Work Package 5
University of Bergen
Samia Touileb is currently a researcher in MediaFutures WP5 on Norwegian Language Technologies. Prior to this she was a Postdoc at the Language Technology Group (LTG), Department of Informatics, at the University of Oslo. She holds a PhD in Information Science with a focus on Natural Language Processing (NLP) from the University of Bergen, and has been working within research in and applications of NLP for almost a decade.
Her main research interests are information extraction, sentiment analysis, bias and fairness in NLP, and applications of NLP and machine learning methods to tasks within social science research. She also mainly works on under-resourced languages such as Norwegian.
Publications from 2020 and before are not direct results of the SFI MediaFutures, but are key results from our team members working on related topics in MediaFutures.
|Occupational Biases in Norwegian and Multilingual Language Models Workshop |
|Using Gender- and Polarity-Informed Models to Investigate Bias Inproceedings |
In: Association for Computational Linguistics, 2021.
|Using Gender- and Polarity-informed Models to Investigate Bias Working paper |
|Gender and sentiment, critics and authors: a dataset of Norwegian book reviews Journal Article |
In: Gender Bias in Natural Language Processing. Association for Computational Linguistics, 2020, (Pre SFI).
|Identifying Sentiments in Algerian Code-switched User-generated Comments Conference |
2020, (Pre SFI).
|Named Entity Recognition without Labelled Data: A Weak Supervision Approach Journal Article |
In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pp. 1518–1533, 2020, (Pre SFI).
|Lexicon information in neural sentiment analysis: a multi-task learning approach Conference |
Linköping University Electronic Press, 2019, (Pre SFI).
NoReC: The Norwegian Review Corpus Proceeding
2018, (Pre SFI).
|Automatic identification of unknown names with specific roles Journal Article |
In: Proceedings of the Second Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature, pp. 150-158, 2017, (Pre SFI).