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Reflections from the 'Strava-sphere': Kudos, community, and (self)-surveillance on a social network for athletes



In recent years, there has been a growing interest in the practice of digital self-tracking. Researchers have drawn attention to who self-tracks, why people self-track, and what it feels like to self-track in the context of sport and physical activity. To date, limited research has focused on self-tracking as a social practice and there has been minimal engagement with the specific online platforms that individuals use to share their self-tracking data online. In this paper I engage with findings from an ethnographic study of Strava, a popular social fitness platform. I propose that while Strava can be a source of motivation and entertainment for its users, and even help to establish or strengthen social networks, the platform invites users to adopt and adapt to technologically-mediated surveillance strategies that encourage and reward displays of bodily self-discipline.
Couture, J. (2021). Reflections from the ‘Strava-sphere’: Kudos, community, and (self-)
surveillance on a social network for athletes. Qualitative Research in Sport, Exercise
and Health, 13(1), 184-200, DOI: 10.1080/2159676X.2020.1836514
In recent years, there has been a growing interest in the practice of digital self-tracking.
Researchers have drawn attention to who self-tracks, why people self-track, and what it feels like
to self-track in the context of sport and physical activity. To date, limited research has focused on
self-tracking as a social practice and there has been minimal engagement with the specific online
platforms that individuals use to share their self-tracking data online. In this paper I engage with
findings from an ethnographic study of Strava, a popular social fitness platform. I propose that
while Strava can be a source of motivation and entertainment for its users, and even help to
establish or strengthen social networks, the platform invites users to adopt and adapt to
technologically-mediated surveillance strategies that encourage and reward displays of bodily
Keywords: Strava, self-tracking, surveillance, physical activity, technology
Over a decade has passed since Apple’s iconic commercial for the App Store first captured the
attention of viewers around the world. The thirty second spot, which premiered in 2009, urged
consumers to think of their cellular phones as more than a communications device1. The
commercial featured Apple’s now-trademarked tagline, ‘there’s an app for that’, which has since
become an iconic piece of pop culture. Now more than a decade since the commercial invited us
to ‘think differently’ about our devices, the most popular apps continue to be those that facilitate
communication2. The ubiquity of app-based social networks, such as Facebook and Twitter, has
had a profound impact on the way we communicate. For many years, Facebook has been among
the most widely used apps around the world3. In recent years, however, the body has also
emerged as a site upon which many app developers have focused their attention, and an ever-
expanding catalogue of apps designed to help users keep track of their fitness and their bodies in
various ways contribute to the near 160,000 different health-related apps now available for
download (Goodyear, Armour, & Wood, 2018).
The focus of this paper is one particular app that has successfully managed to blur the
once rigid boundaries between apps designed for communication and those designed for fitness.
Described as ‘the social network for athletes’, Strava is a web-based platform and mobile app
used by recreational and professional athletes alike and, over the past decade, has established
itself as a global leader in a burgeoning ‘social fitness’ industry. Strava is designed to help users
keep track of their physical activity, but it is also a place to ‘connect with friends and share your
1 See
2 This is an interesting ‘full circle’, of sorts, if we consider that telephones have always been about facilitating
3 Nearly 70% of American adults use Facebook, making it the most widely used of all social media platforms
(Greenwood, Perrin, & Duggan, 2016). Facebook use is reportedly on the decline, however, amongst younger users
who are engaging more often with photo and video-centric platforms such as YouTube, Instagram, and Snapchat
(Anderson & Jiang, 2018).
adventure’ with other users around the world (Strava, 2020). To date, limited attention has been
paid to Strava in the academic literature and, to the best of my knowledge, no empirical research
has engaged with Strava from an ethnographic perspective.
This paper is guided by three central aims. The first is to describe what Strava is, what it
looks like, and what it affords its users, but also to consider what it might have the power to do.
Second, I hope to highlight some of the ways and reasons Strava is used by recreational runners,
a group that has been the subject of many previous studies but, with a few notable exceptions
(Esmonde, 2019, 2020), has seldom been the focus of self-tracking studies. Finally, I attempt to
give voice to some of the methodological tensions and experiences of doing research in
‘ethnographic places’ (Pink, 2009) that transcend a discretely online or offline field of study by
weaving ethnographic field notes into the text as narrative vignettes. This ‘analytic lattice’
(Wacquant, 2011) is used to shed light on some of the affective domains of self-tracking. In so
doing, I hope to draw attention to some of the complexities of doing hybrid ethnographic work
(Przybylski, 2020) all the while offering additional insights into what it feels like to self-track
In what follows, I begin by providing a brief overview of Strava and by highlighting some
of the existing literature that have informed my thinking about digital self-tracking, broadly, and
Strava, more specifically. Next, I outline the methodological approach and specific methods that
were used in this study prior to discussing some of the key findings.
Situating Strava
Strava (from the Swedish word for ‘to strive’) is a social fitness platform designed to help
users to keep track of, analyze, and share their workouts online. First released in 2009, the
platform supports thirty-two types of physical activity but, overwhelmingly, the two most
common activities uploaded to the platform are cycling and running. Mark Gainey, one of
Strava’s co-founders, explains that the idea for the platform first emerged in the mid-1990s but
that he and co-founder, Michael Horvath, were unsure how to turn their idea into a viable
business at the time. To hear them tell it, the platform began as a passion project inspired by
nostalgia. As the story goes, the idea behind Strava was to create a ‘virtual locker room’ that
would mimic the type of supportive and playfully competitive environment the two fondly
remembered as varsity crew athletes at Harvard in the late 80s (Schoups, 2017, n.p.). Horvath
has described how it was his teammates that often motivated him the most during his varsity
career, often more than the sport itself. Strava was created with this in mind. There are many
products on the market designed to help athletes get fitter, faster, or stronger. For Gainey and
Horvath, Strava was about finding a way to keep people connected, entertained, and motivated in
between their workouts.
