Q2YouTube: Quantitative and Qualitative Information Analysis based Influencer-aware YouTube Channel Ranking Scheme

Abstract

With the development of big data, artificial intelligence and deep learning, various social information networks are becoming exponentially intelligent. Of all the various social networks, YouTube is so popular that it is called the YouTube era. Not only video viewers, but also actual video producers, influencer youtubers, are increasing, allowing individuals as well as operators to use and market contents on various topics. As the number of users and contents increases, the choice of information increases, but it is more difficult for individual and business owners to select information that meets their needs. Therefore, this study aims to analyze the channel of the subject that the user needs from various angles and provide the ranking of the channel to individuals and businesses. We crawl the channels and measure the average awareness and influencer youtuber of channels and channel videos by analyzing the qualitative data of quantitative data and comments which are statistical information. As a final case study, we recommend the English learning channel to individual users based on numerical data statistics and emotional analysis results to show the maximum of flipped learning effect regardless of time and space. Plus, we prove the maximum of the effectiveness of marketing by influencer channel which is influential to operators in the medium and long term.