Beyond Swipes and Scores: Investigating Practices, Challenges and User-Centered Values in Online Dating Algorithms
Article No.: 486, Pages 1 - 30
Abstract
The reliability of online dating algorithms has sparked considerable debate, particularly regarding skepticism about their excessive emphasis on evaluating and getting evaluated, which often overshadows the quest for authentic romantic connections. To understand the multifaceted influence of dating algorithms on end-users and explore avenues for algorithmic features considering the dynamics of human relationships, we conducted a mixed-methods study comprising in-depth interviews (N = 22) and a metaphoric co-design workshop (N = 12) with active users of online dating platforms. Interviews revealed that users perceive and respond to algorithmic evaluations with varied perceptions and behaviors, often expressing concerns about the emotional burden of constant self-presentation and the pursuit of quantitative assessments over genuine connections. In the design workshop, users envisioned desired algorithmic features to overcome investigated challenges, such as prioritizing personal values, tailored matchmaking, and support for personal growth in relationships. This research contributes to unraveling the complex dynamics of human-algorithm interaction in the context of online dating. By aligning algorithmic functions more closely with user desires and relationship goals, this study paves the way for more meaningful and authentic connections in the digital dating landscape.
References
[1]
Aaron C Ahuvia and Mara B Adelman. 1992. Formal intermediaries in the marriage market: A typology and review. Journal of Marriage and the Family (1992), 452--463.
[2]
Brian Alexander. 2014. The chemistry between us: Love, sex, and the science of attraction. Penguin.
[3]
Courtney Blackwell, Jeremy Birnholtz, and Charles Abbott. 2015. Seeing and being seen: Co-situation and impression formation using Grindr, a location-aware gay dating app. New media & society 17, 7 (2015), 1117--1136.
[4]
Kallista Bonawitz, Peter Kairouz, Brendan McMahan, and Daniel Ramage. 2021. Federated learning and privacy: Building privacy-preserving systems for machine learning and data science on decentralized data. Queue 19, 5 (2021), 87--114.
[5]
Aaron S Breslow, Riddhi Sandil, Melanie E Brewster, Mike C Parent, Anthea Chan, Aysegul Yucel, Nicholas Bensmiller, and Elizabeth Glaeser. 2020. Adonis on the apps: Online objectification, self-esteem, and sexual minority men. Psychology of Men & Masculinities 21, 1 (2020), 25.
[6]
Katherine Bryant and Pavica Sheldon. 2017. Cyber dating in the age of mobile apps: Understanding motives, attitudes, and characteristics of users. American Communication Journal 19, 2 (2017), 1--15.
[7]
Taina Bucher and Anne Helmond. 2017. The affordances of social media platforms. (2017).
[8]
Judee K Burgoon, Lesa A Stern, and Leesa Dillman. 1995. Interpersonal adaptation: Dyadic interaction patterns. Cambridge University Press.
[9]
John T Cacioppo, Stephanie Cacioppo, Gian C Gonzaga, Elizabeth L Ogburn, and Tyler J VanderWeele. 2013. Marital satisfaction and break-ups differ across on-line and off-line meeting venues. Proceedings of the National Academy of Sciences 110, 25 (2013), 10135--10140.
[10]
Austin Carr. 2016. I found out my secret internal Tinder rating and now I wish I hadnt. Fast Company 1, 11 (2016), 2016.
[11]
Yoonseo Choi, Eun Jeong Kang, Min Kyung Lee, and Juho Kim. 2023. Creator-friendly Algorithms: Behaviors, Challenges, and Design Opportunities in Algorithmic Platforms. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems. 1--22.
[12]
ChosunBiz. [n. d.]. 7500? ", .
[13]
Jennifer Cobbe, Michael Veale, and Jatinder Singh. 2023. Understanding accountability in algorithmic supply chains. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency. 1186--1197.
[14]
Fernando Delgado, Solon Barocas, and Karen Levy. 2022. An uncommon task: Participatory design in legal AI. Proceedings of the ACM on Human-Computer Interaction 6, CSCW1 (2022), 1--23.
[15]
Fei Deng, Jibing Huang, Xiaoling Yuan, Chao Cheng, and Lanjing Zhang. 2021. Performance and efficiency of machine learning algorithms for analyzing rectangular biomedical data. Laboratory Investigation 101, 4 (2021), 430--441.
