Papers by Viviana Patti
Dealing with Controversy: An Emotion and Coping Strategy Corpus Based on Role Playing (2024.findings-emnlp)
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| Challenge: | Psychological studies aim at explaining internal mechanisms of emotions, while computational studies simplify them into labels. |
| Approach: | They propose to treat emotions as strategies to cope with salient situations . they introduce a task of coping identification and a corpus constructed via role-playing . |
| Outcome: | The proposed method allows to investigate the link between emotions and behavior, which also emerges in language. |
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. |
WikiBio: a Semantic Resource for the Intersectional Analysis of Biographical Events (2023.acl-long)
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Marco Antonio Stranisci, Rossana Damiano, Enrico Mensa, Viviana Patti, Daniele Radicioni, Tommaso Caselli
| Challenge: | Existing corpora and models for biographical event detection are lacking . Detecting biographical events from unstructured data is a useful task to explore and compare bias in representations of individuals. |
| Approach: | They present a corpus annotated for biographical event detection using 20 Wikipedia biographies and 5 existing corpora to train a model. |
| Outcome: | The proposed model detects all mentions of the target-entity in a biography with an F-score of 0.808 and the entity-related events with an 0.859 score. |
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. |
Cross-domain and Cross-lingual Abusive Language Detection: A Hybrid Approach with Deep Learning and a Multilingual Lexicon (P19-2)
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| Challenge: | Detecting online abusive language in social media messages is gaining increasing attention from scholars and stakeholders. |
| Approach: | They propose a hybrid approach with deep learning and a multilingual lexicon to cross-domain and cross-lingual detection of abusive content. |
| Outcome: | The proposed system can detect abusive content across domains and languages using a multilingual lexicon and a domain-independent lexical. |
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. |
Do You Really Want to Hurt Me? Predicting Abusive Swearing in Social Media (2020.lrec-1)
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| Challenge: | Swearing is a common form of verbal communication and occurs in social media and online forums . a study by a team of researchers has investigated the phenomenon of swearing in Twitter . |
| Approach: | They analyze tweets to determine abusive swearing using models that automatically predict it . they also investigate lexical, syntactic, and affective features that are more informative . |
| Outcome: | The proposed model can predict abusive swearing in a tweet context and provide an intrinsic evaluation of the model. |
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. |
APPReddit: a Corpus of Reddit Posts Annotated for Appraisal (2022.lrec-1)
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Marco Antonio Stranisci, Simona Frenda, Eleonora Ceccaldi, Valerio Basile, Rossana Damiano, Viviana Patti
| Challenge: | Existing resources for emotion recognition are lacking for appraisal models. |
| Approach: | They propose to use APPReddit to annotate non-experimental data according to Appraisal theories . they compare it with enISEAR, a corpus of events created in an experimental setting and annotated according to this theory. |
| Outcome: | The proposed model predicts four appraisal dimensions without significant loss . the proposed model is compared with enISEAR, a corpus of events created in an experimental setting and annotated for appraisal. |