Difference between revisions of "Bias in Dating Apps"

Revision as of 03:22, 27 January 2023

Bias in dating apps refers to the way the algorithm that operates these apps filters through profiles of users based on certain characteristics, such as race, gender, sexual orientation, age, ability and other factors. This bias can manifest in different ways, including through the use of data gathered from the user’s profile which is usually entered by the user upon creation of the profile, as well as information from social media and other apps that the user chooses to link to the profile, such as Instagram and Spotify ^[1]. The algorithm also uses a technique known as “collaborative filtering”, where the potential profiles shown to users are based on opinions from other users on these apps, such as on apps like Tinder, Bumble, and Hinge ^[2].

History

How the Algorithm Works

Tinder

The algorithm implemented by Tinder is the Elo rating system, which resembles the same method to assess and calculate the relative skill levels of players in zero-sum games such as chess ^[3]. Tinder implements the same concept by coining the term “desirability” instead ^[3]. The app uses this scoring system to compare and match users of those in the same or similar ranking ^[4]. Users who are on the same ratio of right and left swipes are understood by Tinder’s algorithms to be at eye-to-eye desirability ^[4].

Purpose

Types of Bias

Race

Many dating apps had ethnicity filters such as Grindr, Tinder and Bumble, but were pressured to eliminate them after the Black Lives Matter (BLM) movement ^[5]. Currently, dating apps like Hinge and OkCupid allow users to identify their own race and their racial preference in a potential partner ^[5]. When a user decides to share this information, the algorithm would group other individuals by race and learn their preferences from the data it has access to ^[6]. However, even when users refuse to state any race or racial preference, the collaborative data still allows the algorithm to make predictions and recommendations based on similar racial lines by using assumptions about an individual’s race based on the data it has about the preferences of other users who are similar to them in other ways ^[6].

Research has shown that dating apps that allow users to implement racial preferences by filters, or rely on the algorithm to show potential users of the same race, perpetuates racial biases and divisions ^[7]. For example, men and women who identify as black on the app are 10 times more likely to message those who identify as white or caucasian than those who were white to message those who are black ^[7].

Gender and Identity

A study was done on the dating app Tinder, which suggested that there is the existence of gender bias on the platform, where men had a higher success rate of getting matches than women users ^[9]. The reason behind this was due to the relationship of the amount of swipes and the amount of matches made as a result, where they both increased in volume ^[9]. In addition, men users had a higher tendency to make the first move by initiating the conversation after matching ^[9]. The purpose of men using the app as a platform for casual hookups had also contributed to the higher success rate of receiving matches. The study also found that women are more likely to be judged on their physical appearance and how they present themselves, whereas men are judged based on their occupation and education level ^[9].

Sexual Orientation

Queer women reported having to face certain challenges on dating apps, such as exclusion for their sexual orientation, other than being a lesbian ^[10]. HER, a dating app for queer women remains as one of the platforms for those seeking the same dating social space. A claim was made by Exton where “lesbian users are much more valuable”, dismissing the different sexual orientations and are on a different spectrum such as users who are bicurious or bisexual ^[10]. Scarcity was prevalent when lesbian users on all-inclusive dating apps like Tinder, would often be left with no other profiles to swipe on who were in the similar spectrum of sexual orientation. Women of color found it difficult to connect with others of the same race, as these apps were predominantly white ^[10].

There were also risks imposed by the infiltration of users who did not identify with being a queer women, including those who were heterosexual men, heterosexual women, and couples. To an extent where in China, there were users seeking surrogacy services ^[10].

Ableism

Ableism takes on many forms such as not having enough representation for those with disabilities, accessibility options for users with visual or hearing impairments, underrepresentation of individuals with disabilities in advertisements or profiles of users using the app, as well as negative connotations ^[11].

Dating apps heavily focus on visual representation, for example, pictures of the users’ profiles, biography and instances where a conversation occurs through text. These examples present challenges for users who have visual impairments. A study done by Arizona State University’s Center for Cognitive Ubiquitous Computing found that dating apps are hard to visualize, even with the assistance of a screen reader. However, some apps such as Tinder, Hinge and OKCupid implemented features like labeled buttons, clear navigation, and a screen reader to improve accessibility ^[12].

Age

References

1. ↑ Dating apps’ darkest secret: their algorithm. (n.d.). IE HST Rewire Magazine. Retrieved January 26, 2023, from https://rewire.ie.edu/dating-apps-darkest-secret-algorithm/
2. ↑ Tseng, K. (2022, March 21). The Bias and Contradiction of Dating Apps. Viterbi Conversations in Ethics. Retrieved January 26, 2023, from https://vce.usc.edu/weekly-news-profile/the-bias-and-contradiction-of-dating-apps/
3. ↑ ^{3.0 3.1} Tiffany, K. (2019, February 7). The Tinder algorithm, explained. Vox. Retrieved January 26, 2023, from https://www.vox.com/2019/2/7/18210998/tinder-algorithm-swiping-tips-dating-app-science
4. ↑ ^{4.0 4.1} Rolle, M. (2019, January 16). The biases of Tinder’s algorithm. Diggit Magazine. Retrieved January 26, 2023, from https://www.diggitmagazine.com/articles/biases-we-feed-tinder-algorithms
5. ↑ ^{5.0 5.1} Viana, M. (2022, March 6). Should Dating Apps Allow "Ethnicity Filters?" | by Carlyn Beccia | Heart Affairs. Medium. Retrieved January 26, 2023, from https://medium.com/heart-affairs/should-dating-apps-allow-ethnicity-filters-3599ed1b1f35
6. ↑ ^{6.0 6.1} Nader, K. (2021, May 4). Dating Through the Filters. Cambridge University Press. https://www.cambridge.org/core/services/aop-cambridge-core/content/view/EA64BE27CD7D2A1749D712A5E179828D/S0265052521000133a.pdf/dating_through_the_filters.pdf
7. ↑ ^{7.0 7.1} Redesign Dating Apps to Lessen Racial Bias, Study Recommends | Cornell Computing and Information Science. (n.d.). Cornell CIS. Retrieved January 26, 2023, from https://cis.cornell.edu/redesign-dating-apps-lessen-racial-bias-study-recommends
8. ↑ Kleinman, A. (2014, September 12). Black People And Asian Men Have A Much Harder Time Dating On OKCupid. HuffPost. Retrieved January 26, 2023, from https://www.huffpost.com/entry/okcupid-race_n_5811840
9. ↑ ^{9.0 9.1 9.2 9.3} Lopes, M. (2018, July). Gender Bias on Tinder: Transforming an Exploratory Qualitative Survey into Statistical Data for Contextualized Interpretation. https://www.researchgate.net/publication/318170809_Gender_Bias_on_Tinder_Transforming_an_Exploratory_Qualitative_Survey_into_Statistical_Data_for_Contextualized_Interpretation
10. ↑ ^{10.0 10.1 10.2 10.3} Smith, M. G. (2022, October 3). Queer enough to swipe right? Dating app experiences of sexual minority women: A cross-disciplinary review. Science Direct. https://www.sciencedirect.com/science/article/pii/S2451958822000720
11. ↑ Lodhi, T. (n.d.). Ableism. Wikipedia. Retrieved January 26, 2023, from https://en.wikipedia.org/wiki/Ableism
12. ↑ Awad, N. (2022, July 14). How Accessible are Dating Apps? Accessibility.com. Retrieved January 26, 2023, from https://www.accessibility.com/blog/how-accessible-are-dating-apps