[16]
Michael A DeVito, Jeremy Birnholtz, and Jeffery T Hancock. 2017. Platforms, people, and perception: Using affordances to understand self-presentation on social media. In Proceedings of the 2017 ACM conference on computer supported cooperative work and social computing. 740--754.
[17]
Michael A DeVito, Darren Gergle, and Jeremy Birnholtz. 2017. " Algorithms ruin everything" # RIPTwitter, Folk Theories, and Resistance to Algorithmic Change in Social Media. In Proceedings of the 2017 CHI conference on human factors in computing systems. 3163--3174.
[18]
Karen K Dion and Kenneth L Dion. 1996. Cultural perspectives on romantic love. Personal relationships 3, 1 (1996), 5--17.
[19]
Jonathan Dodge, Q Vera Liao, Yunfeng Zhang, Rachel KE Bellamy, and Casey Dugan. 2019. Explaining models: an empirical study of how explanations impact fairness judgment. In Proceedings of the 24th international conference on intelligent user interfaces. 275--285.
[20]
Neslihan Dogan and Zuhal Tanrikulu. 2013. A comparative analysis of classification algorithms in data mining for accuracy, speed and robustness. Information Technology and Management 14 (2013), 105--124.
[21]
Leyla Dogruel, Dominique Facciorusso, and Birgit Stark. 2022. Im still the master of the machine.Internet users awareness of algorithmic decision-making and their perception of its effect on their autonomy. Information, Communication & Society 25, 9 (2022), 1311--1332.
[22]
Susan Dumais, Thorsten Joachims, Krishna Bharat, and AndreasWeigend. 2003. SIGIR 2003 workshop report: implicit measures of user interests and preferences. In ACM SIGIR Forum, Vol. 37. ACM New York, NY, USA, 50--54.
[23]
Johnathan Dunlop. 2018. App-ily ever after-self-presentation and perception of others on the dating app Tinder. (2018).
[24]
Emory James Edwards and Tom Boellstorff. 2021. Migration, non-use, and the Tumblrpocalypse: Towards a unified theory of digital exodus. Media, Culture & Society 43, 3 (2021), 582--592.
[25]
Nicole Ellison, Rebecca Heino, and Jennifer Gibbs. 2006. Managing impressions online: Self-presentation processes in the online dating environment. Journal of computer-mediated communication 11, 2 (2006), 415--441.
[26]
Nicole B Ellison, Jeffrey T Hancock, and Catalina L Toma. 2012. Profile as promise: A framework for conceptualizing veracity in online dating self-presentations. New media & society 14, 1 (2012), 45--62.
[27]
Ahmed Elsaid Abdelhalim Eliwa Elshazly. 2018. Business of love: exploring motivations to use and sentiments towards online dating using big data analytics.
[28]
Emojipedia. 2023. Apple Emoji List - Emojis for iPhone, iPad and macOS [Updated: 2023].
[29]
Motahhare Eslami, Karrie Karahalios, Christian Sandvig, Kristen Vaccaro, Aimee Rickman, Kevin Hamilton, and Alex Kirlik. 2016. First I" like" it, then I hide it: Folk Theories of Social Feeds. In Proceedings of the 2016 cHI conference on human factors in computing systems. 2371--2382.
[30]
Catherine S Fichten, Vicki Tagalakis, Darlene Judd, John Wright, and Rhonda Amsel. 1992. Verbal and nonverbal communication cues in daily conversations and dating. The Journal of Social Psychology 132, 6 (1992), 751--769.
[31]
Eli J Finkel, Paul W Eastwick, Benjamin R Karney, Harry T Reis, and Susan Sprecher. 2012. Online dating: A critical analysis from the perspective of psychological science. Psychological Science in the Public interest 13, 1 (2012), 3--66.
[32]
Forbes. [n. d.]. 9 Best Dating Apps Of 2024.
[33]
Ajit G. Pillai, A Baki Kocaballi, Tuck Wah Leong, Rafael A. Calvo, Nassim Parvin, Katie Shilton, Jenny Waycott, Casey Fiesler, John C. Havens, and Naseem Ahmadpour. 2021. Co-designing resources for ethics education in HCI. In Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems. 1--5.
