首页> 外文期刊>International Journal of Combinatorial Optimization Problems and Informatics >Proposal of a Sentiment Analysis Model in Tweets for Improvement of the Teaching - Learning Process in the Classroom Using a Corpus of Subjectivity
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Proposal of a Sentiment Analysis Model in Tweets for Improvement of the Teaching - Learning Process in the Classroom Using a Corpus of Subjectivity

机译:在推文中建立情感分析模型的建议,以利用主体性语料库改善课堂教学过程。

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In this paper, we propose a sentiment analysis model for the assessment of teacher performance in the classroom by tweets written by a pilot group of college students. Naive Bayes (NB) is the technique to be applied to classify tweets based on the polar express emotion (positive, negative and neutral), to carry out this process, a dataset fits adding distinctive terms of context as possible features to support the classification process.
机译:在本文中,我们提出了一种情绪分析模型,用于通过大学生试点小组撰写的推文来评估课堂上教师的表现。朴素贝叶斯(NB)是一种用于基于极性表达情绪(正,负和中性)对推文进行分类的技术,以执行此过程,数据集适合添加独特的上下文项作为可能的特征以支持分类过程。

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