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