Papers by Farhana Ferdousi Liza
Room to Glo: A Systematic Comparison of Semantic Change Detection Approaches with Word Embeddings (D19-1)
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| Challenge: | Word embeddings are increasingly used for automatic detection of semantic change, but a robust evaluation and systematic comparison of the choices involved has been lacking. |
| Approach: | They propose a new evaluation framework for semantic change detection using whole time series and a Twitter dataset spanning 5.5 years. |
| Outcome: | The proposed framework shows that using whole time series is preferable over continuously trained embeddings for long time periods and that the reference point matters. |
The Causal News Corpus: Annotating Causal Relations in Event Sentences from News (2022.lrec-1)
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Fiona Anting Tan, Ali Hürriyetoğlu, Tommaso Caselli, Nelleke Oostdijk, Tadashi Nomoto, Hansi Hettiarachchi, Iqra Ameer, Onur Uca, Farhana Ferdousi Liza, Tiancheng Hu
| Challenge: | Existing annotation guidelines for event causality focus on only explicit relations or clauses. |
| Approach: | They propose an annotation schema for event causality that addresses these concerns . they annotated 3,559 event sentences from protest event news with labels on whether it contains causal relations or not. |
| Outcome: | The proposed annotation schema for event causality addresses these concerns . it performs well with 81.20% F1 score on test set and 83.46% in 5-folds cross-validation . |