Investigating the AlgoRythmics YouTube channel: the Comment Term Frequency Comparison social media analytics method-Reference-Cited by-同舟云学术

Investigating the AlgoRythmics YouTube channel: the Comment Term Frequency Comparison social media analytics method

Published:2022-12-01 Issue:2 Volume:14 Page:273-301
ISSN:2066-7760
Container-title:Acta Universitatis Sapientiae, Informatica
language:en
Short-container-title:

Author:

Osztián Pálma Rozália¹^ORCID,Kátai Zoltán¹^ORCID,Sántha Ágnes²^ORCID,Osztián Erika¹^ORCID

Affiliation:

1. Sapientia Hungarian University of Transylvania Târgu Mureş , Romania , Department of Mathematics-Informatics

2. Sapientia Hungarian University of Transylvania Târgu Mureş , Romania , Department of Applied Social Sciences

Abstract

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.

Publisher

Walter de Gruyter GmbH

Link

https://www.sciendo.com/pdf/10.2478/ausi-2022-0016

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