| Title |
Analysis of Topic Evolution in Educational Data |
| Authors |
(Lei Peng) ; (Kwankamol Nongpong) ; (Paitoon Porntrakoon) |
| DOI |
https://doi.org/10.5573/IEIESPC.2023.12.2.178 |
| Keywords |
Website; Crawler; Topic model; Topic transfer; Development |
| Abstract |
Analyzing the developing trends of educational data has always been an important issue. However, it is challenging to do it manually because of the data expansion in recent years. A topic evolution-analyzing framework, comprised of a data crawling module and a topic-processing module, is proposed to solve this problem. The Chongqing Three Gorges Medical College of China was used as a case for the experiment, and the framework was implemented using Python language. First, the data were obtained from the website, and its format was reorganized, which is appropriate to be fed into the topic-processing module. Subsequently, all topics were obtained and interpreted as several related phrases. Finally, the topic evolution was obtained over years and months. This work can help education organizations with their historical information summarization, contributing to their development planning and providing academic support to the decision-makers. |