调查YouTube频道的算法:评论词频率比较社交媒体分析方法

IF 0.3 Q4 COMPUTER SCIENCE, THEORY & METHODS
Pálma Rozália Osztián, Z. Kátai, Ágnes Sántha, Erika Osztián
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引用次数: 0

摘要

摘要本文采用评论词频比较社交媒体分析方法对算法YouTube频道的评论进行了研究。评论术语频率比较是一种有用的工具,可以帮助我们了解用户如何讨论社交媒体平台(如Youtube频道),并识别与受众互动的机会。了解观众对视频的意见和反应,确定人们讨论特定主题的趋势和模式,以及衡量视频在实现预期目标方面的有效性,是频道发展的最重要的观点之一。Youtube评论分析是一个很有价值的工具,它可以帮助我们了解AlgoRythmics频道视频是如何被观众接受的,并找到改进的机会。我们的研究集中在用户反馈的重要性基于十个算法可视化视频从算法频道。为了找到我们的渠道如何运作的证据和改进的新思路,我们使用了所谓的评论词频率比较社交媒体分析方法来调查用户反馈的主要特征。我们使用Youtube Studio Analytics和Mozdeh大数据分析工具对评论进行了分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Investigating the AlgoRythmics YouTube channel: the Comment Term Frequency Comparison social media analytics method
Abstract In this paper we investigate the comments from the AlgoRythmics YouTube channel using the Comment Term Frequency Comparison social media analytics method. Comment Term Frequency Comparison can be a useful tool to understand how a social media platform, such as a Youtube channel is being discussed by users and to identify opportunities to engage with the audience. Understanding viewer opinions and reactions to a video, identifying trends and patterns in the way people are discussing a particular topic, and measuring the effectiveness of a video in achieving its intended goals is one of the most important points of view for a channel to develop. Youtube comment analytics can be a valuable tool looking to understand how the AlgoRythmics channel videos are being received by viewers and to identify opportunities for improvement. Our study focuses on the importance of user feedback based on ten algorithm visualization videos from the AlgoRythmics channel. In order to find evidence how our channel works and new ideas to improve we used the so-called comment term frequency comparison social media analytics method to investigate the main characteristics of user feedback. We analyzed the comments using both Youtube Studio Analytics and Mozdeh Big Data Analysis tool.
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来源期刊
Acta Universitatis Sapientiae Informatica
Acta Universitatis Sapientiae Informatica COMPUTER SCIENCE, THEORY & METHODS-
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