Data analysis and visualization on trending YouTube statistic / Nik Hafifi Mamat

YouTube is a free video hosting Internet site that permits participants to keep and offer video content material. YouTube helps videos that constitute capability content that has content material that would come to be famous in a tremendously short time known as trends. YouTube Trends videos assist visitors see what is going on YouTube and across the world. Trends aim to function compelling videos through a wide variety of audiences. However, there are numerous issues faced through content creators. Among them is that content creators cannot recognize the types of videos that visitors like in YouTube. Content creators need to are expecting the amount of YouTube’s viewing capabilities to assist them come up with ideas or create videos that have content recognizing the types of movies that visitors want to watch. To overcome this problem, a technique was carried out on this study through visualizing records from YouTube trending statistics. This studies additionally assists content creators through growing data visualizations that examine the information of streaming videos that represent records in machine learning. The goal of this study will assist content creators examine and combine records to identify factors influencing the popularity of YouTube videos, which can be now famous and visualize the data for their YouTube videos. In this project, a dataset of YouTube trending videos taken from the kaggle website will be incorporated into Jupyter Notebook for data analysis and will be displayed via Voila to the website. The project use three phases in the methodology which is project initialization, system formulation and evaluation. For the findings and analysis, this project has used the user acceptance test (UAT) method which has 11 questions that have been answered by 30 respondents. Results obtained from UAT shows this prototype was accepted by the majority of respondents for Data Analysis and Visualization on Trending YouTube Statistic. Hence, this project helps the content creator knows how to design their content for their video based on the factor influence of the YouTube trending videos.