Publicação

Generation of breaking news contents using LLM (Large Language Models) and SEO (Search Engine Optimization)

Detalhes bibliográficos
Resumo:	With the rapid advance of digital technologies, verifying the authenticity of news has become increasingly difficult. The proliferation of social media platforms and websites has facilitated the spread of misinformation and biased content, undermining the traditional role of news as a source of unbiased information. The fake news phenomenon, amplified by platforms such as Facebook, WhatsApp and Twitter, has demonstrated its ability to influence public opinion by taking advantage of the viral nature of social sharing. This thesis aims to address these challenges by proposing a solution to support the creation of credible news content quickly, impartially and effectively. The aim is to harness Artificial Intelligence (AI) and Search Engine Optimisation (SEO) technologies to develop a news platform capable of quickly producing comprehensive articles on trending topics. Using AI, the platform seeks to aggregate and analyse information from multiple reliable sources, ensuring that the news content is factual and unbiased. The main components of the proposed platform include real-time monitoring of hot topics using tools such as Google Trends, which identify popular searches related to current events. These trending topics serve as input for the AI-powered system, which retrieves and synthesises information from reliable news sources. The reliable sources are selected by the user from a list of available sources (online newspapers and news agencies, etc.). Using generative AI, based on a Large Language Model (LLM), the platform generates concise and informative news summaries, presenting a complete picture of the topic. User empowerment is fundamental to the platform’s design. Users have the autonomy to select, modify and approve the articles generated by the AI, ensuring that the final result meets their editorial standards and is in line with the context in which it will be published. This process not only increases the user’s credibility as a reliable source of information, but also promotes transparency in the dissemination of news content. Through this innovative approach, the thesis aims to contribute to the evolution of digital journalism by demonstrating how AI and SEO technologies can be effectively integrated to combat disinformation and improve access to credible news sources. By enabling users to quickly disseminate factual and unbiased news in an era dominated by digital information overload, the platform represents a significant step towards restoring trust and reliability in online news consumption.
Autores principais:	Pereira, João Paulo Machado
Assunto:	Artificial intelligence News SEO Python Journalist Computer system Inteligência artificial Notícias Jornalista Sistema informático
Ano:	2024
País:	Portugal
Tipo de documento:	dissertação de mestrado
Tipo de acesso:	acesso aberto
Instituição associada:	Instituto Politécnico de Viana do Castelo
Idioma:	inglês
Origem:	Repositório Científico IPVC