Summary information
Study title
Training Data for German Sentiment Analysis of Political Communication (SUF edition)
Creator
Haselmayer, Martin (University of Vienna)
Jenny, Marcelo (University of Innsbruck)
Study number / PID
doi:10.11587/EOPCOB (DOI)
Data access
Information not available
Series
Not available
Abstract
Full edition for scientific use. The dataset contains 125871 sentences extracted from Austrian parliamentary debates and party press releases. Press releases were collected under the auspices of the Austrian National Election Study (AUTNES) and cover 6 weeks prior to each national election 1995-2013. Data from parliamentary debates stem from a random sample of sentences drawn from sessions of the Austrian National Council (1995-2013). The sentiment of the sentences was crowdcoded on a five-point-scale ranging from 0 “Not negative” to 5 “Very strongly negative”. As each sentence has been coded by ten coders, there are multiple codingids for each unitid (sentence).
Topics
Keywords
Methodology
Data collection period
23/01/2014 - 25/11/2016
Country
Austria
Time dimension
Other
Analysis unit
Text unit
Universe
Parliamentary speech
Sampling procedure
Other
Kind of data
Numeric; Text
Data collection mode
Content coding
Funding information
Funder
Austrian Science Fund
Grant number
S10903-G11, S10908-G11
Funder
Vienna Anniversary Foundation for Higher Education
Grant number
H-304565/2015
Access
Publisher
The Austrian Social Science Data Archive
Publication year
2020
Terms of data access
For more Information please visit AUSSDA's web page
Related publications
- Rudkowsky, E., Haselmayer, M., Wastian, M., Jenny, M., Emrich, S., & Sedlmair, M. (2018). More than bags of words: Sentiment Analysis with word embeddings. Communication Methods and Measures, 12(2-3), 140-157.
- Haselmayer, M. & Jenny, M. (2017). Sentiment analysis of political communication: Combining a dictionary approach with crowdcoding. Quality & Quantity, 51(6), 2623-2646.