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Renita Washburn

dblp:344/9755 · DBLP profile ↗
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2ranked-venue papers
1as first author
2since 2021 · last 2026
0000-0002-7649-3417ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 1 · 1 since 2021Human-computer interaction and ubiquitous computing · 1 · 1 first-author · 1 since 2021Applied, interdisciplinary, general and emerging computing · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Network and information security
2 papers
Privacy and data protection · 56% Usable security · 44%
Human-computer interaction and pervasive computing
2 papers
Collaborative and social computing · 100%

Topics — the 7 heaviest of 7, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Collaborative and social computing › social computing
peer influence
1.012026
How Social Media Peer Comments Influence Privacy Decisions in Photo Sharing: Context and Individual Differences Cause Comments to Backfire · WWW 2026
Collaborative and social computing
social media
1.012026
How Social Media Peer Comments Influence Privacy Decisions in Photo Sharing: Context and Individual Differences Cause Comments to Backfire · WWW 2026
Usable security › usable privacy
privacy decision-making
1.012026
How Social Media Peer Comments Influence Privacy Decisions in Photo Sharing: Context and Individual Differences Cause Comments to Backfire · WWW 2026
Privacy and data protection
social network privacy
1.012026
How Social Media Peer Comments Influence Privacy Decisions in Photo Sharing: Context and Individual Differences Cause Comments to Backfire · WWW 2026
Privacy and data protection › privacy management › multi-user privacy
interdependent privacy
0.712023
Bottom-up psychosocial interventions for interdependent privacy: Effectiveness based on individual and content differences · CHI 2023
Usable security › usable privacy
privacy nudges
0.312026
How Social Media Peer Comments Influence Privacy Decisions in Photo Sharing: Context and Individual Differences Cause Comments to Backfire · WWW 2026
Collaborative and social computing › social media › media sharing
social media sharing
0.212023
Bottom-up psychosocial interventions for interdependent privacy: Effectiveness based on individual and content differences · CHI 2023

Methods — techniques the papers use, named apart from their topics

experimental study · 2.0narrative transportation theory · 1.3educational video · 1.3
YearPublicationVenuePosition
2026 How Social Media Peer Comments Influence Privacy Decisions in Photo Sharing: Context and Individual Differences Cause Comments to Backfire
abstract
Although extensive research has examined social media nudges to influence privacy, comparably less work investigates mechanisms of peer-to-peer influence, or the ways in which peer groups can amplify or dampen privacy considerations. This study takes an experimental approach to examining how people are influenced to share potentially sensitive photos of others without consent---a common practice on social media---by comparing the effects of encouraging, discouraging, or mixed feedback social media comments. The results show that discouraging peer comments reduce the sharing of others' photos when content portrayed targets negatively. However, peer influence backfired among users with a history of online misconduct, with both encouraging and discouraging comments leading to more photo sharing. Moreover, a mix of comments that both discouraged and encouraged sharing led to the highest levels of sharing. Linking to prior work, this research establishes a broader understanding of when privacy nudges are likely to backfire on social media: for users with past online misconduct and when information goes against social norms. The findings advance understanding of how peer-to-peer dynamics shape online information flows and highlight the complex effects of Web-based social feedback on privacy decisions. These insights provide actionable design recommendations for platforms to foster responsible, privacy-conscious sharing norms.
Tangila Islam Tanni, Renita Washburn, Yan Solihin, Mary Jean Amon
WWW2
2023 Bottom-up psychosocial interventions for interdependent privacy: Effectiveness based on individual and content differences
abstract
Although a great deal of research has examined interventions to help users protect their own information online, less work has examined methods for reducing interdependent privacy (IDP) violations on social media (i.e., sharing of other people's information). This study tested the effectiveness of concept-based (i.e., general information), fact-based (i.e., statistics), and narrative-based (i.e., stories) educational videos in altering IDP-relevant attitudes and multimedia sharing behaviors. Our study revealed concept and fact videos reduced sharing of social media content that portrayed people negatively. The narrative intervention backfired and increased sharing among participants who did not believe IDP violations to be especially serious; however, the narrative intervention decreased sharing for participants who rated IDP violations as more serious. Notably, our study found participants preferred narrative-based interventions with real world examples, despite other strategies more effectively reducing sharing. Implications for narrative transportation theory and advancing bottom-up (i.e., user-centered) psychosocial interventions are discussed.
Renita Washburn, Tangila Islam Tanni, Yan Solihin, Apu Kapadia, Mary Jean Amon
CHI1