Automatically Infer Human Traits and Behavior from Social Media Data

dc.contributor.authorPan, Shimei
dc.contributor.authorDing, Tao
dc.date.accessioned2018-05-08T13:14:22Z
dc.date.available2018-05-08T13:14:22Z
dc.date.issued2018
dc.description.abstractGiven 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.en_US
dc.description.urihttps://arxiv.org/abs/1804.04191en_US
dc.format.extent7 pagesen_US
dc.genrejournal articles preprintsen_US
dc.identifierdoi:10.13016/M2S17SW3D
dc.identifier.urihttp://hdl.handle.net/11603/10728
dc.language.isoen_USen_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.isAvailableAtUMBC Faculty Collection
dc.relation.isAvailableAtUMBC Student Collection
dc.relation.ispartofUMBC Information Systems Department Collection
dc.rightsThis 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.
dc.subjectsocial mediaen_US
dc.subjecthuman behavioren_US
dc.subjectmachine learningen_US
dc.titleAutomatically Infer Human Traits and Behavior from Social Media Dataen_US
dc.typeTexten_US

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