Python for Big Data Psychology Research

Subjects: Psychology >> Applied Psychology submitted time 2022-03-18

吕思华 宋梦瑶 莫柳铃 李东启 朱廷劭

Abstract：

This paper introduces the big data research method in psychology in details, taking Ninety-Nine Articles website as an example. Using the collected textual data, we calculated word frequencies as features, then trained machine learning models, and used models to predict life satisfaction for texts crawled from Ninety-Nine Articles website, providing inspiration and help for beginners in big data research. This paper introduces text-based word frequency calculation using Python and sentiment dictionary through specific examples, and completes the training, testing and application of the machine learning model using Python's scikit-learn library. Furthermore, we uploaded the accompanying source program for direct operation. This paper introduces the big data research method of machine learning modeling via text-based word frequency. Our article emphasizes how to apply the technology, and thus we introduce the technology in a more basic way with less involvement of the technical principles.

Peer Review Status:Awaiting Review

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