https://github.com/mkearney/resist_oped

🕵🏽‍♀️ Identifying the author behind New York Time’s op-ed from inside the Trump White House.
https://github.com/mkearney/resist_oped

Last synced: about 1 month ago
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🕵🏽‍♀️ Identifying the author behind New York Time’s op-ed from inside the Trump White House.

• Host: GitHub
• URL: https://github.com/mkearney/resist_oped
• Owner: mkearney
• Created: 2018-09-05T23:27:03.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2018-09-10T16:47:08.000Z (over 6 years ago)
• Last Synced: 2024-05-19T14:22:06.925Z (8 months ago)
• Language: R
• Homepage: https://github.com/mkearney/resist_oped
• Size: 1.77 MB
• Stars: 201
• Watchers: 14
• Forks: 41
• Open Issues: 0
• Metadata Files:
  • Readme: README.Rmd

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README

        
---

output: 

  github_document: 

    df_print: kable

---

```{r setup, include = FALSE}

knitr::opts_chunk$set(

	echo = FALSE,

  collapse = TRUE,

  comment = "#>"

)

library(tidyverse)

```

# resist_oped

🕵🏽

♀️ Identifying the author behind New York Time's op-ed from [*inside the Trump White House*](https://www.nytimes.com/2018/09/05/opinion/trump-white-house-anonymous-resistance.html).

```{r}

## corr matrix

mat <- readRDS("data/mat.rds")

## plot estimates

est <- cor(t(mat))[, "op-ed"] %>% sort()

```

I compared the paragraphs of the op-ed to tweets posted to timelines by members of the Cabinet. Here's what I found:



## Method

I've written an [explanation post](resist-oped-text-similarity.md), which I expect to publish at TBD outlet.

## Code/Estimates

See the [analysis](R/01-features.R) (to replicate, btw, start here as well) and [visualization](R/02-plot.R) code.

Download the [raw estimates here](estimates.csv) or view the results below:

```{r}

## print matrix

results <- cor(t(mat))[, "op-ed"] %>% sort(decreasing = TRUE) %>% data.frame(author = names(.), r = ., stringsAsFactors = FALSE, row.names = NULL) %>% `names<-`(c("author", "r"))

write.csv(results, "estimates.csv", row.names = FALSE)

results

```