| dc.contributor | 教育與心理研究 | |
| dc.creator (作者) | 林松柏 | |
| dc.date (日期) | 2019-09 | |
| dc.date.accessioned | 24-Nov-2020 15:22:39 (UTC+8) | - |
| dc.date.available | 24-Nov-2020 15:22:39 (UTC+8) | - |
| dc.date.issued (上傳時間) | 24-Nov-2020 15:22:39 (UTC+8) | - |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/132820 | - |
| dc.description.abstract (摘要) | 教育主體為學生，學校經營管理應視學生為校園主人，而非過客。因此，校務研究相當重視學生所反映的意見，能夠即時持續地蒐集與分析學生的真實意見則是校務研究的重要課題。本研究運用文字探勘與情緒分析，蒐集大學生於網路社群平臺的文字內容進行分析。研究結果發現，大學生於網路社群平臺的留言內容多關注生活面向的需求問題，故校務研究者若能運用文字探勘比較情緒的跨時期變動情形，將有助於察覺敏感性的校園議題。 | |
| dc.description.abstract (摘要) | Students are the primary stakeholders in education and are thus the school hosts, not guests, regarding school management. Accordingly, institutional research has paid considerable attention to students’ true opinions; institutional researchers must immediately and continually collect and analyze these opinions. This study combined text mining and sentiment analysis to construct an institutional research method that was used to analyze real data obtained from social network text content. The study results revealed that social network text content focused on students’ basic daily living needs. Institutional researchers could use this method to conduct a comparative analysis of dynamic emotions across time to determine sensitive campus issues. | |
| dc.format.extent | 5653962 bytes | - |
| dc.format.mimetype | application/pdf | - |
| dc.relation (關聯) | 教育與心理研究, 42(3), 79-109 | |
| dc.subject (關鍵詞) | 大數據 ; 文字探勘 ; 校務研究 | |
| dc.subject (關鍵詞) | big data ; text mining ; institutional research | |
| dc.title (題名) | 大學生網路社群平臺巨量資料探勘之應用 | |
| dc.title (題名) | Applying Big Data Mining in University Students’ Social Network | |
| dc.type (資料類型) | article | |
| dc.identifier.doi (DOI) | 10.3966/102498852019094203004 | |
| dc.doi.uri (DOI) | https://doi.org/10.3966/102498852019094203004 | |
