TY - JOUR T1 - Knowledge Transfer Mechanisms Using Text Mining and Sentiment Analysis – Case in an Online Collaboration AU - Davıd, Firmansyah AU - Nursyahrına, Nursyahrina AU - Syahranı, Anna AU - Mandaranı, Putri AU - Putra, Dede Wira Trise PY - 2022 DA - December DO - 10.55549/epstem.1218708 JF - The Eurasia Proceedings of Science Technology Engineering and Mathematics JO - EPSTEM PB - ISRES Publishing WT - DergiPark SN - 2602-3199 SP - 21 EP - 34 VL - 19 LA - en AB - This study aims to test, examine, and validate text-based human-machine knowledge transfer (KT) by comparing it with human-human KT. The online discussion experiment was carried out via WhatsApp group chats. Chat sentiment was determined using text mining and sentiment analysis and then compared with the respondent's understanding of the knowledge obtained from interviews. The results have shown that human-machine KT is close to human-human KT. By analyzing the correlation coefficient between the two, it is proven that sentiment indicates an understanding of knowledge. Positive sentiment shows similar or in-line understanding between the source and recipient of knowledge and indicates the achievement of KT objectives. Neutral sentiment indicates incomprehension due to the failure of KT. Meanwhile, negative sentiment is ambiguous; it may indicate an incomprehension or a misunderstanding of the knowledge received. This study contributes to the area of knowledge and sentiments, showing that the effectiveness of text-based KT activity can be identified using the sentiment analysis approach. KW - Human-machine KW - Knowledge transfer KW - Online KW - Sentiment analysis KW - Text mining CR - David, F., Nursyahrina, N., Syahrani, A., Mandarani, P., & Putra, D.W.T. (2022). Knowledge transfer mechanisms using text mining and sentiment analysis – case in an online collaboration. The Eurasia Proceedings of Science, Technology, Engineering & Mathematics (EPSTEM), 19, 21-34. UR - https://doi.org/10.55549/epstem.1218708 L1 - https://dergipark.org.tr/en/download/article-file/2830375 ER -