| Authors |
Jacobo Rouces Nina Tahmasebi Lars Borin Stian Rødven Eide |
|---|---|
| Published in | To appear in Language Resources and Evaluation Conference (LREC2018) |
| Publication year | 2018 |
| Published at |
Department of Literature, History of Ideas, and Religion Department of Swedish |
| Language | en |
| Subject categories | Language Technology (Computational Linguistics), Languages and Literature |
We create a gold standard for sentiment annotation of Swedish terms, using the freely available SALDO lexicon and the Gigaword corpus. For this purpose, we employ a multi-stage approach combining corpus-based frequency sampling, direct score annotation and Best-Worst Scaling. In addition to obtaining a gold standard, we analyze the data from our process and we draw conclusions about the optimal sentiment model.
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