BibTeX

@inProceedings{masciolini-etal-2024-synthetic-338288,
	title        = {Synthetic-Error Augmented Parsing of Swedish as a Second Language: Experiments with Word Order},
	abstract     = {Ungrammatical text poses significant challenges for off-the-shelf dependency parsers. In this paper, we explore the effectiveness of using synthetic data to improve performance on essays written by learners of Swedish as a second language. Due to their relevance and ease of annotation, we restrict our initial experiments to word order errors. To do that, we build a corrupted version of the standard Swedish Universal Dependencies (UD) treebank Talbanken, mimicking the error patterns and frequency distributions observed in the Swedish Learner Language (SweLL) corpus. We then use the MaChAmp (Massive Choice, Ample tasks) toolkit to train an array of BERT-based dependency parsers, fine-tuning on different combinations of original and corrupted data. We evaluate the resulting models not only on their respective test sets but also, most importantly, on a smaller collection of sentence-correction pairs derived from SweLL. Results show small but significant performance improvements on the target domain, with minimal decline on normative data.},
	booktitle    = {Proceedings of the Joint Workshop on Multiword Expressions and Universal Dependencies (MWE-UD) @ LREC-COLING 2024, May 25, 2024, Torino, Italia},
	author       = {Masciolini, Arianna and Francis, Emilie and Szawerna, Maria Irena},
	year         = {2024},
	publisher    = {ELRA and ICCL},
	address      = {Torino, Italy},
	ISBN         = {978-2-493814-20-3},
}

@inProceedings{francis-2025-language-348452,
	title        = {Language of the Swedish Manosphere with Swedish FrameNet},
	abstract     = {The manosphere is a loose group of online communities centralised around the themes of anti-feminism, misogyny, racism, and hetero-masculinity. It has gained a reputation for violent extremism, particularly from members of the involuntary celibate (incel) community. Sweden sees one of the highest volumes of online traffic to well-known incel forums in all of Europe. In spite of this, there is little information on manosphere/incel cultre in Swedish. This paper uses posts from Flashback’s manosphere subforum automatically annotated with Swedish FrameNet to analyse the language community in a Swedish context. To do so, a lexicon for the Swedish manosphere was created and terms of interest were identified in the Swedish discourse. Analysis of prominent semantic frames linked to these terms of interest presents a detailed look into the language of the Swedish manosphere.},
	booktitle    = {25th Nordic Conference on Computational Linguistics and 11th Baltic Conference on Human Language Technologies (NoDaLiDa/Baltic-HLT 2025)},
	author       = {Francis, Emilie},
	year         = {2025},
	publisher    = {University of Tartu Library},
	address      = {Tartu, Estonia},
	pages        = {10},
}

@inProceedings{francis-2024-variation-342620,
	title        = {Variation between Credible and Non-Credible News Across Topics},
	abstract     = {‘Fake News’ continues to undermine trust in modern journalism and politics. Despite con- tinued efforts to study fake news, results have been conflicting. Previous attempts to analyse and combat fake news have largely focused on distinguishing fake news from truth, or differ- entiating between its various sub-types (such as propaganda, satire, misinformation, etc.) This paper conducts a linguistic and stylistic analy- sis of fake news, focusing on variation between various news topics. It builds on related work identifying features from discourse and linguis- tics in deception detection by analysing five distinct news topics: Economy, Entertainment, Health, Science, and Sports. The results em- phasize that linguistic features vary between credible and deceptive news in each domain and highlight the importance of adapting clas- sification tasks to accommodate variety-based stylistic and linguistic differences in order to achieve better real-world performance.},
	booktitle    = {The First International Conference on Natural Language Processing and Artificial Intelligence for Cyber Security},
	author       = {Francis, Emilie},
	year         = {2024},
	publisher    = {NLPAICS’2024},
	address      = {Lancaster, U.K.},
	pages        = {86--96},
}