1 code implementation • LREC 2022 • Stefano Menini, Teresa Paccosi, Serra Sinem Tekiroğlu, Sara Tonelli
Olfactory references play a crucial role in our memory and, more generally, in our experiences, since researchers have shown that smell is the sense that is most directly connected with emotions.
1 code implementation • LREC 2022 • Federico Bonetti, Elisa Leonardelli, Daniela Trotta, Raffaele Guarasci, Sara Tonelli
In this work, we contribute to this debate by presenting a 3D video game that was used to collect acceptability judgments on Italian sentences.
no code implementations • EMNLP (LaTeCHCLfL, CLFL, LaTeCH) 2021 • Sara Tonelli, Stefano Menini
Although olfactory references play a crucial role in our cultural memory, only few works in NLP have tried to capture them from a computational perspective.
1 code implementation • ACL (WOAH) 2021 • Marta Marchiori Manerba, Sara Tonelli
Our evaluation shows that, although BERT-based classifiers achieve high accuracy levels on a variety of natural language processing tasks, they perform very poorly as regards fairness and bias, in particular on samples involving implicit stereotypes, expressions of hate towards minorities and protected attributes such as race or sexual orientation.
no code implementations • EACL (HCINLP) 2021 • Federico Bonetti, Sara Tonelli
In this paper we discuss several challenges related to the development of a 3D game, whose goal is to raise awareness on cyberbullying while collecting linguistic annotation on offensive language.
1 code implementation • EMNLP 2021 • Elisa Leonardelli, Stefano Menini, Alessio Palmero Aprosio, Marco Guerini, Sara Tonelli
Since state-of-the-art approaches to offensive language detection rely on supervised learning, it is crucial to quickly adapt them to the continuously evolving scenario of social media.
1 code implementation • NAACL 2022 • Alan Ramponi, Sara Tonelli
Avoiding to rely on dataset artifacts to predict hate speech is at the cornerstone of robust and fair hate speech detection.
no code implementations • games (LREC) 2022 • Federico Bonetti, Sara Tonelli
In this work we present an analysis of abusive language annotations collected through a 3D video game.
no code implementations • ACL (mmsr, IWCS) 2021 • Daniela Trotta, Sara Tonelli
Speaker gestures are semantically co-expressive with speech and serve different pragmatic functions to accompany oral modality.
1 code implementation • LT4HALA (LREC) 2022 • Alessio Palmero Aprosio, Stefano Menini, Sara Tonelli
This has led to the creation of BERT-like models for different languages trained with digital repositories from the past.
no code implementations • LChange (ACL) 2022 • Stefano Menini, Teresa Paccosi, Sara Tonelli, Marieke van Erp, Inger Leemans, Pasquale Lisena, Raphael Troncy, William Tullett, Ali Hürriyetoğlu, Ger Dijkstra, Femke Gordijn, Elias Jürgens, Josephine Koopman, Aron Ouwerkerk, Sanne Steen, Inna Novalija, Janez Brank, Dunja Mladenic, Anja Zidar
We present a benchmark in six European languages containing manually annotated information about olfactory situations and events following a FrameNet-like approach.
no code implementations • 28 Oct 2024 • Ivan Srba, Olesya Razuvayevskaya, João A. Leite, Robert Moro, Ipek Baris Schlicht, Sara Tonelli, Francisco Moreno García, Santiago Barrio Lottmann, Denis Teyssou, Valentin Porcellini, Carolina Scarton, Kalina Bontcheva, Maria Bielikova
In the current era of social media and generative AI, an ability to automatically assess the credibility of online social media content is of tremendous importance.
no code implementations • 10 Oct 2024 • Camilla Casula, Sara Tonelli
Hate speech is one of the main threats posed by the widespread use of social networks, despite efforts to limit it.
1 code implementation • 27 Sep 2024 • Nicolò Penzo, Maryam Sajedinia, Bruno Lepri, Sara Tonelli, Marco Guerini
Assessing the performance of systems to classify Multi-Party Conversations (MPC) is challenging due to the interconnection between linguistic and structural characteristics of conversations.
no code implementations • 21 Feb 2024 • Elisa Leonardelli, Sara Tonelli
Language (English) is pivotal for information to become transnational and reach far.
