Papers by Erik Körner
Casting the Same Sentiment Classification Problem (2021.findings-emnlp)
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| Challenge: | Identifying the stance of an argument towards a topic is a fundamental problem in computational argumentation. |
| Approach: | They propose a task where text users are asked to determine if they have the same sentiment . they aim to enable a more topic-agnostic sentiment classification by using Yelp data . |
| Outcome: | The proposed task achieves an accuracy above 83% for category subsets across topics and 89% on average. |
On Classifying whether Two Texts are on the Same Side of an Argument (2021.emnlp-main)
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| Challenge: | Existing approaches to same side stance classification (S3C) require domain knowledge and semantic inference to solve the task. |
| Approach: | They propose to use same side stance classification to predict whether two arguments argue for the same stance for a given pair of arguments. |
| Outcome: | The proposed model fails to generalize both within and across topics and domains when adjusting the sampling strategy to a more adversarial scenario. |
Typical Sentences as a Resource for Valence (2020.lrec-1)
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| Challenge: | Verb valence information can be derived from corpora by using subcorpora of typical sentences that are constructed in a language independent manner based on frequent POS structures. |
| Approach: | They propose a method which allows one to 'strip' the POS-pattern of a sentence with various types of adjuncts down to those items representing the valence frame instantiated by the verb in question. |
| Outcome: | The proposed approach can be used to construct valence pairs for a bilingual polyval dictionary using the Norwegian valance dictionary NorVal. |