Browsing by Author "ALASHI, SHUKURAT OPEYEMI"

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    USING ARTIFICIAL INTELLIGENCES AS A TOOL FOR ANALYZING VIDEOS OF SELECTED SKIT MAKERS IN LAGOS STATE
    (2023) ALASHI, SHUKURAT OPEYEMI
    Skit Makers aims to contribute to the understanding of how AI can assist in the analysis of media content produced by skit makers and offer insights on the ethical and security implications of using AI in media content analysis (juwon, 2021). Artificial intelligence (AI) has become an increasingly popular tool in various industries, including video analysis and content creation. One area of focus for AI in video analysis is the analysis of skit makers in Lagos state (Oyemi, B.A. 2021). Lagos state skit makers have become popular on social media platforms such as Instagram and YouTube, where they create and share short comedy videos (Awolesi, 2021). The goal is to explore the potential of AI as a tool for analysing videos of selected skit makers (Kayode, O. 2021). Specifically, this study will examine the accuracy and reliability of AI-based tools for analysing videos of selected skit makers, and the potential of AI to provide insights into the creative process of skit makers (Smith, S.A. 2020). The main objective of this study is to develop an AI model that can analyse videos of selected skit makers in Lagos state. The specific objectives of the study are: To identify the artificial intelligence models for analysing videos of selected skit makers, to use the artificial intelligence model in analysing skit makers' videos, to determine the accuracy analysis of the AI mode in skit makers' videos and to evaluate the effectiveness of using artificial intelligence as a model for analysing videos of selected skit makers. The research method used in the study is the survey method, which involves collecting data from a predefined group of respondents to gain insights into various topics of interest. The survey focused on skit makers and aimed to gather information from journalists, media professionals, and the public about their perceptions, experiences, and attitudes towards skit makers. By conducting surveys or questionnaires, the researchers gained valuable insights into current practices, challenges, and potential improvements related to AI implementation in skit making. The population of this study consist of 100 despondent and 80 sample size. The findings revealed that various AI models were considered suitable for analyzing skit makers' videos. The Recurrent Neural Network (RNN), Support Vector Machine (SVM), Transformer model, Generative Adversarial Network (GAN), and Random Forest received positive agreement, indicating their effectiveness in different aspects of video analysis.