag timeline

Plot the timeline of recent #covidvaccine tweets

ts_plot(twts_vaccine, "hours") +
  labs(x = "Date", y = "Number of Tweets",
       title = "Frequency of tweets with a #covidvaccine hashtag",
       subtitle = paste0(format(min(twts_vaccine$created_at), "%d %B %Y"), " to ", format(max(twts_vaccine$created_at),"%d %B %Y")),
       caption = "Data collected from Twitter's API via rtweet") +
  theme_minimal()

Words in unique tweets

unique_tweets<-distinct(twts_vaccine, text, .keep_all = TRUE)


reg <- "([^A-Za-z\\d#@']|'(?![A-Za-z\\d#@]))"

vaccine_words <- unique_tweets %>% select(status_id, text) %>%
  filter(!str_detect(text, '^"')) %>%
  mutate(text = str_replace_all(text, "https://t.co/[A-Za-z\\d]+|&amp;", "")) %>%
  unnest_tokens(word, text, token = "regex", pattern = reg) %>%
  filter(!word %in% stop_words$word,
         str_detect(word, "[a-z]"))


vaccine_words %>% group_by(word) %>% summarize(n = n()) %>% arrange(desc(n)) %>% top_n(20)
## # A tibble: 20 x 2
##    word              n
##    <chr>         <int>
##  1 #covidvaccine  4912
##  2 vaccine        1578
##  3 #covid19       1176
##  4 #covid         1043
##  5 covid           714
##  6 people          489
##  7 #vaccine        358
##  8 vaccines        335
##  9 #coronavirus    294
## 10 uk              241
## 11 dr              240
## 12 news            189
## 13 #pfizer         179
## 14 health          161
## 15 safe            156
## 16 coronavirus     153
## 17 pfizer          151
## 18 line            148
## 19 government      147
## 20 vaccination     145

Sentiment analysis

nrc <- get_sentiments("nrc") %>%
  select(word, sentiment)
head(nrc)
## # A tibble: 6 x 2
##   word      sentiment
##   <chr>     <chr>    
## 1 abacus    trust    
## 2 abandon   fear     
## 3 abandon   negative 
## 4 abandon   sadness  
## 5 abandoned anger    
## 6 abandoned fear
vaccine_words_sentiments <- vaccine_words %>% inner_join(nrc, by = "word")

vaccine_words_sentiments %>% group_by(sentiment) %>% summarize(n = n()) %>% arrange(desc(n))
## # A tibble: 10 x 2
##    sentiment        n
##    <chr>        <int>
##  1 positive      6421
##  2 negative      3373
##  3 trust         3112
##  4 anticipation  2429
##  5 fear          2390
##  6 joy           1470
##  7 sadness       1468
##  8 anger         1415
##  9 surprise       934
## 10 disgust        918

Vizualizing Sentiments

Pie chart displaying sentiment counts

pie_words<- vaccine_words_sentiments %>%
  group_by(sentiment) %>% 
  tally %>% 
  arrange(desc(n)) 

ggpubr::ggpie(pie_words, "n", label = "sentiment", 
                fill = "sentiment", color = "white", 
                palette = "Spectral")

The pie chart shows a range of sentiments around a pending COVID-19 vaccine as expected. Looking further into sentiments regionally and over time would be interesting when looking forward to vaccine roll-out.