Conference proceeding
Announcing Pregnancy Loss on Facebook: A Decision-Making Framework for Stigmatized Disclosures on Identified Social Network Sites
PROCEEDINGS OF THE 2018 CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS (CHI 2018), v 2018-, pp 1-14
01 Jan 2018
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Pregnancy loss is a common experience that is often not disclosed in spite of potential disclosure benefits such as social support. To understand how and why people disclose pregnancy loss online, we interviewed 27 women in the U.S. who are social media users and had recently experienced pregnancy loss. We developed a decision-making framework explaining pregnancy loss disclosures on identified social network sites (SNS) such as Facebook. We introduce network-level reciprocal disclosure, a theory of how disclosure reciprocity, usually applied to understand dyadic exchanges, can operate at the level of a social network to inform decision-making about stigmatized disclosures in identified SNSs. We find that 1) anonymous disclosures on other sites help facilitate disclosure on identified sites (e.g., Facebook), and 2) awareness campaigns enable sharing about pregnancy loss for many who would not disclose otherwise. Finally, we discuss conceptual and design implications. CAUTION: This paper includes quotes about pregnancy loss.
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Details
- Title
- Announcing Pregnancy Loss on Facebook: A Decision-Making Framework for Stigmatized Disclosures on Identified Social Network Sites
- Creators
- Nazanin Andalibi - Drexel UniversityAndrea Forte - Drexel UniversityACM
- Publication Details
- PROCEEDINGS OF THE 2018 CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS (CHI 2018), v 2018-, pp 1-14
- Conference
- 2018 CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS (CHI 2018)
- Publisher
- Assoc Computing Machinery
- Number of pages
- 14
- Grant note
- 1253302 / NSF; National Science Foundation (NSF)
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Information Science
- Web of Science ID
- WOS:000509673102003
- Scopus ID
- 2-s2.0-85046958642
- Other Identifier
- 991019168168504721
UN Sustainable Development Goals (SDGs)
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Computer Science, Cybernetics
- Computer Science, Information Systems