Utilização da inteligência artificial na análise de sn: construção de modelos para compreender e prever o comportamento dos utilizadores
Palavras-chave:
Análise de grandes volumes de dados, Aprendizagem automática em SN, Previsão da atividade do utilizador, Algoritmos de classificação, Deteção de padrões de comportamentoResumo
Introdução: Este estudo investiga a aplicação de técnicas de inteligência artificial (IA) e análise de sentimentos para prever traços de personalidade e comportamentos a partir dos dados extensos disponíveis nas redes sociais. O objetivo é entender a dinâmica das interações dos usuários e a disseminação de conteúdo viral através de modelos baseados em IA.
Métodos: A pesquisa emprega diversas técnicas de IA e aprendizado de máquina, com foco especial em processamento de linguagem natural (PLN), para analisar dados de mídia social. A metodologia inclui análise de sentimentos para categorizar textos em respostas emocionais distintas e análise preditiva para prever tendências no engajamento dos usuários e na viralidade do conteúdo.
Resultados: Os resultados indicam que a IA pode prever efetivamente comportamentos e traços de personalidade dos usuários, como neuroticismo, que se correlaciona com maior agressividade e uso mais frequente e prolongado das redes sociais. O estudo identifica padrões e tendências-chave que influenciam as interações dos usuários nas redes sociais.
Discussão: A discussão foca nas implicações do uso da IA na análise de mídias sociais, abordando tanto os avanços tecnológicos quanto as considerações éticas do perfilamento de comportamentos dos usuários. Enfatiza a necessidade de modelos robustos capazes de manejar a complexidade e variabilidade dos dados em redes sociais.
Conclusão: A pesquisa demonstra que a IA e o aprendizado de máquina são ferramentas inestimáveis para a análise de redes sociais, fornecendo insights que podem melhorar estratégias de engajamento dos usuários e entrega de conteúdo. O estudo defende o desenvolvimento e refinamento contínuos de modelos de IA para melhor compreender e prever o comportamento dos usuários.
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