Cluster and Sentiment Analyses of YouTube Textual Feedback of Programming Language Learners to Enhance Learning in Programming

被引:0
作者
Bringula, Rex P. [1 ,2 ]
Noel Victorino, John [2 ]
De Leon, Marlene M. [2 ]
Estuar, Regina [2 ]
机构
[1] Univ East, Manila, Philippines
[2] Ateneo Manila Univ, Manila, Philippines
来源
PROCEEDINGS OF THE FUTURE TECHNOLOGIES CONFERENCE (FTC) 2019, VOL 2 | 2020年 / 1070卷
关键词
Learning; Programming; Sentiment analysis; Videos; YouTube; TUBE;
D O I
10.1007/978-3-030-32523-7_67
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This study intends to determine the clusters and sentiments of feedback of YouTube users in learning to program in Python and C++. Toward this goal, a total of 2,583 feedback on introductory video tutorials about Python and C++ were collected. It is found that the words "thanks" and "thank" were the most frequently occurring word in both YouTube videos - indicating appreciation and helpfulness of the video tutorials. The results of k-means cluster analyses further disclosed that groups of feedback are similar across the two languages, i.e., confirmation, helpfulness, gratitude, and recommendation. YouTube users expressed positive sentiments towards the tutorial videos. Implications to teaching programming and YouTube video content development are presented. Limitations of the study are also offered.
引用
收藏
页码:913 / 924
页数:12
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