twitter02

textmining

twitter

Published

October 28, 2022

Exercise

Laden Sie die neuesten Tweets an karl_lauterbach herunter - und zwar so viele wie auf einmal möglich.

Solution

library(tidyverse)

── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ dplyr     1.1.3     ✔ readr     2.1.4
✔ forcats   1.0.0     ✔ stringr   1.5.0
✔ ggplot2   3.4.4     ✔ tibble    3.2.1
✔ lubridate 1.9.3     ✔ tidyr     1.3.0
✔ purrr     1.0.2     
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()
ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

library(rtweet)


Attaching package: 'rtweet'

The following object is masked from 'package:purrr':

    flatten

Einloggen bei Twitter; zuerst die Credentials bereithalten:

source("/Users/sebastiansaueruser/credentials/hate-speech-analysis-v01-twitter.R")

auth <- rtweet_app(bearer_token = Bearer_Token)

Aus der Hilfe zu search_tweets:

Description
Returns Twitter statuses matching a user provided search query. ONLY RETURNS DATA FROM THE PAST 6-9 DAYS.

Tweets an Karl Lauterbach suchen:

karl_tweets <- search_tweets(q = "@karl_lauterbach", n = 150000, retryonratelimit = TRUE)

Wir könnten n auch auf Inf setzen, aber, da wir auf das Refreshen des Rate Limits warten müssen, könnte sehr lange dauern. Daher nehmen wir hier nur einen kürzeren Wert.

dim(karl_tweets)

[1] 18000    43

head(karl_tweets)

# A tibble: 6 × 43
  created_at               id id_str      full_…¹ trunc…² displ…³ entities     metad…⁴
  <dttm>                <dbl> <chr>       <chr>   <lgl>     <dbl> <list>       <list> 
1 2022-10-23 13:30:18 1.58e18 1584145185… "Bei ⁦@… FALSE       122 <named list> <df>   
2 2022-10-22 18:34:37 1.58e18 1583859379… "Es is… FALSE       263 <named list> <df>   
3 2022-10-22 17:56:39 1.58e18 1583849826… "Die S… FALSE       215 <named list> <df>   
4 2022-10-24 08:10:35 1.58e18 1584427113… "Zu we… FALSE       219 <named list> <df>   
5 2022-10-24 08:10:35 1.58e18 1584427113… "RT @K… FALSE       140 <named list> <df>   
6 2022-10-24 08:10:25 1.58e18 1584427072… "RT @U… FALSE       139 <named list> <df>   
# … with 35 more variables: source <chr>, in_reply_to_status_id <dbl>,
#   in_reply_to_status_id_str <chr>, in_reply_to_user_id <dbl>,
#   in_reply_to_user_id_str <chr>, in_reply_to_screen_name <chr>, geo <list>,
#   coordinates <list>, place <list>, contributors <lgl>, is_quote_status <lgl>,
#   retweet_count <int>, favorite_count <int>, favorited <lgl>, retweeted <lgl>,
#   possibly_sensitive <lgl>, lang <chr>, quoted_status_id <dbl>,
#   quoted_status_id_str <chr>, quoted_status <list>, retweeted_status <list>, …
# ℹ Use `colnames()` to see all variable names

Categories:

textmining
twitter