Twitter Data Analytics of Announcement of Team India for ICC T20 World Cup

I have to start off by admitting that my domain knowledge on the subject (BCCI and Indian Cricket Team) is not what it used to be. However, the announcement of the Indian Cricket Team roster for the ICC T20 World Cup on September 12th, 2022 left many of the folks I follow in social media in bad taste. Most of the posts were surrounding how the team selection was not merit based (a particular highlight being the exclusion of #SanjuSamson from the roster). I found this an interesting topic to pursue and started collecting twitter data from the 12th of September, till today Oct23rd. 325,847 tweets later this is what I have. I did not collect the data for the lull period of Sept 27th and Oct 4th.

There was a lot of spurious data that was removed through R and a further filtering was done on the source to make sure bot entries did not make through into the data. There was quite a bit of manual stemming and removal of stop words in order to filter out the noise (BigBoss, Movie advertisements etc to name a few). 

Primary topics and observations are as below. The visualizations to support are as attached:


1. Volume of twitter activity pertaining to #T20WorldCup2022 #BCCI and #TeamIndia
a. The team announcement too generated some heavy traffic from twitterites with close to 10000 tweets. The sentiments however spread of the days following the team announcement.
b. As expected Twitter exploded with a lot of activity following Team India's first match. This day alone recorded over 100,000 tweets on the topic.
c. Verified twitter users showed an overall negative sentiment trend when compared to the posts made by non-verified users. This data was already cleaned for spurious/bot sources which makes me believe that the common man (non verified accounts) tend to maintain a positive outlook when compared to the verified account holders. This observation begs for a deeper study into the matter. 
2. Primary topics of discussions in the twitter world over the course of time. 
a. Prior to India's opening match, Sanju Samson appeared the most in all tweets. This verifies the suspicion that fans did not take his inclusion lightly. 
b. World cloud shows that Twitter world went abuzz after King Kohli's return to form and the huge win for team India. No rocket science there as the data just showed what most fans felt. Highlighted are the variants of the Kohli effect.
3. How the general sentiments changed over time. 
a. Sep 14th : Indian Cricket Team for ICC T20 World Cup Announce. The sentiments prior to the WC was already on the negative side, thanks to the showing at Asia Cup
b. Sep 14 - 17th : Despite the tremendous push from fans for the inclusion of Sanju Samson, the overall sentiments remained positive. The fans were backing the team to perform well. The Australia series helped.
c. Oct 4th : The massive loss against SA pulled back the sentiments over to the negative side. 
d. Oct 23rd: Despite the huge win in the opening match the sentiments remained somewhat non explosive. This shows a huge disadvantage of text analytics. We see that there was a very strong and opposite force of negative sentiments expressed by Pakistan fans with tweets posted with the same hashtags.

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