YOUTUBE ALGORITHM MODELING WITH NEURAL NETWORKS FOR VIDEO PERFORMANCE ANALYSIS

YOUTUBE ALGORITHM MODELING WITH NEURAL NETWORKS FOR VIDEO PERFORMANCE ANALYSIS

With the shift from the conventional world to the virtual world, understanding Internet algorithms is essential to adapt to global developments, particularly in the realms of information and commerce. This research involves the development of a machine learning model capable of predicting the vie...

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Main Author: Hasan Amrulloh, Natsir
Format: Final Project
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/81627
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Institution: Institut Teknologi Bandung
Language: Indonesia
id id-itb.:81627
spelling id-itb.:816272024-07-02T10:51:45ZYOUTUBE ALGORITHM MODELING WITH NEURAL NETWORKS FOR VIDEO PERFORMANCE ANALYSIS Hasan Amrulloh, Natsir Indonesia Final Project backpropagation, factor weight, machine learning, views, Youtube INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/81627 With the shift from the conventional world to the virtual world, understanding Internet algorithms is essential to adapt to global developments, particularly in the realms of information and commerce. This research involves the development of a machine learning model capable of predicting the view count of a Youtube video by analyzing the weight of each factor influencing the video's performance, namely title interestingness, video interestingness, video retention, number of subscribers, and video response. The model was developed using a neural network algorithm, resulting in a model that can predict the number of viewers of a video with an error rate of 8.62%. Additionally, the model reveals that the most influential factor on the number of views in the first layer is the number of subscribers a channel has, with a weight percentage of 72.03%, and video quality in the second layer, with a weight percentage of 84.33%. . text
institution Institut Teknologi Bandung
building Institut Teknologi Bandung Library
continent Asia
country Indonesia
Indonesia
content_provider Institut Teknologi Bandung
collection Digital ITB
language Indonesia
description With the shift from the conventional world to the virtual world, understanding Internet algorithms is essential to adapt to global developments, particularly in the realms of information and commerce. This research involves the development of a machine learning model capable of predicting the view count of a Youtube video by analyzing the weight of each factor influencing the video's performance, namely title interestingness, video interestingness, video retention, number of subscribers, and video response. The model was developed using a neural network algorithm, resulting in a model that can predict the number of viewers of a video with an error rate of 8.62%. Additionally, the model reveals that the most influential factor on the number of views in the first layer is the number of subscribers a channel has, with a weight percentage of 72.03%, and video quality in the second layer, with a weight percentage of 84.33%. .
format Final Project
author Hasan Amrulloh, Natsir
spellingShingle Hasan Amrulloh, Natsir
YOUTUBE ALGORITHM MODELING WITH NEURAL NETWORKS FOR VIDEO PERFORMANCE ANALYSIS
author_facet Hasan Amrulloh, Natsir
author_sort Hasan Amrulloh, Natsir
title YOUTUBE ALGORITHM MODELING WITH NEURAL NETWORKS FOR VIDEO PERFORMANCE ANALYSIS
title_short YOUTUBE ALGORITHM MODELING WITH NEURAL NETWORKS FOR VIDEO PERFORMANCE ANALYSIS
title_full YOUTUBE ALGORITHM MODELING WITH NEURAL NETWORKS FOR VIDEO PERFORMANCE ANALYSIS
title_fullStr YOUTUBE ALGORITHM MODELING WITH NEURAL NETWORKS FOR VIDEO PERFORMANCE ANALYSIS
title_full_unstemmed YOUTUBE ALGORITHM MODELING WITH NEURAL NETWORKS FOR VIDEO PERFORMANCE ANALYSIS
title_sort youtube algorithm modeling with neural networks for video performance analysis
url https://digilib.itb.ac.id/gdl/view/81627
_version_ 1822997383743537152

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