Publication Type

Conference Proceeding Article

Version

acceptedVersion

Publication Date

11-2020

Abstract

Personality inference has received widespread attention for its potential to infer psychological well being, job satisfaction, romantic relationship success, and professional performance. In this research, we focus on Conscientiousness, one of the well studied Big Five personality traits, which determines if a person is self-disciplined, organized, and hard-working. Research has shown that Conscientiousness is related to a person's academic and workplace success. For an expert to evaluate a person's Conscientiousness, long-term observation of the person's behavior at work place or at home is usually required. To reduce this evaluation effort as well as to cope with the increasing trend of human behavior turning digital, there is a need to conduct the evaluation using digital traces of human behavior. In this paper, we propose a novel framework, called HAPE, to automatically infer an individual's Conscientiousness scores using his/her behavioral data in an E-learning system. We first determine how users learn in the E-learning system, and design a novel Pattern Relational Graph Embedding method to learn the representations of users, their learning actions, and learning situations. The interaction between users, learning actions and situations characterizes the learning style of a user. Through experimental studies on real data, we demonstrate that HAPE framework outperforms the baseline methods in the Conscientiousness inference task

Keywords

Personality inference, E-learning system, activity pattern mining, graph embedding

Discipline

Databases and Information Systems | Numerical Analysis and Scientific Computing | Online and Distance Education | Personality and Social Contexts

Research Areas

Data Science and Engineering

Publication

2020 IEEE International Conference on Data Mining ICDM: Virtual, November 17-20: Proceedings

First Page

1292

Last Page

1297

ISBN

9781728183169

Identifier

10.1109/ICDM50108.2020.00166

Publisher

IEEE

City or Country

Piscataway, NJ

Embargo Period

5-10-2021

Copyright Owner and License

Authors

Additional URL

https://doi.org/10.1109/ICDM50108.2020.00166

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