The language of vocational interests on social media

Du, Yan Yi Lance

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https://hdl.handle.net/2142/120547 Copy

Description

Title

The language of vocational interests on social media

Author(s)

Du, Yan Yi Lance

Issue Date

2023-04-28

Director of Research (if dissertation) or Advisor (if thesis)

Drasgow, Fritz

Committee Member(s)

Roberts, Brent W

Department of Study

Psychology

Discipline

Psychology

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

M.S.

Degree Level

Thesis

Keyword(s)

• vocational interests
• interest assessment
• language analysis
• social media
• Facebook

Abstract

There is a burgeoning interest in using natural language to study vocational interests. However, little to no research has used social media language to predict users’ interests. The present study investigated how accurately language used on Facebook predicts individuals’ self-ratings on eight basic interests: Agriculture, Engineering, Human Resource, Life Science, Management/Administration, Mechanics/Electronics, Media, and Social Science. This study employed closed-vocabulary (Linguistic Inquiry and Word Count 2015) and open-vocabulary approaches (Latent Dirichlet Allocation topic modeling) to analyze 3.2 million Facebook posts from 2,834 participants, who completed a 32-item basic interest measure (adapted from the Comprehensive Assessment of Basic Interests; CABIN; Su et al., 2019). Findings showed that the predictive accuracies of the linguistic models (mean r = .24; LDA topics) in assessing vocational interests are comparable to previous language research predicting personality traits (r = 0.27; Tay et al., 2020). Further, the present study revealed the unique language markers which characterize different basic interests. Together, the findings represent a novel advancement in vocational interest assessment. The results further suggest that automated language-based assessments can complement traditional self-report interest inventories to match people’s interests to their ideal occupations. Implications for research and applied settings were discussed.

Graduation Semester

2023-05

Type of Resource

Thesis

Handle URL

https://hdl.handle.net/2142/120547

Copyright and License Information

Copyright 2023 Yan Yi Lance Du

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