Strava first launched as a browser-based platform. Users would have to physically
connect their wearable tracking devices to a computer and manually upload their data to the
platform. In 2011, Strava released an app-based version of the platform, which removed the need
for a third-party device since users could now use their smartphones to track their workouts.
Strava’s user base doubled over the next two years, and has continued to see near-linear growth
in the years that have since passed. In 2017, more than one billion activities were uploaded to the
platform (Strava, 2020) and an article published in Outside magazine in 2019 suggested that
nearly a million new accounts were being created every month (Lindsay, 2019). Self-
quantification, it seems, has gone mainstream.
Literature Review & Theoretical Overview
Digital self-tracking and the ‘Quantified Self’
In recent years there has been a proliferation of academic interest in the practice of
digital self-tracking. Researchers have drawn attention to questions including who self-
tracks and why people self-track (Lupton, 2017; Goodyear, Kerner, & Quennerstedt, 2019)
and others have highlighted some of the different ways that digital self-tracking devices are
used and what it feels like to self-track (Esmonde, 2019; Fotopoulou & O’Riordan, 2017).
With a few notable exceptions, limited research has focused on digital self-tracking as a
social practice, particularly in the context of sport and physical activity (Lupton, 2017;
Pink et. al, 2017). As many have rightly identified, there is nothing new about self tracking
(Lupton, 2016; Millington, 2017). What is new is the ease of self-tracking. Self-tracking is
increasingly automated and, with the assistance of various ‘smart devices’ that “facilitate
the collection of ever-more detailed personal information” keeping track of the self has
become less a task that people do and, rather, something that is done for us (Lupton, 2017,
p. 564).
The term ‘the Quantified Self’ (QS) was first coined in 2007 by Gary Wolf and Kevin
Kelly, then-editors of Wired magazine. To hear members of the QS community tell it, to self-
quantify is insightful in its own right, but also serves as a meaningful way to see and measure
self-improvement. As Millington (2014) suggests, “‘bettering the self’ stands as a primary reason
for using health and fitness apps” and he explains that health and fitness app adherents, many of
whom routinely “divid[e] their bodies and habits into atomized components”, are encouraged to
share these measurements with others in “an assortment of online communities” (p. 487-488).
As noted by Fotopoulou and O’Riordan (2017), the sharing of personal self-tracking data
can also be understood as a biopedagogical apparatus to the extent that people learn about their
bodies and “learn to selfcare” by using wearable self-tracking technologies (p. 54). They explain
that the “micropractices of knowing one’s body through data regulate the contemporary fit and
healthy subject” and suggest that digital self-tracking devices, though often understood as
informative and innocuous, are, in fact, normalizing devices that “teac[h] users how to be good
consumers and [proper] biocitizens” (p. 54).
Health(ism) and the datafied body
Neoliberal narratives of health hold that bodily discipline is both a personal and moral
responsibility. From such a perspective, those who fail to ‘appropriately’ discipline their bodies
(whether through exercise or diet) are understood as less responsible than those who do. Such an
understanding of health is commonly referred to as healthism (Crawford, 1980) and it has been
well-established that healthism is an important lens through which to examine people’s
participation in and perceptions of physical (in)activity (see Ayo, 2012; Wiest, Andrews, &
Giardina, 2015). Millington (2016) explains how healthist understandings of the body “helped to
establish the ‘common sense’ of neoliberalism” during the first fitness boom of the late 1970s
and early 80s, and describes how the fit body not only functioned as a status symbol, imbued
with social and cultural capital, but that this mode of thinking came to influence prevailing
understandings of health, as something that was “legible on the body” (p. 1186).
As noted by Wiest, Andrews, and Giardina (2015), “there has been substantial shift in the
ways that individuals are said to be uniquely responsibility to pursue healthiness (in particular
ways, with particular idealized outcomes)” and remind us thatthe relationship conjoining health
and fitness is not given” but, rather, “is a product of the historical and contextual forces that
make fitness a necessary constituent of healthiness (p. 22). In the contemporary moment, routine
digital self-tracking and, in particular, the use of health and fitness apps in the interest of self-
discipline and self-improvement are one of those ways. ). Millington (2016) explains that fitness
technologies have long been promoted as a means of empowering individuals and, to this day,
are routinely framed as one of many purchasable tools that people can use to ‘achieve’ good
health. As Ruckenstein (2014) suggests that “when bodies and lives are made more transparent,
they can be better acknowledged and acted upon” and, thus, “[w]ith the aid of digital
technology…optimization becomes not only possible, but also desirable (Ruckenstein, 2014, p.
Social networks and surveillance
Michel Foucault (1975) famously drew attention to the panopticon as a way of
conceptualizing the disciplinary society, but the extent to which online spaces can or should be
considered ‘panoptic’ continues to be a source of debate. Over the years, there has been talk of an
‘electronic panopticon’ (Lyon, 1993), an ‘information panopticon’ (Zuboff, 1988) and a ‘mobile
panopticon’ (Rämö & Edenius, 2008), but the very idea of digital panopticism has also been
troubled due to the ways that surveillance is often understood in digital spaces. Lupton (2012)
suggests that social self-tracking software complicates the idea of panopticism altogether since
digital self-trackers invite the gaze upon themselves and often enjoy the surveillance from others.
But how are we to make sense of people’s willing participation in their own surveillance,
particularly in a historical moment in which controversies about the rise of intrusive, oftentimes
state-sanctioned, forms of surveillance continue to make headlines around the world? Anders
Albrechtslund’s (2008) notion of participatory surveillance is helpful in this regard. He explains
that online social networking is anchored in surveillance practices, but that active participation in
one’s own surveillance works to challenge traditional ‘top-down’ understandings of surveillance
and, importantly, can empower (rather than violate) those who consensually participate. There
are clear similarities between what Albrechtslund describes and what Koskela (2004) calls
empowering exhibitionism. Though originally developed in reference to a then-growing use of
home webcams, Koskela explains that the virtual world was once imagined and talked about as a
place where identities could be hidden (cf. Rheingold, 1993), but that new technologies have
turned this upside down and brought the body back into focus.
