Papers by Cristina Bosco
Italian NLP for Everyone: Resources and Models from EVALITA to the European Language Grid (2022.lrec-1)
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| Challenge: | European Language Grid enables researchers and practitioners to easily distribute and use NLP resources and models. |
| Approach: | They propose to integrate Italian NLP resources into the European Language Grid . they show how easy it is to use the integrated systems and demonstrate how seamless it is . |
| Outcome: | The European Language Grid enables researchers and practitioners to easily distribute and use NLP resources and models. |
PoSTWITA-UD: an Italian Twitter Treebank in Universal Dependencies (L18-1)
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Manuela Sanguinetti, Cristina Bosco, Alberto Lavelli, Alessandro Mazzei, Oronzo Antonelli, Fabio Tamburini
| Challenge: | Various approaches and ad hoc resources are needed to provide proper coverage of specific linguistic phenomena. |
| Approach: | They propose to annotate tweets using a well-known dependency-based annotation format . they propose to use the tweets for training NLP systems to improve their performance . |
| Outcome: | The proposed resource can be used for training of NLP systems on social media texts. |
Marking Irony Activators in a Universal Dependencies Treebank: The Case of an Italian Twitter Corpus (2020.lrec-1)
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| Challenge: | Existing annotations for irony are difficult, and the recognition of it is difficult due to its polarity. |
| Approach: | They propose a fine-grained annotation scheme centered on irony that highlights the tokens responsible for its activation and their morpho-syntactic features. |
| Outcome: | The proposed scheme highlights the tokens responsible for irony activation and their morpho-syntactic features. |
QUEEREOTYPES: A Multi-Source Italian Corpus of Stereotypes towards LGBTQIA+ Community Members (2024.lrec-main)
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Alessandra Teresa Cignarella, Manuela Sanguinetti, Simona Frenda, Andrea Marra, Cristina Bosco, Valerio Basile
| Challenge: | a dataset of social media texts addressing LGBTQIA+ individuals is presented in this paper . the dataset is based on two sources in italian: Facebook and Twitter . |
| Approach: | They describe a dataset composed of two sub-corpora from two different sources in Italian . the dataset includes social media texts regarding LGBTQIA+ individuals, behaviors, ideology and events . |
| Outcome: | The QUEEREOTYPES dataset includes social media texts regarding LGBTQIA+ individuals, behaviors, ideology and events. |
An Italian Twitter Corpus of Hate Speech against Immigrants (L18-1)
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| Challenge: | a recent study has annotated 6,000 tweets for hate speech against immigrants . the annotation scheme was designed to account for the multiplicity of factors that can contribute to the definition of a hate speech notion . |
| Approach: | They describe a Twitter corpus annotated for hate speech against immigrants . they propose a scheme that includes aggressiveness, offensiveness, irony, stereotype and intensity . |
| Outcome: | The proposed annotation scheme includes aggressiveness, offensiveness, irony, stereotype, intensity and (on an experimental basis) intensity. |
EPIC: Multi-Perspective Annotation of a Corpus of Irony (2023.acl-long)
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Simona Frenda, Alessandro Pedrani, Valerio Basile, Soda Marem Lo, Alessandra Teresa Cignarella, Raffaella Panizzon, Cristina Marco, Bianca Scarlini, Viviana Patti, Cristina Bosco, Davide Bernardi
| Challenge: | EPIC is the first annotated corpus for irony analysis based on data perspectivism . a recent trend in natural language processing (NLP) postulates that the disagreement among annotators in a language resource is a valuable source of knowledge, rather than noise that ought to be minimized or discarded. |
| Approach: | They propose to annotate an English perspectivist irony corpus based on data perspectivism . they validate the model by creating perspective-aware models that encode the perspectives of annotators grouped according to their demographic characteristics. |
| Outcome: | The proposed model can capture different perspectives on irony among different groups of annotators, and is more confident than non-perspectivist models. |
