Martin Haselmayer
Data

The German Political Sentiment Dictionary

Haselmayer, Martin and Marcelo Jenny (2020). The German Political Sentiment Dictionary (SUF edition). AUSSDA, V1. doi:10.11587/7PFLIU

The dataset contains a German-language sentiment dictionary of 5,001 negative words and their associated sentiment strength on a five-point-scale from 0 (not negative) to 4 (very strongly negative).

Data and documentation can be downloaded for scientific use at AUSSDA (Austrian Social Science Data Archive)


Related publication:

Haselmayer, Martin and Marcelo Jenny. (2017). Sentiment Analysis Of Political Communication: Combining a dictionary approach with crowdcoding. Quality & Quantity 51(6): 2623-2646. doi:10.1007/s11135-016-0412-4


Training Data for German Sentiment Analysis of Political Communication

Haselmayer, Martin, and Marcelo Jenny (2020). Training Data for German Sentiment Analysis of Political Communication (SUF edition). AUSSDA, V1. doi:10.11587/EOPCOB

The dataset contains 125,871 sentences extracted from Austrian parliamentary debates and party press releases (1995-2013). The sentiment of the sentences was crowdcoded on a five-point-scale ranging from 0 “Not negative” to 5 “Very strongly negative”.

Data and documentation can be downloaded for scientific use at AUSSDA (Austrian Social Science Data Archive)


Related publications:

Rudkowsky, Elena, Martin Haselmayer, Matthias Wastian, Marcelo Jenny, Stefan Emrich, and Michael Sedlmair (2018). More than bags of words: Sentiment Analysis with word embeddings. Communication Methods and Measures 12(2-3): 140-157. DOI: 10.1080/19312458.2018.1455817

Haselmayer, Martin and Marcelo Jenny. (2017). Sentiment Analysis Of Political Communication: Combining a dictionary approach with crowdcoding. Quality & Quantity 51(6): 2623-2646. doi:10.1007/s11135-016-0412-4


All data were collected under the auspices of the Austrian National Election Study (AUTNES).