With location-aware mobile devices, we can now connect with people in our close vicinity for particular purposes. Dating apps are also referred to as ‘location-based real-time dating’ applications (Handel Shklovski, 2012 ) or ‘People-Nearby Applications’ (Van de Wiele Tom Tong, 2014 ) as they draw on the location of the user in order to provide matches in one’s geographic proximity. , 2015 ; Ellison et al., 2012 ), which could increase impression motivation.
Further, due to the issue of proximity, especially in the case of location-based dating apps, there may be less of a tendency to deceive potential matches, as there is a real chance that they will meet face to face and form a relationship (Ellison et al., 2012 ). Researchers describe this as identifiability or the ease with which an online identity can be connected to a known person (Blackwell et al., 2015 ; Woo, 2006 ). Due to this possibility, Blackwell et al. ( 2015 ) say users have ‘an incentive to present in an attractive, but plausible, light’ (p. 6).
Minimal filtering process
When it comes to choosing romantic partners, filtering works to screen potential contacts. Focusing on how people choose sexual partners online, Couch and Liamputtong ( 2008 ) describe filtering as ‘simple assessments of attractiveness and geography and physical proximity … identity, including appearance, personality, sexual tastes and preferences, and risk management’ (p. 273). Best and Delmege find that in an online dating environment that offers a ‘plethora of choice … filtering strategies are adopted spontaneously and refined conscientiously by participants’ ( 2012 , p. 253). This process is often more complex on dating websites, in which users are allowed to additionally screen potential matches on height and weight (Hancock, indian dating uk app Toma, Ellison, 2007 ), race (Lin Lundquist, 2013 ), and education level (Skopek, Schulz, Blossfeld, 2011 ).
In relation to dating websites, Best and Delmege ( 2012 ) describe the filtering process as starting with an initial screening, where users choose potential romantic partners based on search criteria. Then, users interact with the preselected potential romantic partners via messaging. On Tinder, filtering operates by allowing users to determine with whom they would like the possibility to chat, but users are provided only with geographical proximity, age, and sex as criteria, in contrast to more detailed filtering options on dating websites (Hamilton, 2016 ). This adaptation provides further incentive for research into the impression management practices of dating app users.
With these theoretical considerations, my research tries to answer the following question: What are the pre-match impression management practices of Tinder users? In line with Leary and Kowalski’s ( 1990 ) concept of impression management, my goal is to, first, understand Tinder users’ motivations for downloading and using the app and, second, explore how Tinder users construct her/his profile and swipe potential partners. I examine these queries through interviews with Tinder users in the Netherlands.
Similar to Blackwell et al. ( 2015 ), participants were recruited via Tinder profiles that advertised the study using the University emblem and a brief description. Hamilton and Bowers ( 2006 ) suggest that researchers should ‘select the most appropriate Internet site to place an announcement of the study’ (p. 825). Two profiles with the username ‘TinderStudy’ were created: One male and one female, both with a reported age of 25 years. This strategy allowed me to access both male and female Tinder users, contributing to the aim of interviewing an equal number of each. Participants could email or contact me through Tinder with questions or to participate (see Figure 1).