Question 1

What is the difference in the number of tweets towards Walmart and Target over the course of the day? I will collect 1000 tweets that conatain @’s towards Target or Walmart,I will use the created_at and full_text columns so I can see the @’s and use the time to create a graph.

From the data collected, it looks like Target has more tweets directed at them than Walmart does, but I think that is mainly due to the spike between hours 9 and 11, after that spike it decreased. I think that without that spike, Walmart would have more tweets that Target does.

Question 2

How does the number of tweets containing #MWII compare to the number of tweets using #Overwatch2? For this I will only be using the full_text column as it contains the hashtags, and I am only inserted in the number of tweets.

## # A tibble: 2 × 2
##   OW2   tweets
##   <lgl>  <int>
## 1 FALSE    858
## 2 TRUE    1142

Of the 2000 tweets collected 1142 contained #Overwatch2, while 858 tweets contained #MWII. I think that this results makes sense, Overwatch 2 was released several weeks ago and MWII will come out in a few days, My guess would be that if I ran this again next week, there would be more tweets with #MWII than #Overwatch2.

Question 3

Is there a difference in the number of tweets with bacon and sausage in them, if there is, what is the difference?

I was running out of ideas and hungry. Also, bacon and sausage can be considered complementary or substitute products to each other.

## # A tibble: 2 × 2
##   Bacon tweets
##   <lgl>  <int>
## 1 FALSE   1900
## 2 TRUE     600

I was very disappointed with the results, of the 2500 tweets collected, 1900 contained the word sausage, while only 600 contained the word bacon.One thing that I noticed while looking at the data was the problem where people had bacon in their name, I saw a tweet about Kevin Bacon and a politician who’s name was also bacon. Another thing that I found interestig was that there was no overlap, I had guessed that there would be some tweets that contained both but there were not, unless it was a misteak on my end.

I also looked at the time of tweet to see if it would be concentrated in the morning, they are pretty concentrated from hours 17 to 21, I don’t remember what time zone the created_ar column uses, but I would imagine those are hours in the morning.