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| Classifying Social Media Users with Machine Learning |
Gang Li,Huayang Zhou,Jin Mao( ),Sijing Chen |
| Center for Studies of Information Resources, Wuhan University, Wuhan 430072, China |
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Abstract [Objective] This paper uses multi-dimensional information of social media users to automatically classify them. [Methods] First, we defined social media users as individual, media, government, and organization. Then, we extracted the following features from user profiles: demographic characteristics, namings, and self-descriptions. Third, we created a user classification models based on machine learning algorithms and evaluated its performance with real Twitter dataset. [Results] Both precision and recall of the proposed model were greater than 83%. The naming, demographic characteristics, and self-description features posed increasing contributions to the classification model. [Limitations] The sample size needs to be expanded, which helps us better analyzed the characteristics of different users. [Conclusions] The proposed method could accurately identify four types of users, which benefits social media user classification research in the future.
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Received: 31 October 2018
Published: 29 September 2019
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Corresponding Authors:
Jin Mao
E-mail: danveno@163.com
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