[34]
Simson Garfinkel, Jeanna Matthews, Stuart S Shapiro, and Jonathan M Smith. 2017. Toward algorithmic transparency and accountability., 5--5 pages.
[35]
Susan A Gelman and Cristine H Legare. 2011. Concepts and folk theories. Annual review of anthropology 40 (2011), 379.
[36]
Jeffrey A Hall, Namkee Park, Hayeon Song, and Michael J Cody. 2010. Strategic misrepresentation in online dating: The effects of gender, self-monitoring, and personality traits. Journal of Social and Personal Relationships 27, 1 (2010), 117--135.
[37]
Juho Hamari, Nicolai Hanner, and Jonna Koivisto. 2017. Service quality explains why people use freemium services but not if they go premium: An empirical study in free-to-play games. International Journal of Information Management 37, 1 (2017), 1449--1459.
[38]
Juho Hamari and Vili Lehdonvirta. 2010. Game design as marketing: How game mechanics create demand for virtual goods. International Journal of Business Science & Applied Management 5, 1 (2010), 14--29.
[39]
Jeffrey T Hancock and Catalina L Toma. 2009. Putting your best face forward: The accuracy of online dating photographs. Journal of Communication 59, 2 (2009), 367--386.
[40]
Meredith G Harrison, Richard D McAnulty, and Amy Canevello. 2022. College Students? Motives for In-Person Meetings with Dating Application Matches. Cyberpsychology, Behavior, and Social Networking 25, 2 (2022), 130--134.
[41]
Heiner Heiland. 2023. The social construction of algorithms: A reassessment of algorithmic management in food delivery gig work. New Technology, Work and Employment (2023).
[42]
Rebecca D Heino, Nicole B Ellison, and Jennifer L Gibbs. 2010. Relationshopping: Investigating the market metaphor in online dating. Journal of Social and Personal relationships 27, 4 (2010), 427--447.
[43]
Günter J Hitsch, Ali Hortaçsu, and Dan Ariely. 2005. What makes you click: An empirical analysis of online dating. In 2005 Meeting Papers, Vol. 207. Society for Economic Dynamics Minneapolis, MN, 1--51.
[44]
Mitchell Hobbs, Stephen Owen, and Livia Gerber. 2017. Liquid love? Dating apps, sex, relationships and the digital transformation of intimacy. Journal of Sociology 53, 2 (2017), 271--284.
[45]
Nicol Holtzhausen, Keersten Fitzgerald, Ishaan Thakur, Jack Ashley, Margaret Rolfe, and Sabrina Winona Pit. 2020. Swipe-based dating applications use and its association with mental health outcomes: a cross-sectional study. BMC psychology 8, 1 (2020), 1--12.
[46]
Antoine Houssard, Federico Pilati, Maria Tartari, Pier Luigi Sacco, and Riccardo Gallotti. 2023. Monetization in online streaming platforms: an exploration of inequalities in Twitch. tv. Scientific Reports 13, 1 (2023), 1103.
[47]
Chin-Lung Hsu and Judy Chuan-Chuan Lin. 2016. Effect of perceived value and social influences on mobile app stickiness and in-app purchase intention. Technological forecasting and social change 108 (2016), 42--53.
[48]
Sabrina Angela Huang, Jeffrey Hancock, and Stephanie Tom Tong. 2022. Folk theories of online dating: Exploring people's beliefs about the online dating process and online dating algorithms. Social Media Society 8, 2 (2022), 20563051221089561.
[49]
Jevan A Hutson, Jessie G Taft, Solon Barocas, and Karen Levy. 2018. Debiasing desire: Addressing bias & discrimination on intimate platforms. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (2018), 1--18.
[50]
Daniela Jaramillo-Dent, Amanda Alencar, and Yan Asadchy. 2022. Precarious Migrants in a Sharing Economy|# Migrantes on TikTok: Exploring Platformed Belongings. International Journal of Communication 16 (2022), 25.
[51]
Shagun Jhaver, Yoni Karpfen, and Judd Antin. 2018. Algorithmic anxiety and coping strategies of Airbnb hosts. In Proceedings of the 2018 CHI conference on human factors in computing systems. 1--12.
[52]
Nadia Karizat, Dan Delmonaco, Motahhare Eslami, and Nazanin Andalibi. 2021. Algorithmic folk theories and identity: How TikTok users co-produce Knowledge of identity and engage in algorithmic resistance. Proceedings of the ACM on Human-Computer Interaction 5, CSCW2 (2021), 1--44.
