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Instagram Posts by German Parties

  • 1. University of Regensburg

Published: August 20, 2024

Version v1

Description

The dataset contains Instagram posts by candidates from the Bavarian state election campaigns of the CSU, Freie Wähler, AFD, Grüne, SPD, FDP and Linke parties. An attempt was made to find an Instagram profile for all 1134 people standing for election, and this was achieved for 632 of them. The state and parliamentary group accounts of the listed parties were also included. For each profile found, all posts on the profile overview page were collected for the period under investigation. Reels that do not appear there or stories are not included in the data set. In addition to the image and caption, further metadata such as interaction figures, hashtags and time of publication were saved for each post. In addition, text modules contained in the image were extracted and captions with a short image description were also generated for further machine processing.

N = 46,897
Survey period: 01.04.2023 - 08.10.2023

Files

final_df_pm.csv

Files (41.3 MB)

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md5:84335c732baa451bced04a390b81df0e
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Variables

Name Description
id Unique identifier for post
body Text content of the post
author Username of the author
name Full name of the author
timestamp Date and time of post
type Media type (e.g., video, photo)
url Link to the post
hashtags Hashtags used in the post
likes Number of likes received
comments Number of comments received
num_media Count of media items
location Location associated with the post
location_latlong Latitude and longitude of location
location_city City name of the location
unix_timestamp Timestamp in Unix format
ocr_text Extracted text from image
file File associated with the post
party Political party affiliation
caption Image caption description
follower Number of followers of the author
interaction_rate Interaction rate of the post

Details

Resource type Open dataset
Title Instagram Posts by German Parties
Creators
  • Berg, Jakob1
  • Research Fields Political Science Business Administration Communication Sciences
    Size 0.41 GB
    Formats Comma-separated values (CSV) (.csv)
    License(s) Please cite when using the dataset
    Dates of collection April 1, 2023 ; October 8, 2023