Fake news, fake accounts, social media analysis, data mining, machine learning, NLP, feature engineering
The research collaborator will work on the definition and development of software prototypes for ranking the content produced and diffused over the Internet and social networks, as well as their producers and spreaders. Final aim is assessing credibility of such content, and trustworthiness of the creators and spreaders. The software solutions will process web data and data from social media, primarily by means of machine learning techniques. The position is framed into the IMT Lucca-funded PAI project TOFFEe "Tools for fighting fakes".
The planned research activities are as follows:
- to continue the studies already started within the Toffee project on the detection of bots and disinformation on Twitter, primarily using machine learning techniques;
- study how to extend these studies to other social platforms (e.g. Instagram);
- collect new datasets from social media related to relevant events, both Italian and foreign;
- contribute to the drafting of scientific articles for the dissemination of the results obtained.
The activities will be carried out working together with the participants of the Toffee project.
- Master's degree (preferential: Computer Science, Computer Engineering, Physics, Mathematics, Statistics)
- Good knowledge of written and spoken English.
- web programming languages;
- machine learning algorithms and related libraries - web crawling/scraping;
- statistics techniques and related libraries - NLP and related libraries;
- Applications: Web and Social Media analysis.
ING-INF/05 Sistemi di elaborazione delle informazioni;
MAT/06 Probabilità e statistica matematica;
MAT/07 Fisica matematica;
FIS/02 Fisica teorica, modelli e metodi matematici;
FIS/07 Fisica applicata (a beni culturali, ambientali, biologia e medicina).
"TOols for Fighting FakEs” (TOFFEe), finanziato nell’ambito del bando PAI – Programmi di Attività Integrata 2018 - codice P0140.
Apply ONLINE only.
Before filling in the application form, please read thoroughly the full call and collect all the files you may need:
- Personal info and contact info (compulsory);
- University degree (compulsory);
- PhD (compulsory only if stated in the full call).
- The scanned copy of a valid identity document (Passport or Identity Card - compulsory);
- Your CV in English (compulsory).