[53]
Melissa G Keith, Peter D Harms, and Alexander C Long. 2020. Worker health and well-being in the gig economy: A proposed framework and research agenda. Entrepreneurial and small business stressors, experienced stress, and well-being 18 (2020), 1--33.
[54]
Willett Kempton. 1986. Two theories of home heat control. Cognitive science 10, 1 (1986), 75--90.
[55]
Zoltán Kövecses. 2005. Metaphor in culture: Universality and variation. Cambridge University Press.
[56]
Mikhail Kuznetsov, Evgenia Novikova, Igor Kotenko, and Elena Doynikova. 2022. Privacy policies of IoT devices: collection and analysis. Sensors 22, 5 (2022), 1838.
[57]
George Lakoff and Mark Johnson. 2008. Metaphors we live by. University of Chicago press.
[58]
Min Kyung Lee, Daniel Kusbit, Anson Kahng, Ji Tae Kim, Xinran Yuan, Allissa Chan, Daniel See, Ritesh Noothigattu, Siheon Lee, Alexandros Psomas, et al. 2019. WeBuildAI: Participatory framework for algorithmic governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (2019), 1--35.
[59]
Jon Levy, Devin Markell, and Moran Cerf. 2019. Polar similars: Using massive mobile dating data to predict synchronization and similarity in dating preferences. Frontiers in Psychology (2019), 2010.
[60]
Frederike Lichtenstein. 2017. Is Vidme the NewTube Why video creators are changing sides and how they feel about it. Masters of Media (2017).
[61]
Dan Lockton, Devika Singh, Saloni Sabnis, Michelle Chou, Sarah Foley, and Alejandro Pantoja. 2019. New metaphors: A workshop method for generating ideas and reframing problems in design and beyond. In Proceedings of the 2019 on Creativity and Cognition. 319--332.
[62]
Nick Logler, Daisy Yoo, and Batya Friedman. 2018. Metaphor cards: A how-to-guide for making and using a generative metaphorical design toolkit. In Proceedings of the 2018 designing interactive systems conference. 1373--1386.
[63]
David Ludden. 2021. How Couples Can Improve Their Communication.
[64]
Kai Lukoff, Ulrik Lyngs, Himanshu Zade, J Vera Liao, James Choi, Kaiyue Fan, Sean A Munson, and Alexis Hiniker. 2021. How the design of youtube influences user sense of agency. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems. 1--17.
[65]
Shanhong Luo and David Watson. 2021. 17 Accuracy and Bias of Trait Judgments in Romantic Relationships. The Oxford Handbook of Accurate Personality Judgment (2021), 261.
[66]
Zilin Ma and Krzysztof Z Gajos. 2022. Not just a preference: Reducing biased decision-making on dating websites. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems. 1--14.
[67]
Christian Maier, Sven Laumer, Andreas Eckhardt, and Tim Weitzel. 2015. Giving too much social support: social overload on social networking sites. European Journal of Information Systems 24, 5 (2015), 447--464.
[68]
April S Masarik, Rand D Conger, Monica J Martin, M Brent Donnellan, Katherine E Masyn, and Frederick O Lorenz. 2013. Romantic relationships in early adulthood: Influences of family, personality, and relationship cognitions. Personal Relationships 20, 2 (2013), 356--373.
[69]
Bennie Mols. 2017. In black box algorithms we trust (or do we). Commun. ACM (2017).
[70]
Maddy Mussen. [n. d.]. This is how the Nobel prize winning Hinge algorithm actually works.
[71]
Karim Nader and Min Kyung Lee. 2022. Folk Theories and User Strategies on Dating Apps. In International Conference on Information. Springer, 445--458.
[72]
Gregory Narr. 2021. The uncanny swipe drive: The return of a racist mode of algorithmic thought on dating apps. Studies in Gender and Sexuality 22, 3 (2021), 219--236.
[73]
Cecilia Panigutti, Ronan Hamon, Isabelle Hupont, David Fernandez Llorca, Delia Fano Yela, Henrik Junklewitz, Salvatore Scalzo, Gabriele Mazzini, Ignacio Sanchez, Josep Soler Garrido, et al. 2023. The role of explainable AI in the context of the AI Act. In Proceedings of the 2023 ACM conference on fairness, accountability, and transparency. 1139--1150.
