Most Retweeted

mm <- read.csv("file:///C:/Users/s-das/Syncplicity Folders/MyProjects_IMP/MY_Papers_V2/TRB 2020/00000000 FINALz/0010 nlp Twitter VisionZero/visionzero06192019_16191.csv")
mm

##                                                                                                                                           text
## 1 RT @jen_keesmaat: Cities that are safe for everyone, have *literally* been redesigned to be safe, particularly for pedestrians and cyclistsâ€¦
## 2 RT @MetCycleCops: Please be aware that Mechanically Propelled Scooters are illegal and canâ€™t be used on roads. If you know someone that useâ€¦
## 3 RT @Dale_Bracewell: â€œAfter analyzing traffic crash data over a 13-year period... having a protected bike facility in a city would result inâ€¦
## 4 RT @cityoftoronto: At a red light, bikes should stop inside the green bike box and cars should stop behind it. Bicycles go first when traffâ€¦
##    screenName retweetCount
## 1 darweesh821          418
## 2  MPSHammFul          193
## 3   geeemmpee          141
## 4   hexturtle          133

names(mm)

## [1] "text"         "screenName"   "retweetCount"

library(tidytext)

## Warning: package 'tidytext' was built under R version 3.5.3

# plot points labelled with tweet text
plot_tweets <- function(.df, y) {
  y <- enquo(y)
  .df %>% 
    mutate(text = str_wrap(text, 50)) %>% 
    ggplot(aes(x = fct_inorder(screenName), y = !!y)) + 
    geom_point(color = "#0172B1", size = 2) +
    geom_label_repel(
      aes(label = text), 
      size = 4, 
      force = 4, 
      nudge_y = 3, 
      point.padding = .5
    ) +
    theme_minimal(14)
}


library(dplyr)

## Warning: package 'dplyr' was built under R version 3.5.3

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

library(ggrepel)

## Warning: package 'ggrepel' was built under R version 3.5.3

## Loading required package: ggplot2

library(stringr)
library(forcats)
mm %>% 
  arrange(desc(retweetCount)) %>%
  plot_tweets(retweetCount) +
  labs(x = "twitter user", y = "n retweets")+theme_bw(base_size = 16)