Predicting Responses to Psychological Questionnaires from Participants’ Social Media Posts and Question Text Embeddings

Huy Vu, Suhaib Abdurahman, Sudeep Bhatia, Lyle Ungar


Abstract
Psychologists routinely assess people’s emotions and traits, such as their personality, by collecting their responses to survey questionnaires. Such assessments can be costly in terms of both time and money, and often lack generalizability, as existing data cannot be used to predict responses for new survey questions or participants. In this study, we propose a method for predicting a participant’s questionnaire response using their social media texts and the text of the survey question they are asked. Specifically, we use Natural Language Processing (NLP) tools such as BERT embeddings to represent both participants (via the text they write) and survey questions as embeddings vectors, allowing us to predict responses for out-of-sample participants and questions. Our novel approach can be used by researchers to integrate new participants or new questions into psychological studies without the constraint of costly data collection, facilitating novel practical applications and furthering the development of psychological theory. Finally, as a side contribution, the success of our model also suggests a new approach to study survey questions using NLP tools such as text embeddings rather than response data used in traditional methods.
Anthology ID:
2020.findings-emnlp.137
Volume:
Findings of the Association for Computational Linguistics: EMNLP 2020
Month:
November
Year:
2020
Address:
Online
Venue:
Findings
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
1512–1524
Language:
URL:
https://aclanthology.org/2020.findings-emnlp.137
DOI:
10.18653/v1/2020.findings-emnlp.137
Bibkey:
Cite (ACL):
Huy Vu, Suhaib Abdurahman, Sudeep Bhatia, and Lyle Ungar. 2020. Predicting Responses to Psychological Questionnaires from Participants’ Social Media Posts and Question Text Embeddings. In Findings of the Association for Computational Linguistics: EMNLP 2020, pages 1512–1524, Online. Association for Computational Linguistics.
Cite (Informal):
Predicting Responses to Psychological Questionnaires from Participants’ Social Media Posts and Question Text Embeddings (Vu et al., Findings 2020)
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PDF:
https://aclanthology.org/2020.findings-emnlp.137.pdf
Optional supplementary material:
 2020.findings-emnlp.137.OptionalSupplementaryMaterial.zip