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Samia Touilebs bilde

Samia Touileb

Forsker, MediaFutures: Research Centre for Responsible Media Technology & Innovation
SFI – MediaFutures
  • E-postSamia.Touileb@uib.no
  • Telefon+47 55 58 41 31
  • Besøksadresse
    Fosswinckels gate 6
    Lauriz Meltzers hus
    5007 Bergen
    Rom 
    516
  • Postadresse
    Postboks 7802
    5020 Bergen
Vitenskapelig artikkel
  • Vis forfatter(e) (2016). ADIOS LDA: When Grammar Induction Meets Topic Modeling. NIKT: Norsk IKT-konferanse for forskning og utdanning.
  • Vis forfatter(e) (2014). Inducing Information Structures for Data-driven Text Analysis. Association for Computational Linguistics (ACL). Annual Meeting Conference Proceedings.
  • Vis forfatter(e) (2014). Applying grammar induction to text mining. Association for Computational Linguistics (ACL). Annual Meeting Conference Proceedings. 712-717.
Faglig foredrag
  • Vis forfatter(e) (2016). Getting to know large newsflows: Automatically induced information structures as keyphrases for news content analysis.
  • Vis forfatter(e) (2012). Networks of texts and people.
Vitenskapelig foredrag
  • Vis forfatter(e) (2018). Operationalising Diversity for Big Data Policy Research.
  • Vis forfatter(e) (2017). Finding Voices in the Margins: Computer-Assisted Discovery of Naturally Belonging Names .
  • Vis forfatter(e) (2015). Computer supported deliberation and argumentation online. Proposing a system for online argumentation.
  • Vis forfatter(e) (2013). Inducing local grammars from n-grams.
Vitenskapelig antologi/Konferanseserie
  • Vis forfatter(e) (2021). Proceedings of the Sixth Arabic Natural Language Processing Workshop. Association for Computational Linguistics.
Doktorgradsavhandling
  • Vis forfatter(e) (2017). Automatically Inducing Information Structures. A Text Mining Approach Based on the Distributional Hypothesis.
Vitenskapelig Kapittel/Artikkel/Konferanseartikkel
  • Vis forfatter(e) (2022). NorDiaChange: Diachronic Semantic Change Dataset for Norwegian. 10 sider.
  • Vis forfatter(e) (2021). Using Gender- and Polarity-Informed Models to Investigate Bias. 9 sider.
  • Vis forfatter(e) (2021). The interplay between language similarity and script on a novel multi-layer Algerian dialect corpus. 13 sider.
  • Vis forfatter(e) (2021). NorDial: A Preliminary Corpus of Written Norwegian Dialect Use. 7 sider.
  • Vis forfatter(e) (2020). Named Entity Recognition without Labelled Data: A Weak Supervision Approach . 16 sider.
  • Vis forfatter(e) (2020). LTG-ST at NADI Shared Task 1: Arabic Dialect Identification using a Stacking Classifier. 7 sider.
  • Vis forfatter(e) (2020). Identifying Sentiments in Algerian Code-switched User-generated Comments. 8 sider.
  • Vis forfatter(e) (2020). Gender and sentiment, critics and authors: a dataset of Norwegian book reviews. 14 sider.
  • Vis forfatter(e) (2019). Measuring Diachronic Evolution of Evaluative Adjectives with Word Embeddings: the Case for English, Norwegian, and Russian. 8 sider.
  • Vis forfatter(e) (2019). Lexicon information in neural sentiment analysis: a multi-task learning approach. 12 sider.
  • Vis forfatter(e) (2018). NoReC: The Norwegian Review Corpus. 6 sider.
  • Vis forfatter(e) (2018). Automatic identification of unknown names with specific roles. 9 sider.
  • Vis forfatter(e) (2014). Constructions: a new unit of analysis for corpus-based discourse analysis . 11 sider.
Poster
  • Vis forfatter(e) (2021). Using Gender- and Polarity-informed Models to Investigate Bias.
  • Vis forfatter(e) (2018). Automatically identifying names of unrecognized politicians.
  • Vis forfatter(e) (2015). A computational approach to organize and analyze online communication data.
  • Vis forfatter(e) (2013). Applying Corpus Techniques to Climate Change Blogs.

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