韩国国际中文学习者在线评论内容挖掘与情感倾向分析 — 基于YouTube平台

Content Mining and Emotional Tendency Analysis of Online Comments from Korean International Chinese Learners : Based on YouTube platform

YouTube is a crucial platform for Korean learners of Chinese, offering a wealth of resources and a large community of Chinese language learners. Compared to traditional classrooms, learners on this platform have more participation and choice. This study collected 16,489 Korean comments from 66 international Chinese learning videos on YouTube using Python, conducted word segmentation with Python-KoNLPy, performed content analysis using LDA, and carried out sentiment analysis with SnowNLP to identify factors influencing Korean learners’ evaluations. Finally, grounded theory was used to develop a model of factors affecting user sentiment tendencies, aiming to provide insights for improving and optimizing online international Chinese teaching from the learner’s perspective. The study found that: 1) teaching quality, course content, HSK exam preparation, and the consistency of content updates from subscription channels are the factors online learners are most concerned about; 2) the majority of learners hold a positive attitude towards international Chinese teaching videos on YouTube; 3) individual factors, teacher factors, course factors, and satisfaction levels are the four primary factors influencing the sentiment tendencies of Korean learners.

YouTube是韩国学习者学习中文的重要网络平台，上面汇集了大量的汉语学习者与汉语学习资源。相较于传统课堂，学习者拥有了更多的参与权与选择权。文章通过Python爬取了66个国际中文学习视频中的16489条韩文评论，利用Python-KoNLPy进行分词，LDA进行内容挖掘，SonwNLP进行情感分析后，得出影响韩国汉语学习者评价的因素，最后运用扎根理论，构成用户情感倾向影响因素模型，旨通过“学习者”视角对在线国际中文教学完善与优化提供一定的参考。研究发现：1）授课教师、课程内容、HSK考试、订阅号的持续输出性等是线上学习者相对更关注的；2）大多数学习者对YouTube上的国际中文教学短视频持积极态度；3）个体因素、教师因素、课程因素与满足度成为影响韩国汉语学习者情感倾向的四大因素。