Antonio Pascucci


2020

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Proceedings of the Workshop on Resources and Techniques for User and Author Profiling in Abusive Language
Johanna Monti | Valerio Basile | Maria Pia Di Buono | Raffaele Manna | Antonio Pascucci | Sara Tonelli
Proceedings of the Workshop on Resources and Techniques for User and Author Profiling in Abusive Language

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Is this hotel review truthful or deceptive? A platform for disinformation detection through computational stylometry
Antonio Pascucci | Raffaele Manna | Ciro Caterino | Vincenzo Masucci | Johanna Monti
Proceedings for the First International Workshop on Social Threats in Online Conversations: Understanding and Management

In this paper, we present a web service platform for disinformation detection in hotel reviews written in English. The platform relies on a hybrid approach of computational stylometry techniques, machine learning and linguistic rules written using COGITO, Expert System Corp.’s semantic intelligence software thanks to which it is possible to analyze texts and extract all their characteristics. We carried out a research experiment on the Deceptive Opinion Spam corpus, a balanced corpus composed of 1,600 hotel reviews of 20 Chicago hotels split into four datasets: positive truthful, negative truthful, positive deceptive and negative deceptive reviews. We investigated four different classifiers and we detected that Simple Logistic is the most performing algorithm for this type of classification.

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The Role of Computational Stylometry in Identifying (Misogynistic) Aggression in English Social Media Texts
Antonio Pascucci | Raffaele Manna | Vincenzo Masucci | Johanna Monti
Proceedings of the Second Workshop on Trolling, Aggression and Cyberbullying

In this paper, we describe UniOr_ExpSys team participation in TRAC-2 (Trolling, Aggression and Cyberbullying) shared task, a workshop organized as part of LREC 2020. TRAC-2 shared task is organized in two sub-tasks: Aggression Identification (a 3-way classification between “Overtly Aggressive”, “Covertly Aggressive” and “Non-aggressive” text data) and Misogynistic Aggression Identification (a binary classifier for classifying the texts as “gendered” or “non-gendered”). Our approach is based on linguistic rules, stylistic features extraction through stylometric analysis and Sequential Minimal Optimization algorithm in building the two classifiers.

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The Challenge of the TV game La Ghigliottina to NLP
Federico Sangati | Antonio Pascucci | Johanna Monti
Workshop on Games and Natural Language Processing

In this paper, we describe a Telegram bot, Mago della Ghigliottina (Ghigliottina Wizard), able to solve La Ghigliottina game (The Guillotine), the final game of the Italian TV quiz show L’Eredità. Our system relies on linguistic resources and artificial intelligence and achieves better results than human players (and competitors of L’Eredità too). In addition to solving a game, Mago della Ghigliottina can also generate new game instances and challenge the users to match the solution.