[74]
Luiz Pizzato, Thomas Chung, Tomasz Rej, Irena Koprinska, Kalina Yacef, and Judy Kay. 2010. Learning user preferences in online dating. In Proceedings of the Preference Learning (PL-10) Tutorial and Workshop, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD). Citeseer.
[75]
Mashita Phitaloka Fandia Purwaningtyas, Syakira N Maharani, and Dian Arymami. 2020. The Commoditized self: interpersonal communication in tinder online dating apps. International Journal of Indonesian Popular Cultura and Communication 1, 2 (2020), 84--95.
[76]
Marissa Radensky, Julie Anne Séguin, Jang Soo Lim, Kristen Olson, and Robert Geiger. 2023. I Think You Might Like This: Exploring Effects of Confidence Signal Patterns on Trust in and Reliance on Conversational Recommender Systems. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency. 792--804.
[77]
Emilee Rader, Kelley Cotter, and Janghee Cho. 2018. Explanations as mechanisms for supporting algorithmic transparency. In Proceedings of the 2018 CHI conference on human factors in computing systems. 1--13.
[78]
Emilee Rader and Rebecca Gray. 2015. Understanding user beliefs about algorithmic curation in the Facebook news feed. In Proceedings of the 33rd annual ACM conference on human factors in computing systems. 173--182.
[79]
Giulia Ranzini and Christoph Lutz. 2017. Love at first swipe Explaining Tinder self-presentation and motives. Mobile Media & Communication 5, 1 (2017), 80--101.
[80]
Paul Resnick and Hal R Varian. 1997. Recommender systems. Commun. ACM 40, 3 (1997), 56--58.
[81]
Larry D Rosen, Nancy A Cheever, Cheyenne Cummings, and Julie Felt. 2008. The impact of emotionality and self-disclosure on online dating versus traditional dating. Computers in Human Behavior 24, 5 (2008), 2124--2157.
[82]
Michael J Rosenfeld, Reuben J Thomas, and Sonia Hausen. 2019. Disintermediating your friends: How online dating in the United States displaces other ways of meeting. Proceedings of the National Academy of Sciences 116, 36 (2019), 17753--17758.
[83]
Christian Rudder. 2014. Dataclysm: Who we are (when we think no one's looking). Random House Canada.
[84]
Dan Saffer. 2005. The role of metaphor in interaction design. Information Architecture Summit 6 (2005).
[85]
Kourosh Sayehmiri, Karez Ibrahim Kareem, Kamel Abdi, Sahar Dalvand, and Reza Ghanei Gheshlagh. 2020. The relationship between personality traits and marital satisfaction: a systematic review and meta-analysis. BMC psychology 8, 1 (2020), 1--8.
[86]
Liesel L Sharabi. 2022. Finding love on a first data: Matching algorithms in online dating. Harvard Data Science Review 4, 1 (2022), 1--11.
[87]
Liesel L Sharabi. 2023. The enduring effect of internet dating: Meeting online and the road to marriage. Communication Research (2023), 00936502221127498.
[88]
Donghee Shin. 2020. Howdo users interact with algorithm recommender systems? The interaction of users, algorithms, and performance. Computers in human behavior 109 (2020), 106344.
[89]
Donghee Shin, Azmat Rasul, and Anestis Fotiadis. 2022. Why am I seeing this? Deconstructing algorithm literacy through the lens of users. Internet Research 32, 4 (2022), 1214--1234.
[90]
Maria STOICESCU and Cosima RUGHINIS, . 2020. LEARNING ABOUT SELF AND SOCIETY THROUGH ONLINE DATING PLATFORMS. eLearning & Software for Education 3 (2020).
[91]
Sindy R Sumter, Laura Vandenbosch, and Loes Ligtenberg. 2017. Love me Tinder: Untangling emerging adults? motivations for using the dating application Tinder. Telematics and informatics 34, 1 (2017), 67--78.
[92]
Joëlle Swart. 2021. Experiencing algorithms: How young people understand, feel about, and engage with algorithmic news selection on social media. Social media society 7, 2 (2021), 20563051211008828.
