Posted: December 3rd, 2015

TwitterR

For this project you will use twitter data to determine if two phone platforms have different “like” and “hate” ratings. The first platform is “Android” and the other is “iPhone”. Complete the following tasks.

Create two dictionaries with at least 10 words each. One dictionary is for “positive” statements for the “like” category and the other dictionary is for “negative” statements for the “hate” category. Clearly comment your code on which dictionary is which. (20 pts. One point for each word 🙂 )
Pull 10,000 tweets for Android and determine the number of “like” and “hate” ratings. (10 points)
For the android tweets use the R function prop.test() to create a confidence interval for the proportion who “like” and another confidence interval for the proportion who “hate” android. (15 points)
Pull 10,000 tweets for iPhone and determine the number of “like” and “hate” ratings. (10 points)
For the iPhone tweets use the R function prop.test() to create a confidence interval for the proportion who “like” and another confidence interval for the proportion who “hate” android. (15 points)
Use the prop.test() function in R to perform a two sample test on proportions to see if the proportion who “like” is the same across the two platforms (15 points)
Use the prop.test() function in R to perform a two sample test on proportions to see if the proportion who “hate” is the same across the two platforms (15 points)
You will submit one file of only R code.

Clearly comment your code.

I will have my account logged into twitter.

Be sure to tell me where I should begin running your code by commenting out any lines that I should not need. As I will be running the whole file.

Your code should be dynamic in that I should get a different answer for the items than you did as I will pull my tweets at a different time. This means you should not hard code any numbers for “like” or “hate” for each.

Here is a YouTube video to help you use prop.test(). https://www.youtube.com/watch?v=OheuwK4JKPk

I will attach my R codes from the lecture
you need to have a twitter account to this project.