Papers by Matthias Matti
GRUBERT: A GRU-Based Method to Fuse BERT Hidden Layers for Twitter Sentiment Analysis (2020.aacl-srw)
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| Challenge: | GRUBERT learns to map the different BERT hidden layers to fused embeddings . aims to achieve high accuracy on Twitter sentiment analysis task . |
| Approach: | They propose a GRU-based architecture that learns to map BERT hidden layers to fused embeddings to capture tweets' full extent. |
| Outcome: | The proposed method outperforms well-known embeddings and heuristics on Twitter sentiment analysis. |
Crowdsourcing a Large Corpus of Clickbait on Twitter (C18-1)
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Martin Potthast, Tim Gollub, Kristof Komlossy, Sebastian Schuster, Matti Wiegmann, Erika Patricia Garces Fernandez, Matthias Hagen, Benno Stein
| Challenge: | Clickbait is a nuisance on social media. |
| Approach: | a corpus of 38,517 annotated Twitter tweets was constructed to detect clickbait . the corpus was annotating tweets on 4-point scale by five annotators at Amazon's Mechanical Turk . |
| Outcome: | The corpus of 38,517 annotated Twitter tweets was used to evaluate 12 clickbait detectors submitted to the Clickbait Challenge 2017 . |