'What is in a Name?’: Using Natural Language Processing Techniques to Examine Attitudes About Solitude

This research characterized how adolescents and young adults describe someone who ‘enjoys solitude’ – and how these descriptions relate to their experiences of solitude. Participants’ descriptions of someone who enjoys solitude were coded using content analysis and lexicon-based sentiment analysis (from natural language processing). The content analysis found five themes: Introvert, Ambivert, Neutral, Positive, and Negative, representing different attitudes participants held towards one who enjoys solitude. The themes were differentially associated with attitudes towards solitude, and time alone alongside valence, arousal, and dominance scores from the sentiment analysis. Expectedly, compared to adolescents, emerging adults displayed more positive views of someone who enjoys solitude, evidenced by both methods. This research improves understanding of the utilities of language as indices of internal processes and provides insight into a novel method for psychological research. Most notably, results empirically support developmental differences in the perception of solitude between adolescents and emerging adults.

Name thesis:degree_name

Master of Arts (M.A.)

Level thesis:degree_level

Master's

Discipline thesis:degree_discipline

Psychology

Grantor dc:publisher

Carleton University

Year dc:date.issued

2024

Author dc:creator

• Cheng, Tiffany

Statement dc:rights

• Copyright © 2024 the author(s). Theses may be used for non-commercial research, educational, or related academic purposes only. Such uses include personal study, distribution to students, research and scholarship. Theses may only be shared by linking to the Carleton University Institutional Repository and no part may be copied without proper attribution to the author; no part may be used for commercial purposes directly or indirectly via a for-profit platform; no adaptation or derivative works are permitted without consent from the copyright owner.

Language dc:language.iso

en

DOI

10.22215/etd/2024-16219

OAI identifier oai:identifier

oai:carleton.scholaris.ca:20.500.14718/43402