Automatically Infer Human Traits and Behavior from Social Media Data

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Pan1804.04191.pdf (246.58 KB)

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https://arxiv.org/abs/1804.04191

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http://hdl.handle.net/11603/10728

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UMBC Information Systems Department
UMBC Faculty Collection
UMBC Student Collection

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2018

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journal articles preprints
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This item may be protected under Title 17 of the U.S. Copyright Law. It is made available by UMBC for non-commercial research and education. For permission to publish or reproduce, please contact the author.

Subjects

social media
human behavior
machine learning

Abstract

Given the complexity of human minds and their behavioral flexibility, it requires sophisticated data analysis to sift through a large amount of human behavioral evidence to model human minds and to predict human behavior. People currently spend a significant amount of time on social media such as Twitter and Facebook. Thus many aspects of their lives and behaviors have been digitally captured and continuously archived on these platforms. This makes social media a great source of large, rich and diverse human behavioral evidence. In this paper, we survey the recent work on applying machine learning to infer human traits and behavior from social media data. We will also point out several future research directions.