Comparing Academic Papers of Students and Experts in terms of Linguistic Features with Natural Language Processing

Comparing Academic Papers of Students and Experts in terms of Linguistic Features with Natural Language Processing

연구 분야: Artificial Intelligence

학회: ICSET'20: 2020 The 4th International Conference on E-Society, E-Education and E-Technology

In graduate education, the quality of academic papers can reflect individual scientific research achievements. This study compared the differences in linguistic features between the papers of experts and graduate students with natural language processing. More specifically, for revealing the problems existing in the writing of graduate students, this study analyzed academic papers in a journal as experts and those of graduate students by using Chinese word segmentation. The study found that the graduate students and experts have differences in the use of various parts of speech (i.e., nouns, verbs, adjectives, pronouns, and conjunctions) and connective words (i.e., organization, comparison, summarization, etc.). The results may be helpful for further designing scaffolding to improve the writing quality of graduate students’ papers.