BibTeX

@inProceedings{muti-etal-2025-blue-352653,
	title        = {Blue-haired, misandriche, rabiata: Tracing the Connotation of 'Feminist(s)' Across Time, Languages and Domains},
	abstract     = {Understanding how words shift in meaning is crucial for analyzing societal attitudes.In this study, we investigate the contextual variations of the terms feminist, feminists along three axes: time, language, and domain.To this aim, we collect and release FEMME, a dataset comprising the occurrences of such terms from 2014 to 2023 in English, Italian and Swedish in Twitter, Reddit and Incel domains.Our methodology leverages frame analysis, as well as fine-tuning and LLMs. We find that the connotation of the plural form feminists is consistently more negative than feminist, indicating more hostility towards feminists as a collective, which often triggers greater societal pushback, reflecting broader patterns of group-based hostility and stigma. Across languages, we observe similar stereotypes towards feminists that often include body shaming, as well as accusations of hypocrisy and irrational behavior. In terms of time, we identify events that trigger a peak in terms of negative or positive connotation.As expected, the Incel spheres show predominantly negative connotations, while the general domains show mixed connotations.},
	booktitle    = {Proceedings of the The 9th Workshop on Online Abuse and Harms (WOAH)},
	author       = {Muti, A and Gemelli, S and Moscato, E and Francis, Emilie and Cercas Curry, A and Miriam Plaza-del-Arco, F and Nozza, D},
	year         = {2025},
	publisher    = {Association for Computational Linguistics (ACL)},
	address      = {Vienna, Austria},
}

@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, Lancaster, UK,  July 29-30, 2024},
	author       = {Francis, Emilie},
	year         = {2024},
	publisher    = {NLPAICS’2024},
	address      = {Lancaster, U.K.},
	pages        = {86--96},
}

@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 Technologs (NoDaLiDa/Baltic-HLieT 2025), March 3-4, 2025, Tallin, Estonia / Richard Johansson and Sara Stymne (eds.)},
	author       = {Francis, Emilie},
	year         = {2025},
	publisher    = {University of Tartu Library},
	address      = {Tartu, Estonia},
	ISBN         = {978-9908-53-109-0},
	pages        = {170--180},
}

@inProceedings{munozsanchez-etal-2025-trying-352646,
	title        = {Are You Trying to Convince Me or Are You Trying to Deceive Me? Using Argumentation Types to Identify Deceptive News},
	abstract     = {The way we relay factual information and the way we present deceptive information as truth differs from the perspective of argumentation. In this paper, we explore whether these differences can be exploited to detect deceptive political news in English. We do this by training a model to detect different kinds of argumentation in online news text. We use sentence embeddings extracted from an argumentation type classification model as features for a deceptive news classifier. This deceptive news classification model leverages the sequence of argumentation types within an article to determine whether it is credible or deceptive. Our approach outperforms other state-of-the-art models while having lower variance. Finally, we use the output of our argumentation model to analyze the differences between credible and deceptive news based on the distribution of argumentation types across the articles. Results of this analysis indicate that credible political news presents statements supported by a variety of argumentation types, while deceptive news relies on anecdotes and testimonial.},
	booktitle    = {Proceedings of the The 9th Workshop on Online Abuse and Harms (WOAH)},
	author       = {Muñoz Sánchez, Ricardo and Francis, Emilie and Lindahl, Anna},
	year         = {2025},
	publisher    = {Association for Computational Linguistics (ACL)},
	address      = {Austria, Vienna},
	ISBN         = {979-8-89176-105-6},
	pages        = {355–372},
}

@inProceedings{francis-2025-between-352011,
	title        = {Between Hetero-Fatalism and Dark Femininity: Discussions of Relationships, Sex, and Men in the Femosphere},
	abstract     = {The 'femosphere' is a term coined to describe a group of online ideological spaces for women characterised by toxicity, reactionary feminism, and hetero-pessimism. It is often portrayed as a mirror of a similar group of communities for men, called the 'manosphere'. Although there have been several studies investigating the ideologies and language of the manosphere, the femosphere has been largely overlooked - especially in NLP. This paper presents a study of two communities in the femosphere: Female Dating Strategy and Femcels. It presents an exploration of the language of these communities on topics related to relationships, sex, and men from the perspective of hetero-pessimism using topic modelling and semantic analysis. It reveals dissatisfaction with heterosexual courtship and frustration with the patriarchal society through which members attempt to navigate.},
	booktitle    = {9th Workshop on Online Abuse and Harms (WOAH)},
	author       = {Francis, Emilie},
	year         = {2025},
	publisher    = {Association for Computational Linguistics (ACL)},
}

@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},
}