(Digital) Ethnographic Methods
This study is drawn from a larger ethnographic project on contemporary running
culture(s). Methodologically, this has involved spending a great deal of time with runners ‘where
they are’. I have participated in weekly group runs, competing in local races, and partaken in a
host of other running-related social events. Importantly, early on in my time in the field, I learned
that Strava is one of the ‘places’ where runners routinely interact. People’s lives are increasingly-
saturated with computer-mediated communication and, as Hine (2015) suggests, contemporary
ethnographers “need to take part in those mediated communications alongside whatever face-to-
face interactions may occur” (p. 3). With this in mind, I have also spent time a great deal of time
online, using Strava, all the while observing and interacting with other Strava users. Postil and
Pink (2012) explain thattechnologies are often part of how ethnographic research participants
navigate their wider social, material and technological worlds” and it is helpful to consider
Strava as one piece of a larger ‘ethnographic place’ (p. 124).
Participant observation is widely understood as one of the primary methods used in
ethnographic research, but Wacquant’s (2004) notion of observant participation better reflects
the method(s) used to carry out this particular study. Over the past three years, I have self-tracked
nearly all forms of physical activity; each of my runs, my bike rides, my swims, my yoga
practice – even my daily dog walks – were tracked and uploaded to Strava. To participate fully in
this space, however, meant more than a commitment to digital self-tracking; I also ‘followed’
(and was followed by) a number of other Strava users, many of whom I knew prior to the start of
the project but others were individuals I met in the field.
Detailed field notes were kept throughout the research process. These consist primarily of
observations but also include an “outpouring of memories, thoughts and words” derived from my
experiences with self-tracking and my interactions with other self-trackers (Emerson, Fretz, &
Shaw, 2001, p. 357). As Thorpe and Olive (2016) explain, it can often be difficult to take notes in
the field. The act of pulling out a pen and notebook while running, for instance, would have not
only been impractical but, importantly, would have also have risked disrupting or otherwise
influencing the moment. For this reason, field notes were written as soon as possible after my
time in the field. Digital screenshots were also used as a means of archiving certain posts,
interactions, or other notable ‘moments’ observed online. Screenshots are a convenient method
of capturing data but, perhaps most importantly, can help render permanent an image or an
exchange that might otherwise be lost in the midst of an ever-shifting digital landscape.
No matter how ‘active’ my participation in this space, my perspectives and interpretations
alone can only get me so far in terms of learning what this platform means to Strava users. For
this reason, a series of qualitative interviews were conducted with runners who were regular
Strava users in an attempt to create a space where they might “tell stories, accounts, reports
and/or descriptions about their perspectives, insights, experiences, feelings, emotions and/or
behaviours” (Smith & Sparkes, 2016, p. 103). Interviews were conducted over a span of six
months and took place in a variety of different settings including coffee shops, restaurants, and
offices. Interviews varied in length from just over an hour to two and half hours.
Participant recruitment
A total of sixteen Strava users were interviewed for this study. Following approval from
my home institution’s University Ethical Review Board, recruitment began in August 2019 when
I created a post on Strava4 that provided a brief overview of the study and contact information.
There are clear advantages and limitations of using Strava as a site of participant recruitment.
Individuals who saw the post were, by default, Strava users by default, which automatically
fulfilled one of two inclusionary criteria. For a user to have seen the post, however, means they
had to have been following me on Strava. Finally, since social network feeds are dynamic and
ever-changing, to have seen the post in their ‘feed’, users would have had to have logged into the
platform sometime on or around August 27, 2020, the date of the original post.
Thirteen people reached out in response to the post on Strava and, of those thirteen, eight
met the additional criteria and chose to participate in the study. With my consent, some
participants shared my contact information with friends, which yielded three additional
participants. In addition, five other individuals with whom I had made connections in the field
each expressed interest in participating in the study.
The individuals whose voices and experiences are (in)directly represented in this paper
range in age from twenty-three to sixty-one and represent a variety of racialized identities,
sexualities, and professions. Importantly, while each of these individuals actively participated in
one or more recreational running groups at the time of the interviews, their experiences with
running and their identities as runners were far from homogenous. Some participants self-
4 In addition to those posts that are generated each time a Strava user uploads their physical activity data to the
platform, users can also create text-based posts, similar to those found on other social networking platforms.
identified as lifelong runners while others came to running later in life, as adults. There was also
great variability with regard to participants’ use of self-tracking devices; some self-identified as
diligent self-trackers (for whom physical activity was one of many things they tracked) whereas
others only tracked their running.
Data analysis
Two methods of analysis were used in this study. Interview transcripts were analyzed
using an inductive thematic analysis. Braun, Clarke and Weate (2016) suggest that thematic
analysis “offers a method for identifying patterns (‘themes’) in a dataset” and help researchers
“describe[e] and interpre[t] the meaning and importance of those” patterns (p. 191). Key terms
and themes were identified and close attention was paid to those comments and perspectives that
were consistent among participants, but also to those that stood out as distinct from, or otherwise
inconsistent with, what I heard from others. To be sure, analysis also occurred during the
interviews themselves. Handwritten notes scribbled into the margins of my interview guide often
served as analytic notations; certain words were underlined or circled repeatedly and arrows or
lines were sometimes drawn between words as a way mapping ideas and making thematic
connections ‘on the fly’.
