Conference proceeding
Sensitive Self-disclosures, Responses, and Social Support on Instagram: The Case of #Depression
CSCW'17: PROCEEDINGS OF THE 2017 ACM CONFERENCE ON COMPUTER SUPPORTED COOPERATIVE WORK AND SOCIAL COMPUTING, pp 1485-1500
01 Jan 2017
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
People can benefit from disclosing negative emotions or stigmatized facets of their identities, and psychologists have noted that imagery can be an effective medium for expressing difficult emotions. Social network sites like Instagram offer unprecedented opportunity for image-based sharing. In this paper, we investigate sensitive self-disclosures on Instagram and the responses they attract. We use visual and textual qualitative content analysis and statistical methods to analyze self-disclosures, associated comments, and relationships between them. We find that people use Instagram to engage in social exchange and storytelling about difficult experiences. We find considerable evidence of social support, a sense of community, and little aggression or support for harmful or pro-disease behaviors. Finally, we report on factors that influence engagement and the type of comments these disclosures attract. Personal narratives, food and beverage, references to illness, and self-appearance concerns are more likely to attract positive social support. Posts seeking support attract significantly more comments. CAUTION: This paper includes some detailed examples of content about eating disorders and self-injury illnesses.
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Details
- Title
- Sensitive Self-disclosures, Responses, and Social Support on Instagram: The Case of #Depression
- Creators
- Nazanin Andalibi - Drexel UniversityPinar Ozturk - Stevens Institute of TechnologyAndrea Forte - Drexel UniversityAssoc Comp Machinery
- Publication Details
- CSCW'17: PROCEEDINGS OF THE 2017 ACM CONFERENCE ON COMPUTER SUPPORTED COOPERATIVE WORK AND SOCIAL COMPUTING, pp 1485-1500
- Conference
- CSCW'17: 2017 ACM CONFERENCE ON COMPUTER SUPPORTED COOPERATIVE WORK AND SOCIAL COMPUTING
- Publisher
- Assoc Computing Machinery
- Number of pages
- 16
- Grant note
- 1253302 / National Science Foundation; National Science Foundation (NSF)
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Information Science
- Web of Science ID
- WOS:000455087800110
- Scopus ID
- 2-s2.0-85014801097
- Other Identifier
- 991019168551604721
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Computer Science, Interdisciplinary Applications
- Social Sciences, Interdisciplinary