Propostas Submetidas

DEI - FCTUC
Gerado a 2024-03-28 13:45:02 (Europe/Lisbon).
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Titulo Estágio

Fake News Identification in Social Networks

Áreas de especialidade

Sistemas Inteligentes

Engenharia de Software

Local do Estágio

CISUC

Enquadramento

The constant growth of online platforms like Twitter, or Facebook, shows the importance of social media in nowadays people’s lives. We are now all connected to friends, family, and communities, all around the world, and share information on a daily basis. Different social networks have been created and popularized, like the above mentioned Twitter and Facebook, but also Instagram, LinkedIn, or Reddit.

Mostly considered as an entertainment tool, social networks can be an important source of information, since relevant and valuable information is publicly shared among users, and may be used towards the resolution of challenges faced by individuals and companies. Considering their relevance, especially in information spread, they have gained increasing importance and are being widely studied in many fields of research, especially due to their multiple applications. An important trend in social networks is the profusion of fake news that we are not completely aware of, but are in fact present, e.g., in political campaigns or other autonomous bot-based systems.

Information regarding the confidence of the information source, or the annotators, might be relevant as an additional input so users can share information without being deceived to share content that is fake.

Objetivo

In this internship it is proposed to research and implement learning models able to identify fake news in social networks, by outputting a confidence score regarding the news itself.

To achieve this goal, the following objectives will be pursued:
- Study the state of the art
- Study the available datasets and sources of online information (API)
- Study the available frameworks for model development
- Define, implement, and fine tune the learning architecture
- Propose and deploy test setup

Plano de Trabalhos - Semestre 1

- Literature review
- Identification of datasets and other sources for model development
- Identification and study of available frameworks for model development
- Definition of the architecture of the system
- Design of experiences for model evaluation
- Writing of the intermediate report

Plano de Trabalhos - Semestre 2

- Implementation of the proposed approach
- Fine tuning models
- Testing and evaluation of the performance
- Writing a scientific article
- Writing the final report

Condições

This work should take place in the context of a research project in a CISUC lab.
There is the possibility of a 3-month CISUC scholarship (renewable).

Observações

During the application phase, doubts related to this proposal, namely regarding the objectives and conditions, should be clarified with the advisors, by e-mail (catarina@dei.uc.pt) or a meeting to be arranged after a contact by email.

Orientador

Catarina Silva, Joana Costa, Hugo Oliveira
catarina@dei.uc.pt 📩