It is widely understood that ethnographic studies involve immersion into the cultures,
“contexts, environment, situations, and lifeworlds of [its] subjects” (Altheide & Schneider, 2013,
p. 26). With this in mind, ethnographic content analysis (ECA) was used to examine various
other types of data collected during my time in the field. As noted by Altheide and Schneider
(2013), “products of social interaction”, including documents, photographs, and other types of
digital communication, are ripe for interpretive analysis (p. 24). As noted above, digital
screenshots were collected throughout the duration of this project to help capture particular
‘moments’ and interactions on social networks including (but not limited to) Strava. Analysis of
these screenshots involved “marking what is of interest in the text” (Seidman, 1998, p. 100)
language and imagery that stood out as noteworthy or atypical, but also that which represented
normal imagery and mundane ‘everyday’ interactions in these digital spaces.
The interpretations of the data in the sections that follow are one of many plausible
interpretations, informed both by previous research and, of course, by my own subject position
as a white, male, able-bodied, runner/researcher who self-tracks. The purpose of this project is
not to make broad claims or widely-generalizable truths about what it means or what it feels like
to use Strava. Rather, the findings discussed in in this paper are designed to highlight different
ways of seeing and thinking about Strava and the practice of social self-tracking in the
contemporary moment.
Findings & Discussion
Strava as site of self-tracking
Sunday, August 5 th
, 2018
I remember being pretty resistant to it at first. Do I really need another social
network in my life? The numbers are fun but its also the social piece, maybe more
than I care to admit. I think maybe there’s a part of it that appeals to the gamer in
me. Two quick taps of my finger and I’m back into this this extended community. It’s
bizarre to think about, let alone write about. The seamless ‘scan-assess-compare’
happens so quickly that it’s tough to pull apart - a learned process, I guess.
There are many similarities
between Strava and other popular
social networks. Like Instagram and
Snapchat, Strava uses a now-familiar
system of ‘following’ other users. By
Figure 2: A variety of data
insights are available to users.
Figure 1: Strava posts include
detailed maps of the activity.
Figure 3: Strava keeps track of
user's efforts over time.
following someone on Strava users can see and comment on the other users’ posts in a
centralized ‘feed’. One of the things that sets Strava apart is the type of data that are commonly
shared on the platform. Whereas text-based posts and photographs of food or family vacations
might be considered the common currency of many online social networks, Strava operates near-
exclusively through the sharing of biometric data. A post on Strava is generated each time an
activity is uploaded to the platform (a process which is oftentimes automated), which also stands
in marked contrast to other social media platforms, which require a certain degree of agency with
respect to creating a post5. Since the majority of Strava users self-track with GPS-enabled
devices, posts typically include maps showing precisely where a particular bout of physical
activity took place (see Fig. 1) in addition to other data such as distance, pace, and estimated
caloric expenditure.
A single tap on any one post allows for a ‘deeper dive’ into the data; information is rendered into
easy-to-read charts and colour-coded graphics which allows for quick assessments (see Fig. 2).
Users can also assess how their most recent activity stacks up against previous efforts and
5 It could be argued that the question of agency is a slippery one if we consider that a user must have engaged in
physical activity of some kind for it to be generated. It nevertheless seems there is a distinction to be made here.
Strava’s ranked leaderboards allow users to directly compare their efforts on popular routes
(known as Strava ‘Segments’) against their followers, but also against any Strava user who has
ever completed that ‘segment’ before (Fig. 3). Lupton (2013) reminds us that numbers are not
neutral, “despite the accepted concept of them as devoid of value judgements, assumptions and
meanings”, and it is not difficult to imagine how some of the technological affordances of Strava
might be encouraging for one user but equally discouraging for another (p. 399).
A few of the runners I spoke to were quite reflexive when it came to thinking about the
possible effects of being routinely exposed to other people’s data. Wanda (age 45) felt that it
could be good for some people but acknowledged that there are certain variables that come into
play, such as a person’s insecurities and personal expectations, which might influence how they
interpret, or are influenced by, other people’s data. She emphasized that the extent to which
someone might feel motivated or disheartened would hinge on their self awareness and ‘how
serious they take themselves’.
I totally accept that my times are not gonna be as fast as they used to be, so when I
see people that are in their 20s and 30s and they’re getting faster and faster.
Obviously there’s a little bit of the ‘Oh, I remember when I used to run like…’ or ‘I
wonder if I can…’ and then I’m like ‘Oh, right. It hurts when I wake up’ [laughter].
Kris (age 38) offered a different perspective, inspired by what he referred to as the ‘social media
effect’, that invites us to consider the ‘liveliness’ of the data on consumed on Strava.
I’ve read multiple articles that say the impact that social networks have on people is
it actually makes them unhappy. They see these amazing pictures of everyone living
glamourous lives…and they feel unhappy about the fact that they’re not doing it. So,
if you agree to that theory, and you draw parallels to the running community and
social networks like Strava…if you see people posting ridiculous times or going
insane distances, is the impact gonna be that you feel less satisfied with your own
Lupton (2016) uses the term ‘lively data’ to describe how “people live with, by, and through data
they produce” (p. 1). Lively data matters, she suggests, not only since it digitally represents
particular fragmented facets of human life, but also because it is increasingly social; it
“circulate[s] and combine[s] and recombine[s] in the digital data economy” and can come to
influence people's lives in meaningful ways6 (Lupton, 2016, p. 1-2). Put another way, data has a
life of its own – it can interact with, inform, and act upon those who play no part in its creation.
A Strava user might use data in particular ways during their physical activity (to monitor their
pace or heart rate) or sometime shortly thereafter (to compare their efforts over time), but this
very same data can have a different use value for other actors7 (Millington, 2016). Another user
might use the same data to learn a new running route but they might also, as Kris alludes to
above, use it might also be used as a basis of comparison which have the ability to influence how
users think about their fitness.
