文章基本信息

标题：Classification of user attitudes in Twitter -beginners guide to selected Machine Learning libraries
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作者：Marta Sokolowska ; Maciej Mazurek ; Marcin Majer 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2019
卷号：52
期号：27
页码：394-399
DOI：10.1016/j.ifacol.2019.12.692
语种：English
出版社：Elsevier
摘要：This paper presents an interesting use case for learning as well as teaching basics of Machine Learning systems. Starting from a brief historical outline of the ML, the authors propose and compare a set of popular ML libraries in an interesting exemplary implementation, to present their usability. The paper also describes text classification methods, the aim of which is to distinguish positive and negative labels of particular messages within the Twitter social network. The study is summarized by a brief comparison of the quality of the classification of the libraries and methods used, as an assessment of their suitability. Final thoughts on the importance of teaching ML are included.
关键词：KeywordsMachine LearningNatural Language ProcessingEducationTwitterSentiment AnalysisfastTextTensorFlowScikit-Learn