Sentiment analysis on Twitter in relation to AI technology for image generation

• Autores: Rosales Espinoza, Antony Pyero, Gonzales Suarez, Juan Carlos
• Formato: artículo
• Fecha de Publicación: 2024
• Institución: Universidad La Salle
• Repositorio: Revistas - Universidad La Salle
• Lenguaje: español
• OAI Identifier: oai:ojs.revistas.ulasalle.edu.pe:article/125
• Enlace del recurso: https://revistas.ulasalle.edu.pe/innosoft/article/view/125; https://doi.org/10.48168/innosoft.s15.a125; https://purl.org/42411/s15/a125; https://n2t.net/ark:/42411/s15/a125
• Nivel de acceso: acceso abierto
• Materia: Artificial intelligence; Sentiment analysis; Convolutional neural network; Artistic field; Twitter; Inteligencia artificial; Análisis de sentimiento; Red neuronal convolucional; Ámbito artístico

Advances in artificial intelligence (AI) technology have led to significant improvements in image generation in terms of speed and quality. However, it has generated concern and uncertainty among artists, who fear being replaced by AI in their field of work. In this context, the objective was to analyse Tweets defining the impact of artificial intelligence (AI) on the adoption of imaging technologies. For this purpose, the collection, creation and evaluation of a convolutional neural network that classifies the data according to a sentiment analysis between positive and negative was carried out. Finally, the research determined the loss rate of 63%, the accuracy with 61% and the ROC curve around 64% of a convolutional neural network for predicting Tweets.