1 code implementation • 5 Feb 2024 • Nicolò Penzo, Antonio Longa, Bruno Lepri, Sara Tonelli, Marco Guerini
We also experiment with different amounts of training data and analyse the topology of local discussion networks in a privacy-compliant way.
no code implementations • 28 Sep 2021 • Elisa Leonardelli, Stefano Menini, Alessio Palmero Aprosio, Marco Guerini, Sara Tonelli
Since state-of-the-art approaches to offensive language detection rely on supervised learning, it is crucial to quickly adapt them to the continuously evolving scenario of social media.
1 code implementation • Findings (EMNLP) 2021 • Daniela Trotta, Raffaele Guarasci, Elisa Leonardelli, Sara Tonelli
The development of automated approaches to linguistic acceptability has been greatly fostered by the availability of the English CoLA corpus, which has also been included in the widely used GLUE benchmark.
no code implementations • 6 Jul 2021 • Yi-Ling Chung, Serra Sinem Tekiroglu, Sara Tonelli, Marco Guerini
In this paper, we introduce a novel ICT platform that NGO operators can use to monitor and analyze social media data, along with a counter-narrative suggestion tool.
1 code implementation • 27 Mar 2021 • Stefano Menini, Alessio Palmero Aprosio, Sara Tonelli
We first re-annotate part of a widely used dataset for abusive language detection in English in two conditions, i. e. with and without context.
1 code implementation • SEMEVAL 2020 • Camilla Casula, Alessio Palmero Aprosio, Stefano Menini, Sara Tonelli
In this paper we present our submission to sub-task A at SemEval 2020 Task 12: Multilingual Offensive Language Identification in Social Media (OffensEval2).
no code implementations • Findings of the Association for Computational Linguistics 2020 • Michele Corazza, Stefano Menini, Elena Cabrio, Sara Tonelli, Serena Villata
Recent studies have demonstrated the effectiveness of cross-lingual language model pre-training on different NLP tasks, such as natural language inference and machine translation.
no code implementations • 5 May 2020 • Alessio Palmero Aprosio, Stefano Menini, Sara Tonelli
We find that users judge the same images in different ways, although the presence of a person in the picture increases the probability to get an offensive comment.
no code implementations • LREC 2020 • Daniela Trotta, Alessio Palmero Aprosio, Sara Tonelli, Annibale Elia
This paper introduces a multimodal corpus in the political domain, which on top of transcribed face-to-face interviews presents the annotation of facial displays, hand gestures and body posture.
no code implementations • LREC 2020 • Federico Bonetti, Sara Tonelli
Gamification has been applied to many linguistic annotation tasks, as an alternative to crowdsourcing platforms to collect annotated data in an inexpensive way.
no code implementations • WS 2019 • Stefano Menini, Giovanni Moretti, Michele Corazza, Elena Cabrio, Sara Tonelli, Serena Villata
Social media platforms like Twitter and Instagram face a surge in cyberbullying phenomena against young users and need to develop scalable computational methods to limit the negative consequences of this kind of abuse.
no code implementations • CL 2019 • Rachele Sprugnoli, Sara Tonelli
However, the recognition and elaboration of events is a crucial step when dealing with historical texts Particularly in the current era of massive digitization of historical sources: Research in this domain can lead to the development of methodologies and tools that can assist historians in enhancing their work, while having an impact also on the field of Natural Language Processing.
no code implementations • WS 2019 • Alessio Palmero Aprosio, Sara Tonelli, Marco Turchi, Matteo Negri, Mattia A. Di Gangi
Inspired by the machine translation field, in which synthetic parallel pairs generated from monolingual data yield significant improvements to neural models, in this paper we exploit large amounts of heterogeneous data to automatically select simple sentences, which are then used to create synthetic simplification pairs.
no code implementations • WS 2018 • Rachele Sprugnoli, Stefano Menini, Sara Tonelli, Filippo Oncini, Enrico Piras
Although WhatsApp is used by teenagers as one major channel of cyberbullying, such interactions remain invisible due to the app privacy policies that do not allow ex-post data collection.
no code implementations • IJCNLP 2017 • Carolina Scarton, Alessio Palmero Aprosio, Sara Tonelli, Tamara Mart{\'\i}n Wanton, Lucia Specia
Our implementation includes a set of general-purpose simplification rules, as well as a sentence selection module (to select sentences to be simplified) and a confidence model (to select only promising simplifications).
