Kolb, T. E., Sekanina, K., Kern, B. M. J., Neidhardt, J., Wissik, T., & Baumann, A. (2022). The ALPIN Sentiment Dictionary: Austrian Language Polarity in Newspapers. In LREC 2022 Conference Proceedings (pp. 4708–4716). European Language Resources Association. https://doi.org/10.34726/4101
13th Conference on Language Resources and Evaluation (LREC 2022)
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Event date:
20-Jun-2022 - 25-Jun-2022
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Event place:
Marseille, France
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Number of Pages:
9
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Publisher:
European Language Resources Association, Marseille, France
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Peer reviewed:
Yes
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Keywords:
Collaborative Resource Construction; Crowdsourcing; Digital Humanities; Document Classification; Text Categorisation; Information Extraction; Information Retrieval; Statistical and Machine Learning Methods; Tools; Systems; Applications
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Abstract:
This paper introduces the Austrian German sentiment dictionary ALPIN to account for the lack of resources for dictionary-based sentiment analysis in this specific variety of German, which is characterized by lexical idiosyncrasies that also affect word sentiment. The proposed language resource is based on Austrian news media in the field of politics, an austriacism list based on different resources and a posting data set based on a popular Austrian news media. Different resources are used to increase the diversity of the resulting language resource. Extensive crowd-sourcing is performed followed by evaluation and automatic conversion into sentiment scores. We show that crowd-sourcing enables the creation of a sentiment dictionary for the Austrian German domain. Additionally, the different parts of the sentiment dictionary are evaluated to show their impact on the resulting resource. Furthermore, the proposed dictionary is utilized in a web application and available for future research and free to use for anyone.
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Project title:
Dynamische Sentimentanalyse als emotionaler Kompass für die digitale Medienlandschaft: MA 7 – 737909/19 (Stadt Wien)