Papers by Liane Reiners
HUMAN: Hierarchical Universal Modular ANnotator (2020.emnlp-demos)
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| Challenge: | HUMAN is a web-based annotation tool that covers a variety of annotation tasks on textual and image data. |
| Approach: | They propose a web-based annotation tool that covers a variety of annotation tasks on textual and image data. |
| Outcome: | HUMAN covers a variety of annotation tasks on textual and image data and uses an internal deterministic state machine to chain different tasks in an interdependent manner. |
Placing M-Phasis on the Plurality of Hate: A Feature-Based Corpus of Hate Online (2022.lrec-1)
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Dana Ruiter, Liane Reiners, Ashwin Geet D’Sa, Thomas Kleinbauer, Dominique Fohr, Irina Illina, Dietrich Klakow, Christian Schemer, Angeliki Monnier
| Challenge: | HS-related corpora over-simplify the phenomenon of hate by labelling user content with binary classes, e.g., hate/neutral . this ignores the complex and subjective nature of HS, which limits the real-life applicability of classifiers trained on these corporales. |
| Approach: | They present a corpus of 9k German and french user comments from migration-related news articles. |
| Outcome: | The proposed corpus is annotated with 23 features that become descriptors of various types of speech, ranging from critical comments to implicit and explicit expressions of hate. |