“Date Assist” Plug-in for Self-Affirmation in Online Dating Apps – Fall 2019 Class Project

Yes I am STILL taking courses towards my doctorate in human-computer interaction (HCI) here at Carnegie Mellon! It’s annoying that my department does not count my 2017 master’s degree in HCI from Indiana University as an acceptable credential. The flip side, though, is that I have experience with group projects, so these feel like a breeze – plus, I get to meet and work directly with PhD students outside my area and with our amazing master’s degree students!

The following is a blog post that we created for our final project in Persuasive Design in HCI, taught by Geoff Kaufman. My teammates are Aaron Bishop, Brandon Fiksel, Samantha Reig, Bidisha Roy, and Molly Schaefer.

A summary image of our "Date Assist" plugin. The QR code links to the interactive Figma prototype.
A summary image of our “Date Assist” plugin. The QR code links to the interactive Figma prototype.

Having anxiety about meeting the right romantic partner in today’s online dating apps? You’re not alone. A Google search of the phrase “online dating is stressful” yielded close to 10 million results! Moreover, our research shows that young adults in a college setting struggle with three issues with dating: finding a mutually agreeable time for the first date, bolstering their mental state before the date, and coming up with conversation starters during the date. 

Enter “Date Assist.” Our plugin for online dating apps uses a touch-screen calendar interface to help you and that special someone easily find a meeting time that works for both. Once the date is scheduled, we help you remember what’s most important to you with a simple quiz about your values. We also help you to build a personalized, meaningful playlist to get you feeling great before your date — and, if you so choose, to share one of your favorite songs to break the ice and ease conversation. Finally, we push out reminders to you that help you to stay positive and remember: you’re a catch!

The psychological mechanism that our “Date Assist” plugin uses is called self-affirmation. In this process (Steele, 1988), a person reflects on valued aspects of the self, allowing those positive aspects to counter the negative effects of seeing other aspects of the self as negative. Such a reflection in one domain can reduce threats in unrelated domains by shifting from a narrow focus on the immediate threat to an expanded perspective of one’s self-worth. 

Our “Date Assist” plugin was developed in Sept.-Dec. 2019 using an iterative, user-centered research and design process:

  • We identified the need to test a self-affirmation in a context that is a threat to an individual’s positive self-concept. 
  • We found a novel research domain for this threat — first dates — that is relevant to the research population that we have immediate access to, young adults. 
  • We used interviews to define this population’s need for help in finding a mutually agreeable time for the first date, in bolstering their mental state before the date, and in coming up with conversation starters during the date. 
  • We created sketches and gathered user feedback. We then consolidated these into a high-fidelity prototype with the Figma collaborative design tool. 
  • To test the effectiveness of “Date Assist,” we propose a large-scale 4×2 experimental study.
Our team met weekly to discuss our ideas, interpret interview data and share low-fidelity sketches. Three images: One of team members Bidisha Roy and Aaron Bishop with others reflected in the lab mirror; a sketch of possible app screens; a menu design in progress.
Our team met weekly to discuss our ideas, interpret interview data and share low-fidelity sketches.

Our process gives us confidence that “Date Assist” can make two contributions to the fields of psychology and human-computer interaction. First, our research extends the existing literature on self-affirmation to the context of online dating. Second, our research provides a novel operationalization of self-affirmation with the creation of the “Date Assist” plugin. 

Most importantly, our work may significantly improve the experiences of those who seek romantic connections via dating apps. We hope that “Date Assist” helps to ease the stressful process of finding love and companionship for brave first-daters everywhere!

‘Normal and Easy: Account Sharing Practices in the Workplace’ – new paper for CSCW 2019

Drumroll … I now am a co-author on an archival publication in the lead venue for social computing!

Our paper, “Normal and Easy : Account Sharing Practices in the Workplace,” is being published this month in Proceedings of the ACM on Human-Computer Interaction, Vol. 3, CSCW. This is part of the Conference on Computer-Supported Collaborative Work and Social Computing – which is what most of my life’s work in information technology and media has revolved around.

However, as much as I might want to be present, I am also practicing good self-care this fall – and part of that is limiting my travel so that I don’t run myself ragged trying to be different places plus keep up with my research and personal life! So, my advisor Laura Dabbish is presenting this research on Wed., Nov. 13, in Austin, Tx., USA. 