1 code implementation • RANLP 2017 • Amosse Edouard, Elena Cabrio, Sara Tonelli, Nhan Le-Thanh
This demo paper presents a system that builds a timeline with salient actions of a soccer game, based on the tweets posted by users.
no code implementations • RANLP 2017 • Amosse Edouard, Elena Cabrio, Sara Tonelli, Nhan Le-Thanh
Detecting which tweets describe a specific event and clustering them is one of the main challenging tasks related to Social Media currently addressed in the NLP community.
no code implementations • RANLP 2017 • Amosse Edouard, Elena Cabrio, Sara Tonelli, Nhan Le-Thanh
In this paper, we propose an approach to build a timeline with actions in a sports game based on tweets.
no code implementations • EMNLP 2017 • Stefano Menini, Federico Nanni, Simone Paolo Ponzetto, Sara Tonelli
We present a topic-based analysis of agreement and disagreement in political manifestos, which relies on a new method for topic detection based on key concept clustering.
no code implementations • EACL 2017 • Rachele Sprugnoli, Tommaso Caselli, Sara Tonelli, Giovanni Moretti
This paper presents a new resource, called Content Types Dataset, to promote the analysis of texts as a composition of units with specific semantic and functional roles.
no code implementations • EACL 2017 • Stefano Menini, Rachele Sprugnoli, Giovanni Moretti, Enrico Bignotti, Sara Tonelli, Bruno Lepri
We present RAMBLE ON, an application integrating a pipeline for frame-based information extraction and an interface to track and display movement trajectories.
1 code implementation • COLING 2016 • Paramita Mirza, Sara Tonelli
The effects of the interaction between the temporal and the causal components, although limited, yield promising results and confirm the tight connection between the temporal and the causal dimension of texts.
Ranked #1 on
Temporal Information Extraction
on TimeBank
no code implementations • COLING 2016 • Paramita Mirza, Sara Tonelli
Temporal relation classification is a challenging task, especially when there are no explicit markers to characterise the relation between temporal entities.
no code implementations • COLING 2016 • Stefano Menini, Sara Tonelli
The automated comparison of points of view between two politicians is a very challenging task, due not only to the lack of annotated resources, but also to the different dimensions participating to the definition of agreement and disagreement.
no code implementations • LREC 2016 • Tommaso Caselli, Giovanni Moretti, Rachele Sprugnoli, Sara Tonelli, Damien Lanfrey, Donatella Solda Kutzmann
In this paper we present PIERINO (PIattaforma per l{'}Estrazione e il Recupero di INformazione Online), a system that was implemented in collaboration with the Italian Ministry of Education, University and Research to analyse the citizens{'} comments given in {\#}labuonascuola survey.
no code implementations • LREC 2016 • Francesco Corcoglioniti, Marco Rospocher, Alessio Palmero Aprosio, Sara Tonelli
We introduce PreMOn (predicate model for ontologies), a linguistic resource for exposing predicate models (PropBank, NomBank, VerbNet, and FrameNet) and mappings between them (e. g, SemLink) as Linked Open Data.
1 code implementation • LREC 2014 • Christian Girardi, Manuela Speranza, Rachele Sprugnoli, Sara Tonelli
In this paper we present CROMER (CROss-document Main Events and entities Recognition), a novel tool to manually annotate event and entity coreference across clusters of documents.
no code implementations • LREC 2012 • Sucheta Ghosh, Richard Johansson, Giuseppe Riccardi, Sara Tonelli
We describe two constraint-based methods that can be used to improve the recall of a shallow discourse parser based on conditional random field chunking.