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dc.contributor.advisorDe Choudhury, Munmun
dc.contributor.authorKim, Sang-Chan
dc.date.accessioned2019-05-30T16:23:54Z
dc.date.available2019-05-30T16:23:54Z
dc.date.created2019-05
dc.date.submittedMay 2019
dc.identifier.urihttp://hdl.handle.net/1853/61387
dc.description.abstractPrior literature indicates members of sexual minorities face higher risk of mental health challenges than their counterparts. These individuals are often more predisposed to disorders such as drug addiction, anxiety, depression, and suicidal ideation. Online communities and social media provide a space for individuals to seek support, find peers, and disclose their thoughts and emotions. Using posts from the r/lgbt community on Reddit, we employ social media analysis and machine learning to examine and quantify the language of minority stress. Drawing from existing minority stress theory, we develop a codebook to identify minority stress in social media posts. Using a dataset annotated with the codebook, we train a machine learning classifier to predict posts with minority stress. Lastly, we analyze the linguistic cues of these newly machine-labelled posts, build a lexicon of minority stress markers, and relate our findings back to minority stress theory.
dc.format.mimetypeapplication/pdf
dc.publisherGeorgia Institute of Technology
dc.subjectMental health
dc.subjectSocial media
dc.subjectMinority stress
dc.subjectreddit
dc.subjectLGBTQ
dc.titleThe Language of Minority Stress Experiences of Sexual Minority Communities on Reddit
dc.typeUndergraduate Research Option Thesis
dc.description.degreeUndergraduate
dc.contributor.departmentComputer Science
thesis.degree.levelUndergraduate
dc.date.updated2019-05-30T16:23:54Z


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