{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/121316"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/121316","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Assessing interests using social media","abstract":"Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2025-08-01","abstract_html":"Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2025-08-01","abstract_has_math":false,"creators":["Hyland, William Elliott"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Psychology","degree_department":null,"school":null,"contributors":["Rounds, James","Briley, D.A.","Bosch, Nigel","Alexander, Leo","Hoff, Kevin","Tigunova, Anna"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2023,"date_issued":"2023-08","date_published":"2023-08","updated_at":"2026-07-22T22:24:57Z","subjects":["Vocational Interests","Social Media Text Mining","Natural Language Processing"],"languages":["en","eng"],"rights":["Copyright 2023 William Hyland"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2142/121316","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Rounds, James","Briley, D.A.","Bosch, Nigel","Alexander, Leo","Hoff, Kevin","Tigunova, Anna"]},{"key":"dc:creator","label":"Author","values":["Hyland, William Elliott"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2023-08","2023-06-22"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Psychology"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Vocational Interests","Social Media Text Mining","Natural Language Processing"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en","eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2023 William Hyland"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://hdl.handle.net/2142/121316"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2025-08-01","The student, William Hyland, accepted the attached license on 2023-06-21 at 13:32.","The student, William Hyland, submitted this Dissertation for approval on 2023-06-21 at 13:41.","This Dissertation was approved for publication on 2023-06-22 at 10:17.","DSpace SAF Submission Ingestion Package generated from Vireo submission #19446 on 2023-12-04 at 17:18:05","Interests are explicit in much of the information that is circulated on social media, including Facebook likes, Twitter follows, and discussions of interests on sites such as Reddit, Tumblr, and Pinterest. This wealth of data presents unique opportunities to expand applications of interest research and produce new insights into the structure of interests in novel contexts where people spend considerable time. Digital assessment of interests could also be valuable for career guidance by providing individuals with instant feedback about their interests and how they connect to different careers. In this article, we apply an unsupervised method of digital assessment to develop and validate a measure of interests using Reddit data. Specifically, we analyze thematically organized discussion forums called “subreddits”, using a combination of Natural Language Processing and clustering techniques to group subreddits based on similarity of language usage. Traits were identified at 2 levels of the interest hierarchy, leading to a 4-interest and a 13-interest measure. These interests predicted occupational choice with accuracy similar to self-report interest inventories and were stable over time. Overall, findings demonstrate that interests can be assessed digitally with good psychometric properties, providing a useful complement to self-report methodology. We discuss similarities and differences between digitally assessed interests and the RIASEC self-report model, as well as applications for research and practice."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Assessing interests using social media"]}]}],"canonical_facts":{"dc:contributor":["Rounds, James","Briley, D.A.","Bosch, Nigel","Alexander, Leo","Hoff, Kevin","Tigunova, Anna"],"dc:creator":["Hyland, William Elliott"],"dc:date":["2023-08","2023-06-22"],"dc:description":["Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2025-08-01","The student, William Hyland, accepted the attached license on 2023-06-21 at 13:32.","The student, William Hyland, submitted this Dissertation for approval on 2023-06-21 at 13:41.","This Dissertation was approved for publication on 2023-06-22 at 10:17.","DSpace SAF Submission Ingestion Package generated from Vireo submission #19446 on 2023-12-04 at 17:18:05","Interests are explicit in much of the information that is circulated on social media, including Facebook likes, Twitter follows, and discussions of interests on sites such as Reddit, Tumblr, and Pinterest. This wealth of data presents unique opportunities to expand applications of interest research and produce new insights into the structure of interests in novel contexts where people spend considerable time. Digital assessment of interests could also be valuable for career guidance by providing individuals with instant feedback about their interests and how they connect to different careers. In this article, we apply an unsupervised method of digital assessment to develop and validate a measure of interests using Reddit data. Specifically, we analyze thematically organized discussion forums called “subreddits”, using a combination of Natural Language Processing and clustering techniques to group subreddits based on similarity of language usage. Traits were identified at 2 levels of the interest hierarchy, leading to a 4-interest and a 13-interest measure. These interests predicted occupational choice with accuracy similar to self-report interest inventories and were stable over time. Overall, findings demonstrate that interests can be assessed digitally with good psychometric properties, providing a useful complement to self-report methodology. We discuss similarities and differences between digitally assessed interests and the RIASEC self-report model, as well as applications for research and practice."],"dc:format":["application/pdf"],"dc:identifier":["https://hdl.handle.net/2142/121316"],"dc:language":["en","eng"],"dc:rights":["Copyright 2023 William Hyland"],"dc:subject":["Vocational Interests","Social Media Text Mining","Natural Language Processing"],"dc:title":["Assessing interests using social media"],"dc:type":["text"],"thesis:degree_discipline":["Psychology"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Ph.D."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:24:57Z"}