Treebanking User-Generated Content: A Proposal for a Unified Representation in Universal Dependencies (2020.lrec-1)
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Manuela Sanguinetti, Cristina Bosco, Lauren Cassidy, Özlem Çetinoğlu, Alessandra Teresa Cignarella, Teresa Lynn, Ines Rehbein, Josef Ruppenhofer, Djamé Seddah, Amir Zeldes
| Challenge: | Despite the increasing number of contributions on Part-of-Speech tagging and parsing, automatic processing of user-generated content (UGC) still represents a challenging task. |
| Approach: | They propose a set of guidelines for the annotation of user-generated texts within the Universal Dependencies framework. |
| Outcome: | The proposed annotation guidelines promote cross-linguistic consistency, which has always been in the spirit of UD. |
Confidence-based Ensembling of Perspective-aware Models (2023.emnlp-main)
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Silvia Casola, Soda Lo, Valerio Basile, Simona Frenda, Alessandra Cignarella, Viviana Patti, Cristina Bosco
| Challenge: | Human label variability has been a topic of research in the field of NLP recently . Exploiting disagreements in annotations has been shown to offer advantages for accurate modelling and fairer evaluation. |
| Approach: | They propose a highly perspectivist model that exploits disagreements in annotations to capture the subjectivity encoded in the annotation process. |
| Outcome: | The proposed model is validated on irony and hate speech detection scenarios in in-domain and cross-domain settings. |
UINAUIL: A Unified Benchmark for Italian Natural Language Understanding (2023.acl-demo)
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| Challenge: | a benchmark of six tasks for Italian Natural Language Understanding is presented . large language models (LLMs) have revolutionized the field of natural language processing . a few benchmarks exist for non-English languages, but only a handful are available for nonEnglish languages . |
| Approach: | They introduce a benchmark for Italian Natural Language Understanding that harmonizes the data format and exposes functionalities to facilitate data manipulation and evaluation of custom models. |
| Outcome: | The proposed benchmarks are based on the European Language Grid and available models in Italian and multilingual languages. |
A Multilingual Dataset of Racial Stereotypes in Social Media Conversational Threads (2023.findings-eacl)
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Tom Bourgeade, Alessandra Teresa Cignarella, Simona Frenda, Mario Laurent, Wolfgang Schmeisser-Nieto, Farah Benamara, Cristina Bosco, Véronique Moriceau, Viviana Patti, Mariona Taulé
| Challenge: | a new corpus-based study addresses racial stereotypes in social media conversations . a multilingual corpus of rhs is used to investigate how they are spread . |
| Approach: | They propose a corpus-based method for multilingual racial stereotype identification in social media conversational threads. |
| Outcome: | The proposed method sheds light on how racial hoaxes are spread and allows identification of negative stereotypes that reinforce them. |
Application and Analysis of a Multi-layered Scheme for Irony on the Italian Twitter Corpus TWITTIRÒ (L18-1)
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| Challenge: | Using a multi-layered scheme for the fine-grained annotation of irony on Italian Twitter is a challenging task to be performed by both human annotators and automatic NLP systems. |
| Approach: | They propose to apply a multi-layered scheme for the fine-grained annotation of irony to an Italian Twitter corpus. |
| Outcome: | The proposed scheme can be validated on Italian irony-laden social media contents and is available in the cross- and multi-lingual perspective. |
Multilingual Irony Detection with Dependency Syntax and Neural Models (2020.coling-main)
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Alessandra Teresa Cignarella, Valerio Basile, Manuela Sanguinetti, Cristina Bosco, Paolo Rosso, Farah Benamara
| Challenge: | Several semantic and syntactic devices can be used to express irony, causing the incongruity, determine the clash and play the role of irony triggers within a text. |
| Approach: | They propose to exploit linguistic resources where syntax is annotated according to the Universal Dependencies scheme. |
| Outcome: | The proposed method exploits linguistic resources where syntax is annotated according to the Universal Dependencies scheme. |