Strava as a site for self-trackers
Van Djick (2013) explains that from the earliest days of social media, online platforms
have been presented as tools for making connections and building community, and Strava is no
exception (see Fig. 5). Most of the runners I spoke
with told me that they used Strava, first and
foremost, to keep track of their individual efforts, but
the idea of Strava as a community also featured
prominently in our conversations. Many runners
explained that Strava has become ‘just a part of their
daily social media routine' and that, not unlike Facebook or Instagram, they would often casually
6 Digital self-tracking data is increasingly promoted in the workplace and, in certain contexts, can influence
personal insurance rates (see McFall, 2019). Self-tracking data have also played key roles in lawsuits where
‘quantified self-incrimination’ has (dis)proven claims made in the courtroom (Crawford et al., 2015).
7 While not the focus of this paper, Strava Metro is a subsidiary of Strava that aggregates and de-identifies user-
generated data and provides it to third parties such as departments of transportation and other city planning groups,
“to improve infrastructure for bicyclists and pedestrians” (Strava Metro, 2020, n.p.).
Figure 5: Screenshot from the Strava website
open the app and quickly scroll through to see ‘if they’d missed anything’, oftentimes dolling out
Kudos along the way.
As the founder of a local run club, Karina (age 51) explained that Strava was originally
sold to her ‘as sort of like a Facebook for athletes’. When she first signed up, she found the
personal insights interesting she enjoyed seeing her efforts broken down in but it quickly
became ‘a lot of fun’ for her to complete various monthly challenges and see other people reach
for their fitness goals.
I like comparing my own efforts…but it is cool to see other people’s training- to see
what they’re doing…it’s cool to see what other people are capable of…to read about
how their run went, or their hike, or whatever it is they’re doing. It’s fun!
Similarly, Kris told me that he seldom uses ‘traditional’ social networks such as Facebook but
that he increasingly spends a lot of time on Strava.
I didn’t like the content I was seeing…people ranting about current events- I didn’t
like that at all. I like that on Strava all I see is people’s workouts…‘Oh, you’re faster,
you got a PR, you’re trending up’ …I love seeing that. I could look at that all day
Lupton (2012) suggests that digital self-tracking software effectively “reconfigures the subject of
surveillance” to the extent that it not only encourages users to surveil themselves but also
encourages them to “invite others to do so” (p. 11). She explains that “when an act of
surveillance is rendered playful and willful or consenting it becomes far more acceptable than
those acts of surveillance that are perceived as being imposed by others” (Lupton, 2016, p. 85).
The above excerpts from Karina and Kris are each insightful in their own right, but also support
previous studies that describe digital self-tracking as both insightful and as fun (Lupton, 2016;
Fotopoulou and O’Riordan, 2017). Karina explained that the social element of Strava is a
significant part of its appeal; the platform allows her to connect with, and feel connected to,
people she knows and runs with offline.
Twenty years ago, to connect with someone you had to connect with them in real
life. There was no other option. But people are making connections on social media.
I don’t know if it’s a good thing or a bad thing… Like, we’re making connections
and they do appear...real. You’re connecting with them, you’re commenting, you’re
giving support. It’s good though, I think, especially for people who maybe feel like
they’re alone.
Here, Karina alludes to something that technological theorists have written about at length (cf.
Rheingold, 1993); digital communities such as Strava can be experienced as meaningful sites of
interpersonal connection.
Strava Clubs are an immensely popular feature designed, in part, to add another layer of
sociality to the platform. By joining a Strava Club, users can see, comment on, and give Kudos
to other members, effectively extending their virtual social network. According to its website,
there are now hundreds of thousands of unique Strava Clubs. Some are very small, and might
consist of a small group of friends who train together (offline) and want a place to (re)connect
online, but others are much larger. Clubs are free to join and, with a few exceptions, there are no
restrictions on who can join a Club. Some Clubs are based on an affinity for a particular brand,
such as the Lululemon Run Club, which has nearly 180,000 members, whereas others seem to
function as virtual extensions of groups that exist offline. Karina’s aforementioned run club, for
instance, meets every second Saturday and typically draws anywhere from ten to upwards of
thirty runners. On Strava, however, the same group boasts a membership of nearly six hundred,
including members from Canada, where the club is based, but also from Russia, Vietnam, and
the United States. As Karina suggests, some of the technological affordances of Strava might
help to cultivate or maintain a feeling of connection via connectivity that might be particularly
valuable for individuals who lack training partners or other support systems that are often ‘built-
in’ to offline/physical sporting communities.
Monday, July 21, 2019
I’m cracked. Haven’t ran like that in weeks. I reach for my phone and fire up Strava
before I even take my shoes off. Propped up against the kitchen counter, entirely
unfazed by the beads of sweat dripping from my forehead down onto the orange glow
of the screen, I (am) consume(d by) the data.
I PR’d that segment along Marine Drive!?
Didn’t even feel like I was pushing that hard.
Kate was right. Consistency is paying off.
*Single tap, Swipe up*
Oh, wow. Nick crushed his long run! Sub
4:50 for 22km? Wow.
*Swipe up*
Oh, nice! Hasan’s race went so much better
than he thought it would. 41:02! I knew he had it in him.
[Comment] “Nicely done, sir! #speedy
*Swipe up*
Another huge week for Janelle. 147km?
Who the hell has the time for that?
*Swipe up*
Looks like Lindsay and the rest of the crew had fun at the track.
[Kudos] [Kudos] [Kudos]
[Comment] “I swear I’ll make it out next week!”
*Double tap, swipe left*
Perspectives on privacy
Both among scholars and the broader public alike, concerns
about privacy continue to be raised with regard to social
networking sites (see Madden, 2012; Marwick & boyd, 2014).