For this research paper, we conducted two online surveys. In Study 1, we asked people a series of open-ended questions to elicit their sharing practices and start to zero in on what are their key pain points, while in Study 2, we collected a series of closed-ended items to gather specific details about how and why people shared digital accounts with colleagues and what are their specific struggles with those activities. We have posted these survey protocols on our website at https://socialcybersecurity.org/files/WorkplaceSharing_OpenEndedShort_Qualtrics.pdf and  https://socialcybersecurity.org/files/WorkplaceSharing_ClosedEndedLong_Qualtrics.pdf.

Our results demonstrate that account sharing in the modern workplace serves as a norm rather than a simple workaround (“normal and easy”), with the key motivations being to centralize collaborative activity and to reduce the work needed to manage the boundaries around these collaborative activities.  

However, people still struggle with a number of issues: lack of activity accountability and awareness, conflicts over simultaneous access, difficulties controlling access, and collaborative password use. (Hands up, anyone who has a sticky note taped in their work space to share passwords for key accounts?)

Our work provides insights into the current difficulties people face in workplace collaboration with online account sharing, as a result of inappropriate designs that still assume a single-user model for accounts. We highlight opportunities for CSCW and HCI researchers and designers to better support sharing by multiple people in a more usable and secure way.

This is a BIG paper, so I’ll stop restating the abstract and send you to the link on our website: 

  • Yunpeng Song, Cori Faklaris, Zhongmin Cai, Jason I. Hong, and Laura Dabbish. 2019. Normal and Easy: Account Sharing Practices in the Workplace. In Proceedings of the ACM: Human-Computer Interaction, Vol. 3, Issue CSCW, November 2019. ACM, New York, NY, USA. Available at: https://socialcybersecurity.org/files/CSCW2019_NormalAndEasy.pdf 

‘A Self-Report Measure of End-User Security Attitudes (SA-6)’: New Paper

This month is a personal milestone – my FIRST first-author usability research paper is being published in the Proceedings of the Fifteenth USENIX Symposium on Usable Privacy and Security (SOUPS 2019).

I will present on Monday, Aug. 12, in Santa Clara, Calif., USA, about my creation of the SA-6 psychometric scale. This six-item scale is a lightweight tool for quantifying and comparing people’s attitudes about using expert-recommended security measures. (Examples of these include enabling two-factor authentication, going the extra mile to create longer passwords that are unique to each account, and taking care to update software and mobile apps as soon as these patches are available.)

The scale itself is reproduced below (download the PDF at https://socialcybersecurity.org/sa6.html ):

  • Generally, I diligently follow a routine about security practices.
  • I always pay attention to experts’ advice about the steps I need to take to keep my online data and accounts safe. 
  • I am extremely knowledgeable about all the steps needed to keep my online data and accounts safe. 
  • I am extremely motivated to take all the steps needed to keep my online data and accounts safe.
  • I often am interested in articles about security threats. 
  • I seek out opportunities to learn about security measures that are relevant to me.

Response set: 1=Strongly disagree, 2=Somewhat disagree, 3=Neither disagree nor agree, 4=Somewhat agree, 5=Strongly disagree. Score by taking the average of all six responses.

If you are a researcher who can make use of this work, please download our full research paper and cite us as follows: Cori Faklaris, Laura Dabbish and Jason I. Hong. 2019. A Self-Report Measure of End-User Security Attitudes (SA-6). In Proceedings of the Fifteenth Symposium on Usable Privacy and Security (SOUPS 2019). USENIX Association, Berkeley, CA, USA. DOI: 10.13140/RG.2.2.29840.05125/3.

Many thanks to everyone who helped me develop and bring this project in for a landing, particularly Laura and Jason, Geoff Kaufman, Maria Tomprou, Sauvik Das, Sam Reig, Vikram Kamath Cannanure, Michael Eagle, and the members of the Connected Experience and CHIMPS labs at Carnegie Mellon University’s Human-Computer Interaction Institute. Funding for our Social Cybersecurity project is provided by the U.S. National Science Foundation under grant no. CNS-1704087.