[93]
Mary Anne Lagmay Tanay, Jo Armes, Catherine Oakley, Lesley Sage, Deb Tanner, Jose Roca, Liz Bryson, Barbara Greenall, Lauren Urwin, Toni Wyatt, et al. 2022. Co-designing a cancer care intervention: reflections of participants and a doctoral researcher on roles and contributions. Research Involvement and Engagement 8, 1 (2022), 36.
[94]
Catalina L Toma and Jeffrey T Hancock. 2010. Looks and lies: The role of physical attractiveness in online dating self-presentation and deception. Communication research 37, 3 (2010), 335--351.
[95]
Kun Tu, Bruno Ribeiro, David Jensen, Don Towsley, Benyuan Liu, Hua Jiang, and XiaodongWang. 2014. Online dating recommendations: matching markets and learning preferences. In Proceedings of the 23rd international conference on world wide web. 787--792.
[96]
Janelle Ward. 2017. What are you doing on Tinder? Impression management on a matchmaking mobile app. Information, Communication & Society 20, 11 (2017), 1644--1659.
[97]
Monica T Whitty. 2008. Revealing the realme, searching for the actualyou: Presentations of self on an internet dating site. Computers in human behavior 24, 4 (2008), 1707--1723.
[98]
Wikipedia. [n. d.]. Elo rating system.
[99]
Wikipedia. [n. d.]. Gale--Shapley algorithm.
[100]
Christine T Wolf, Haiyi Zhu, Julia Bullard, Min Kyung Lee, and Jed R Brubaker. 2018. The changing contours of" participation" in data-driven, algorithmic ecosystems: Challenges, tactics, and an agenda. In Companion of the 2018 ACM Conference on Computer Supported Cooperative Work and Social Computing. 377--384.
[101]
Eva Yiwei Wu, Emily Pedersen, and Niloufar Salehi. 2019. Agent, gatekeeper, drug dealer: How content creators craft algorithmic personas. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (2019), 1--27.
[102]
Angie Zhang, Alexander Boltz, Chun Wei Wang, and Min Kyung Lee. 2022. Algorithmic management reimagined for workers and by workers: Centering worker well-being in gig work. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems. 1--20.
[103]
Douglas Zytko, Sukeshini A Grandhi, and Quentin Jones. 2014. Impression management struggles in online dating. In Proceedings of the 2014 ACM International Conference on Supporting Group Work. 53--62.
[104]
Douglas Zytko, Pamela J. Wisniewski, Shion Guha, Eric PS Baumer, and Min Kyung Lee. 2022. Participatory design of AI systems: opportunities and challenges across diverse users, relationships, and application domains. In CHI Conference on Human Factors in Computing Systems Extended Abstracts. 1--4.
Index Terms
- Beyond Swipes and Scores: Investigating Practices, Challenges and User-Centered Values in Online Dating Algorithms
Recommendations
Construction of Values in Online and Offline Dating Discourses: Comparing Presentational and Articulated Rhetorics of Relationship Seeking
This manuscript compares presentational rhetorics in online personal advertisements to articulated rhetorics generated through interviewing sessions to understand rhetorics of online dating. Online self-presentation literature is reviewed and an ...
Frustrations with Pursuing Casual Encounters through Online Dating
CHI EA '15: Proceedings of the 33rd Annual ACM Conference Extended Abstracts on Human Factors in Computing SystemsMany users of online dating systems have a multitude of relationship goals including casual encounters. However, most studies of online dating systems have focused exclusively on users' abilities to find long-term relationships. This has restricted our ...
Impression management through communication in online dating
CSCW Companion '14: Proceedings of the companion publication of the 17th ACM conference on Computer supported cooperative work & social computingPeople use online dating systems to form and create impressions of potential romantic partners. While there is a wealth of research on the use of profile pages for impression management in online dating systems, there is little work on how other forms ...
Comments
Please enable JavaScript to view thecomments powered by Disqus.Information & Contributors
Information
Published In
November 2024
5177 pages
Copyright © 2024 Owner/Author.
This work is licensed under a Creative Commons Attribution International 4.0 License.
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 08 November 2024
Published in PACMHCI Volume 8, Issue CSCW2
Check for updates
Author Tags
Qualifiers
- Research-article
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 93Total Downloads
- Downloads (Last 12 months)93
- Downloads (Last 6 weeks)93
Reflects downloads up to 18 Nov 2024
Other Metrics
Citations
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in