Like other social networking platforms, Strava offers users some
control over their privacy settings, but the platform is perhaps
Figure 9: Creating a ‘Privacy Zone’
allows Strava users to hide where they
start and finish their activity.
best understood as “public-by-default [and] private-through-effort” (boyd, 2011, p. 507). Users
can choose to make some or all of their activities private but, as some runners told me, this
comes with a trade off since it limits some of the platform’s features, such as Segments and
ranked leaderboards, which many users enjoy. For instance, users can create a custom ‘Privacy
Zone’ around a particular area which limits what other users can see on the map that is included
by default with each activity (Fig. 9) Surprisingly few of the runners I spoke with had any
serious concerns about privacy. Of those who did, however, a clear distinction was drawn
between data privacy and personal privacy.
I have zero concerns with data about my running being online. I just don't want
people to know where my home is. (Tina, age 33)
I suppose if someone really wanted to find me they could figure it out…I never
thought of it as a bad thing. I figure, at this point, these companies know so much
about us…I don’t know if I stop using if it’s really gonna make a difference. (Lyn,
age 42)
Now I have the privacy zones around my work and my used to be public
because the hook was that if it’s public then you’ll be on the leaderboards and all
that…but I’ve kind of devalued that. I’m like, no, my privacy’s more important. I just
don’t like the idea that someone could find out where I live and see my health data,
my heart rate information, you know. I don’t want that information out there. (Kris,
age 38)
Madden (2012) explains that there continues to be a polarizing debate about whether or not
privacy “can be dismissed as a relic in the information age” and statements such as these, from
Tina and Lyn, really speak to this idea of the expectation (or lack thereof) of privacy in online
spaces (p. 4). Notably, other than Kris, only one of the men I spoke with used any privacy
settings at all. Carter (age 61) described it as simply not something he was all that concerned
with. ‘People know where I live anyways’, he told me. ‘It’s not like it would be rocket science to
figure it out.’ Conversely, all but one of the women had created Privacy Zones, most often
around their homes but also around their places of work. Sandra (age 49) emphasized that she
hardly used Strava as a social platform whatsoever and that this was largely tied to concerns
about her own physical safety.
Being a woman, it’s kind of a safety thing... I'm not really worried about animal
predators. I’m worried about human predators.
Sandra’s concerns were echoed by other women I spoke with, many of whom described having
to routinely deny requests to be followed by users they did not know (oftentimes men), with
several describing this as an ongoing ordeal.
I’m like, ‘No, I don’t know you.’ I’ve denied them ten times but they keep trying.
(Cindy, age 27)
As these examples suggest, there seem to be some distinctly gendered differences with regard to
both whether and how some Strava users think about data, privacy, and physical safety. As
Anders Albrechtslund (2008) suggests, social networks are a ‘snoop’s dream’. The fact that the
majority of Strava posts include detailed GPS-generated maps that show other users precisely
when and where other users exercise, invites new ways of thinking about the possible
implications of being ‘followed’ by someone online.
Thursday, December 13 th
, 2018
I can see him from across the store. At least I’m pretty sure it’s him. He’s looked over
here at least twice now. One of these nights I should really just go introduce myself. I
don’t know why I haven’t. It just feels weird. I scan the room, purposefully trying to
avoid eye contact. Perfect, Blake’s here. I get two steps in his direction, but I’m cut
off mid-step. Clearly, he decided it wasn’t so awkward.
“Heyyyy! You’re [author], right?”
“I am indeed. And you are... John.”
“Yeah, man. John C.! You know, from Strava!
This is weird, right? It’s cool to meet you in real life!”
“Yeah, it sure is.
You runnin’ the ten tonight, John?”
“Yeah, I’m feeling great these days.
What about you?”
“Nah, I’ve been running a lot the past couple weeks
…but I guess you know that?”
Engulfed in the loud pre-run chatter of forty-some runners itching to head outside,
we share a deafening silence. It’s the first time I’ve experienced anything like this.
John and I have followed each other on Strava for well over a year. I don’t know how
it happened. We must know some of the same people, but I don’t know John. I know
how fast he runs. I know where he runs. I know who he runs with. I see his posts
almost every day and presumably he sees mine. As we funnel out the door into the
brisk winter air I can’t help but smile as I wonder how many times we’ve
unknowingly ran together at one of these group runs, maybe even side-by-side in
complete silence, and then gone home and given each other Kudos on Strava.
When data is disrupted/ive
In one of the few mentions of Strava in the academic literature, one of the participants in
Pink et al.’s (2017) study of commuting cyclists who self-track said, in response to an untracked
ride, that ‘if it isn’t on Strava, it didn’t happen’ (p. 8). This comment came up, in many cases
verbatim, in several conversations. Most said it half-heartedly, with a smile on their face, and
often only the first half of the sentence was uttered, the expectation being that I knew the rest.
This is a ‘Strava-ism’ that circulates with fervour, particularly amongst runners and cyclists. Of
course, the idea that a person feels they should not or cannot exercise without said activity being
tracked and shared online is fascinating for at least two reasons. On one hand, a statement such
as this makes clear the way that self-tracking has become so common as to have influenced ‘the
stories runners tell’, both about themselves and about their exercise habits. On the other hand, it
reflects a normalization of data (over)reliance, which raises further questions about the reason(s)
why people exercise in the first place. In jest or otherwise, to imply that physical activity did not
happen if it was not tracked and made visible to others reflects a relationship to exercise that
seems to be based less on the act of doing it than the fact that it was done. That is, there is a sense
that the desire to ensure that an activity is recorded is only somewhat tied to its (in)visibility to
others. Rather, it seems that much of the anxiety around not having a particular activity recorded
stems from a concern that it might influence the ‘big picture’ when it comes to the data or, put
differently, that the data would no longer faithfully represent all that had happened.
