基于Python的学士学位论文线上评价数据的分析与统计研究

Analysis and Statistical Study on Online Evaluation Data of Bachelor’s paper Based on Python

本文通过唐山师范学院的毕业论文管理平台进行了本科生毕业论文专家评阅信息的数据采集,并对采集的数据进行了数据清洗,修正了数据格式上的错误。运用文本分析法和Jieba库对评语进行分词处理,提取"有待""缺少""不足"等10个关键词进行评语文本挖掘。首先,根据"出现关键词则扣分"的原则,分析论文评阅评语,建立评阅专家观点评价模型及评分标准;其次,根据评分标准计算出每篇论文的文本分析结果所对应分数;最后,根据采集的论文分数的的一致性分析,计算出综合得分。结合论文评价与文本分析结果,给出评价标准,对每篇论文进行综合评价,计算出综合得分。

This paper collects the data of expert evaluation information of undergraduate graduation thesis through the graduation thesis management platform of Tangshan Normal University, cleans the collected data, and corrects the errors in data format. The text analysis method and Jieba database are used to segment the comments, and 10 keywords such as "to be", "missing" and "insufficient" are extracted for comment text mining. Firstly, according to the principle of "deduct points if there are keywords", this paper analyzes the evaluation comments of papers, and establishes the evaluation model and scoring standard of expert opinions;Secondly, the score corresponding to the text analysis result of each paper is calculated according to the scoring standard;Finally, according to the consistency analysis of the collected paper scores, the comprehensive score is calculated. Combined with the results of paper evaluation and text analysis, the evaluation criteria are given, the comprehensive evaluation of each paper is carried out, and the comprehensive score is calculated.