Author: Simona Frenda

for text classification in Italian

Valerio Basile will present some experiments carried out using the new zero-shot technique of prompt-based learning for various text classification tasks in Italian.

Abstract: Prompt-based learning is a recent paradigm in NLP that leverages large pre-trained language models to perform a variety of tasks. With this technique, it is possible to build classifiers that do not need training data (zero-shot). In this work, Valerio assessed the status of prompt-based learning applied to several text classification tasks in the Italian language. The results indicate that the performance gap towards current supervised methods is still relevant. However, the difference in performance between pre-trained models and the characteristic of the prompt-based classifier of operating in a zero-shot fashion open a discussion regarding the next generation of evaluation campaigns for NLP.

The Ontology of Dangerous Speech Messages

Simona Frenda and Marco A. Stranisci will present O-Dang! (Ontology of Dangerous speech), a systematic and interoperable Knowledge Graph for the collection of linguistic annotated data.

Inside the NLP community there is a considerable amount of language resources created, annotated and released every day with the aim of studying specific linguistic phenomena. Despite a variety of attempts in order to organize such resources has been carried on, a lack of systematic methods and of possible interoperability between resources are still present. Furthermore, when storing linguistic information, still nowadays, the most common practice is the concept of “gold standard”, which is in contrast with recent trends in NLP that aim at stressing the importance of different subjectivities and points of view when training machine learning and deep learning methods. In this talk, we present O-Dang!: The Ontology of Dangerous Speech Messages, a systematic and interoperable Knowledge Graph (KG) for the collection of linguistic annotated data. O-Dang! is designed to gather and organize Italian datasets into a structured KG, according to the principles shared within the Linguistic Linked Open Data community. The ontology has also been designed to account a perspectivist approach, since it provides a model for encoding both gold standard and single-annotator labels in the KG.

For more info: Paper, App

When: 08/07/2022

Where: In presence at Sala Riunioni (3° floor) and online

The laboratory and the experiences in Italian high schools.

The possibility of raising awareness about misbehaviour online, such as hate speech, especially in young generations, could help society to reduce their impact, and thus, their consequences.

The Commissione Orientamento e Informatica nelle Scuole of the Computer Science Department of the University of Turin has designed various technologies that support educational projects and activities in this perspective. 

In the past year and a half, Alessandra T. Cignarella, Simona Frenda, Mirko Lai and Marco A. Stranisci developed a laboratory called #DeactivHate, specifically designed for secondary school students (aged 14-19). The cycle of 5 lessons aims at countering hateful phenomena online and also at making students aware of technologies that they use on a daily basis. Furthermore, some basic methodologies and common practices of Computational Linguistics and Artificial Intelligence are introduced.

In this talk, Alessandra will describe the teaching experience in high schools and the usefulness of some of the activities tested for bringing a small taste of NLP in Italian high schools.

When: 17/06/2022

Where: Sala riunioni 3° floor

Paper: https://iris.unito.it/retrieve/handle/2318/1823881/885619/paper35.pdf

Valerio Basile will present an interesting work on the detection of users suffering Fibromyalgia analysing their messages on Twitter.

Fibromyalgia (FM) is a syndrome characterized by a number of symptoms including chronic pain, tiredness, and cognitive dysfunctions. Medical studies estimate a widespread incidence of FM, severely skewed towards women. However, while the European Parliament recognizes FM as a condition negatively impacting the lives of millions, and despite estimates of about 2 million people suffering from FM in Italy, the condition is treated unevenly across this country. One of the main obstacles toward full healthcare for FM patients in Italy is the difficult and often excessively long diagnostic path.

The goal of this study is to leverage the vast amount of natural language data available in social media, in order to model the language of FM and build an automatic system that distinguishes users suffering from FM from healthy users based on their social media post history. To this aim, he collected about 250K messages from Twitter, in Italian, from 145 users who declare to suffer from FM, and an equivalent amount of messages from random users as a control group. He built supervised classifiers with traditional machine learning techniques, namely Support Vector Machine and Random Forest, obtaining a 72% accuracy in a cross-validation experiment aimed at predicting the user class as FM or not-FM. The classifiers employ explicit features such as ngrams and lemma counts from the Italian translation of Linguistic Inquiry Word Count (LIWC), which provide an interpretable insight into the language of people with FM. He further implemented a state-of-the-art classifier based on AlBERTo, the Transformer model based on BERT pre-trained on a large collection of Italian tweets, bringing the classification accuracy up to over 78%. The high precision (0.82) on the positive class (FM) represents a promising result towards automatic, non-invasive screening of Fibromyalgia on Italian social media users.

When: 20/05/2022

Where: Sala conferenze at the 3° floor

Sensory vocabularies and their uses in synesthetic metaphor detection

Simona Corciulo will address the interesting challenge of using sensory vocabularies for synesthetic metaphor detection, presenting the case of the multi-sensory museum exhibitions.

Abstract

While humans can intuitively associate words and sensory domains, it is very challenging for machines to process sensory information. Furthermore, the crucial use of sensory vocabularies for synesthetic
metaphor detection involves many difficulties.
During the CCC meeting, she will focus on considerations and insights around sensory vocabularies for natural language processing tasks and specifically for synesthetic metaphor detection.
The aim is to provide new perspectives on their uses for multi-sensory museums exhibition design informed by language.

When: 22/04/2022

Where: in presence and online

Comparison of definitions and values

Alizia Mantovani will present a survey about analogies and differences between Geoheritage and of Geodiversity.

In literature, the relation between geoheritage and geodiversity is well rooted. In fact, the term geodiversity is always present in papers that concern geoheritage. However, the methods of assessment and the characteristics that describe them have different approaches and use terms that are sometimes similar and sometimes different. In literature, it is possible to find different lists of values that characterize the elements of geoheritage, as well as there is a system of characterization of the services. Those lists, even if applied to concepts that are often associated, are rarely associated and cross-used. In this talk, she will explore different points of view on the characterization of geoheritage and of geodiversity through the comparison of the assessment approaches, and how they are similar and different. 

When: 08/04/2022

Where: in presence and online

Rossana Damiano, Stefano De Martino (Dipartimento di Studi Storici) and Elena Devecchi (Dipartimento di Studi Storici) will present the findings of an interesting investigation performed in the PRIN project  “Writing uses: Transmission of Knowledge, Administrative Practices and Political Control in Anatolian and Syro-Anatolian Polities in the II and I millennium BC”.

Title: Models and vocabularies for ancient Near Eastern prosopographies 

Prosopographies, intended as the large scale study of the people’s life events as they emerge from written sources, have been largely used in the last decade to study the social structure of ancient societies. The analysis of professional, kinship, administrative and political relations of the past, informed on real data, can confirm the models put forth by historians and archaeologists through traditional research paradigms, and in some cases suggest new ones. In this sense, the availability of agreed-upon, formally expressed vocabularies for describing these data and the relations to sources is a key factor to the development of methods for the analysis of social networks from the past in support of the work of historians. 

The PRIN project  “Writing uses: Transmission of Knowledge, Administrative Practices and Political Control in Anatolian and Syro-Anatolian Polities in the II and I millennium BC.” (2020-2022) has investigated the adaptation of a factoid-based model of prosopographic data to the case study of Hittite and Kassite civilizations. Aimed at the collaborative creation of prosopographic datasets for large-scale study of Hittite and Kassite social networks, the project has collected a corpus of person records and relations in a Linked Data format. In this seminar, she will describe the design of the vocabularies for the construction of the datasets and the research methods being developed from these data.  

Related links:

https://hfpo.di.unito.it/

https://kfpo.di.unito.it/

When: 11/03/2022

Where: online