Saturday, January 4 th
, 2020
I’d be lying if I said I didn’t enjoy it. I really do. But the hard truth is that I’m also
increasingly uncomfortable with it. I worry about my reliance on it. It would take me
no time at all to find out how fast Jay and I ran on that ‘stupid cold’ Thursday night
back in December. I could find out exactly how miles I banked in the lead-up to my
first ultra, or what my average cadence is on a quick 5km. But there’s nowhere I can
to find out when I seem to have decided that I’m okay with it telling me if I had a
good run. That’s the part that bothers me. I worry that it’s changed how and
sometimes why I run. I mentioned to K. last night that when this is all over I might
try to start running ‘naked’ again. No watch, no tracking - completely technology
free. She smiled and told me she’d believe it when she sees it. Fair enough. So will I.
During my time spent using Strava, I observed countless instances of users ‘calling out’
their self-tracking devices, the GPS satellites, or Strava itself, for distorting or somehow sullying
the data (see Fig. 7). In these cases, either the title or description section of an activity-based post
was used to help justify to any potential onlookers what the data ‘said’. To be sure, these
attempts to discredit the data seem to sit in a bit of an uncomfortable tension with the ways that,
in other contexts, the data are more or less taken as the ‘truth’ of what happened, as exemplified
by the aforementioned desire to have all activities tracked so as to have a complete and ‘accurate’
representation of a user’s training.
Also intriguing was the ways that pain and ‘suffering’ were represented on Strava or,
more precisely, how the word suffering and other language used to connote pain is used by some
Strava users. Atkinson (2015) explains that sociological literature on pain and injury in sport has
often highlighted how “athletes generally avoid, disavow or privately manage…forms of
suffering” (p. 100). Based on my observations, this is not always the case on Strava. This is a
space where self-imposed ‘suffering’ is lauded or, at least, where
discursive representations thereof are celebrated and, in some cases,
rewarded with more comments and Kudos from other users. To be sure,
this is hardly the norm, and I not convinced that Strava is best
understood as a ‘pain community’ comprised of users with a
“penchant for self-imposed agony [that] binds them together”
(Atkinson, 2008, p. 166). Rather, this is a space where feats of
athleticism are discursively constructed as grueling, as painful, or as
‘sufferfests’ (see Fig. 8). Of course there is no way of knowing the
extent to which an activity was, in fact, painful. Strava users cannot
see the activity unfold in ‘real time’, but instead are presented with
insights (in the form of data) and highlights (in the form of photos and user descriptions) after
the fact. Sandra (age 49) felt that Strava could be very empowering for some people, but felt
strongly that much of this empowerment was tied to a feeling of validation from other users.
I think with Strava, it’s the humble brag…‘Oh, I'm training for this race. Look at this
30k run that I did in the mountains with, like, 2000ft of elevation…You wanna show
off your badassery.
To use Sandra’s language, the rhetorical use of evocative language seems to reflect a purposeful
framing of the self in such a way that demonstrates to others how much their body can endure.
Strava is a site where feats of athleticism are shared, but also a stage upon which individual
actors can curate and perform the athletic self (Goffman, 1959). Both the attempts to justify
‘incorrect’ data and the purposeful framing of activities in particular ways are each impression
management strategies which are insightful in their own right but also align well with previous
studies on social media use amongst athletes (Smith & Sanderson, 2015).
The boastful behaviour that Sandra describes above might be read as egotistical in other
contexts or as an outsider looking in. I vividly recall the first time I overheard a runner describe
Strava to an inquisitive friend as an acronym for Socially Tracking All Vain Activity’. Indeed,
there seems to be a socially-sanctioned level of acceptable narcissism in this space and the same
can be said of exhibitionism. That people want to share with others that they are achieving their
goals makes sense and, as highlighted above, some Strava users enjoy seeing their friends’
progress. From another perspective, the desire to post with regularity might also be read as a way
of routinely re-affirming and showcasing personal responsibility
when it comes to health. To be active on Strava demonstrates a
steadfast commitment to an ongoing self-improvement ‘project’.
Strava is quite literally a ‘technology of the self’ (Foucault, 1975)
that represents, reifies, and perpetuates neoliberal narratives about
the body as an ever-unfinished ‘work in progress’. As Andrejevic
(2004) suggests that “in a climate of perceived risk” it is not
uncommon for individuals to adopt and make use of technologies
“that correspond with an ideology of ‘responsibilization’” and this is
particularly apt when it comes to thinking about Strava (p. 479). This
is a site where fitness is quantifiable and where health is understood as
 
both something to be achieved but also something to be enacted and shared. Strava invites us to
consider how health and fitness are no longer legible exclusively on the body but also from a
distance, behind the warm glow of a screen.
Concluding Thoughts
Hine (2015) questions whether “the internet [has] strengthened, enriched, or challenged
our sense of community” and, while I cannot say with any degree of certainty, it seems to me that
it has changed it in some ways (p. 1). In this paper, I have sought to highlight some of the ways
that Strava is used and experienced by recreational runners, who invite us to consider not only
how sharing data while self-tracking can be fun and empowering but also how it can be
experienced as an important and interactive site of community.
This paper responds to a call made by Pink et al. (2017) for “focused and in-depth
investigation into the human experiences, routines, improvisations and accomplishments…which
implicate digital data in the flow of the everyday” and, in so doing, adds to an ever-expanding
body of research focused on digital self-tracking in the context of sport and physical activity and
builds upon previous critical studies of recreational running cultures. Further, by drawing
attention to some of the ‘behind the scenes’ negotiations that can accompany the doing of
ethnographic research, this paper adds to a rich body of work that highlights the lived
experiences of ethnographers of sport and physical cultures.
Given its global popularity and its support of a wide range of physical activities, future
studies might seek to examine how Strava is used in other sporting contexts since these might
vary, in some important ways, from the findings discussed here. Moreover, this study focused
exclusively on the attitudes and experiences of current, habitual, Strava users, each of whom
reside in a large urban city in Canada. Studies that examine some of the reasons why people stop
using Strava would help us to better understand the role(s) and influence that digital health
technologies might have on people’s relationship to data and, too, their participation in sport and
physical activity. There is also much to be learned about the experiences of Strava users in rural
areas and other geographic locales and, in particular, about the extent to which the networked
connectivity afforded by Strava might, as one user in this study suggests, have the ability to
influence feelings of connectedness to a larger global community. It seems to me that this is a
particularly salient avenue of inquiry in the current moment, not least since the COVID-19
pandemic has had a profound impact on the ways that individuals are encouraged to stay
connected while adhering to social distancing regulations.
