Alisa Zhila


2020

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Data Augmentation using Machine Translation for Fake News Detection in the Urdu Language
Maaz Amjad | Grigori Sidorov | Alisa Zhila
Proceedings of the 12th Language Resources and Evaluation Conference

The task of fake news detection is to distinguish legitimate news articles that describe real facts from those which convey deceiving and fictitious information. As the fake news phenomenon is omnipresent across all languages, it is crucial to be able to efficiently solve this problem for languages other than English. A common approach to this task is supervised classification using features of various complexity. Yet supervised machine learning requires substantial amount of annotated data. For English and a small number of other languages, annotated data availability is much higher, whereas for the vast majority of languages, it is almost scarce. We investigate whether machine translation at its present state could be successfully used as an automated technique for annotated corpora creation and augmentation for fake news detection focusing on the English-Urdu language pair. We train a fake news classifier for Urdu on (1) the manually annotated dataset originally in Urdu and (2) the machine-translated version of an existing annotated fake news dataset originally in English. We show that at the present state of machine translation quality for the English-Urdu language pair, the fully automated data augmentation through machine translation did not provide improvement for fake news detection in Urdu.

2015

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Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Student Research Workshop
Diana Inkpen | Smaranda Muresan | Shibamouli Lahiri | Karen Mazidi | Alisa Zhila
Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Student Research Workshop

2014

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Open Information Extraction for Spanish Language based on Syntactic Constraints
Alisa Zhila | Alexander Gelbukh
Proceedings of the ACL 2014 Student Research Workshop

2013

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Using Factual Density to Measure Informativeness of Web Documents
Christopher Horn | Alisa Zhila | Alexander Gelbukh | Roman Kern | Elisabeth Lex
Proceedings of the 19th Nordic Conference of Computational Linguistics (NODALIDA 2013)

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Combining Heterogeneous Models for Measuring Relational Similarity
Alisa Zhila | Wen-tau Yih | Christopher Meek | Geoffrey Zweig | Tomas Mikolov
Proceedings of the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies