Pavel Brazdil


NaijaSenti: A Nigerian Twitter Sentiment Corpus for Multilingual Sentiment Analysis
Shamsuddeen Hassan Muhammad | David Ifeoluwa Adelani | Sebastian Ruder | Ibrahim Sa’id Ahmad | Idris Abdulmumin | Bello Shehu Bello | Monojit Choudhury | Chris Chinenye Emezue | Saheed Salahudeen Abdullahi | Anuoluwapo Aremu | Alípio Jorge | Pavel Brazdil
Proceedings of the Thirteenth Language Resources and Evaluation Conference

Sentiment analysis is one of the most widely studied applications in NLP, but most work focuses on languages with large amounts of data. We introduce the first large-scale human-annotated Twitter sentiment dataset for the four most widely spoken languages in Nigeria—Hausa, Igbo, Nigerian-Pidgin, and Yorùbá—consisting of around 30,000 annotated tweets per language, including a significant fraction of code-mixed tweets. We propose text collection, filtering, processing and labeling methods that enable us to create datasets for these low-resource languages. We evaluate a range of pre-trained models and transfer strategies on the dataset. We find that language-specific models and language-adaptive fine-tuning generally perform best. We release the datasets, trained models, sentiment lexicons, and code to incentivize research on sentiment analysis in under-represented languages.


Paraphrase Alignment for Synonym Evidence Discovery
Gintarė Grigonytė | João Paulo Cordeiro | Gaël Dias | Rumen Moraliyski | Pavel Brazdil
Proceedings of the 23rd International Conference on Computational Linguistics (Coling 2010)


Unsupervised Induction of Sentence Compression Rules
João Cordeiro | Gaël Dias | Pavel Brazdil
Proceedings of the 2009 Workshop on Language Generation and Summarisation (UCNLG+Sum 2009)