# Welcome!
This is the OSF page Matthew Jordan's Master's thesis in Experimental Psychology at Oxford University, titled "Mean Tweets: The Role of Emotion in
the Spread of Moral Ideas on Twitter."
---
This project is a replication of [(Brady et al., 2017)][1], a paper out of NYU that demonstrated that the presence of moral-emotional words in tweets makes them more likely to be retweeted. <br> <br>
In the spirit of open science and reproducilibty, I have made all my code and data available on this page. The main data set is [filtered_all.RDS][4], located in the **Cleaned Files** folder. You can view these data with [RStudio][2] by entering the following: <br><br>
```
setwd("/Downloads/Tweets") # Wherever you put the file
filtered_all <- readRDS("filtered_all.RDS")
```
<br>
You can now explore this big data set and re-run the analyses I performed. All of the scripts I used to analyze the data are located in the **R Code** folder.
## Collecting Your Own Data
You can collect your own tweets from Twitter's API and run the same analyses to examine moral/emotional language. The steps are as follows: <br><br>
1. Follow [these instructions][3] to create a Twitter App, which you'll need to use `rtweet` and gather data.
2. Modify `Matthew_Thesis_Data_Collection.R` with your personal Twitter App information.
3. Specify keywords and an amount of time to collect for.
<br>
And you're off! The `rtweet` package saves its output as `.JSON` files. You can now use [Matthew_Thesis_Data_Preparation.R][5] to parse these files and turn them into `.csv` files.
<br>
The `.csv` files can in turned be read into R and analyzed using the functions in [Matthew_Thesis_Data_Analysis.R][6]. Before you know it, you'll have pretty much completed a Master's thesis.
<br>
Note that in order to use these two functions, you will also have to download the "Helper" files, which contain useful functions.
[1]: https://osf.io/59uyz/
[2]: https://www.rstudio.com/
[3]: https://github.com/mkearney/rtweet
[4]: https://osf.io/cwbhm/
[5]: https://osf.io/5b9wm/
[6]: https://osf.io/nrgz9/