Lupton (2016) suggests that “research into people’s use of digital technologies for
recreation” can offer valuable insights into “the pleasures, the excitements and the playful
dimensions of digital encounters” (p. 710). There is still much to be learned about the many
different ways that people engage with and understand digital health technologies such as Strava.
It is hoped that this paper sparks conversation, stimulates new ideas, and inspires further research
on digital self-tracking as a meaningful and increasingly social practice.
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... Zu den hochtechnologisch mediatisierten Formen der Selbstoptimierung sind zuletzt detailreiche Studien erschienen, die den Erfahrungen der Akteur_innen auf die Spur gehen (etwa: Selke 2016; Wiedemann 2019; Plohr 2021). Strava ist ein wiederkehrender Fall (Lupton 2016;Lupton et al. 2018;Rivers 2020;Couture 2021). Aufwändige Methoden (etwa Videoaufnahmen) erlauben eine vertiefende Diskussion von qualitativen Differenzen. ...
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Digital technologies transform social practices and pervade the formation of social order in a diffuse form. Platforms become everyday companions and pose fundamental conceptual and methodological challenges to sociology. The article sheds light on the socio-technical configuration of sport and asks how a technological mediation of cycling helps shape (self-)evaluation and informs qualities of intensity in sporting activity. The article is based on autoethnographic research on digitalised road cycling, conducted with different sensor technologies and guided by the digital platform “Strava”, a popular social network for amateur and professional athletes. The article highlights the human and machine dimensions of data practices and takes from the social science research discourse on self-optimisation and self-tracking the desideratum of unfolding the socio-technical mediation and perception of bodily intensity qualities from the practice of cycling itself. Conceptually, the article makes the innovative proposal to turn to the discourse of recent energetic sociology, which argues that sources of energy are interwoven with the social fabric and influence ways of thinking and acting. Using the concept of “expenditure” (George Bataille), the autoethnographic experience of the socio-technique of cycling is discussed and a comparison of different measuring instruments is made, with a focus on the juxtaposition of the heart rate sensor and the “powermeter”, a performance meter. The autoethnography is based on qualitative data analysis and active participation, which is carried out in an ethnographic narration and rendered analytically fruitful. Finally, the paper differentiates between modes of expenditure, elaborates the prominence of the value of energy efficiency, points out some practical shortcomings of this value and outlines the merits of an energy sociological perspective. This raises awareness of the prominence of non-efficient practices in digitalised sport.
... 6) to safeguard privacy, government/corporate surveillance, and commercial exploitation. There are limited means to allows individuals to control the confidentiality of their own urban mobility data; lapses in urban mobility and mobile phone location data inadvertently allows re-identification of people's whereabouts without their explicit knowledge (Gayomali 2014; Yin et al. 2015), while more recent examples of surveillance on Strava, a social network for athletes (Couture 2021) demonstrate how digital privacy is easily compromised. More alarmingly, there is an immense risk that unregulated access to such data can be used by governments and companies to deny services, discriminate, and in effect manipulate the free movement of citizens in their very own cities. ...
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Cities today are dynamic urban ecosystems with evolving physical, socio-cultural, and technological infrastructures. Many contestations arise from the effects of inequitable access and intersecting crises currently faced by cities, which may be amplified by the algorithmic and data-centric infrastructures being introduced in urban contexts. In this article, I argue for a critical lens into how inter-related urban technologies, big data and policies, constituted as Urban AI, offer both challenges and opportunities. I examine scenarios of contestations in urban mobility, defined broadly to include equitable access, movement, and liberty to engage with the socio-cultural, political, and urban fabric of cities. I anchor my arguments through a framework of rights, risks, and responsibilities for critically examining and configuring the roles, values and ethical implications for all stakeholders including human, AI and non-human entities within an urban ecosystem. As a way forward, I examine the European Commission’s proposed regulations on AI systems through an illustrative case study of an automated parking control system introduced by the City of Amsterdam. In moving beyond the city to broader urban ecosystems, I highlight the role of engaging Indigenous perspectives for designing and reconciling the implications of equitable and sustainable Urban AI ecosystems in the future.
This chapter focuses on how embodied mobilities such as commuting on the subway and recreational running and cycling contribute to the sense of place. If we understand the city as not just composed of static spaces (sites) but also of movements of its people, then it is imperative that we account for how space may be expressed as a function of embodied mobility. As we shall see, just as embodied mobilities engender alienation, they can also create a visual-spatial sense of community via recreational cycling and running.KeywordsCommutingMobilitiesMTRNon-placeSensory ethnographySubway
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Despite considerable growth in understanding of various aspects of sporting and exercise embodiment over the last decade, in-depth investigations of embodied affectual experiences in running remain limited. Furthermore, within the corpus of literature investigating pleasure and the hedonic dimension in running, much of this research has focused on experiences of pleasure in relation to performance and achievement, or on specific affective states, such as enjoyment, derived after completing a run. We directly address this gap in the qualitative literature on sporting and exercise embodiment by contributing novel insights on the mind-body pleasures of running via focusing analytic attention towards the pleasures recalled by runners as experienced during positive, rewarding running experiences. Applying conceptual insights drawn from sociological phenomenology, we analyse data from an in-depth, event-focused interview study with distance runners who reported positive, rewarding experiences in recent recreational runs. Through reflexive thematic analysis, we present findings in relation to three themes: (1) ‘running feels like it should’; (2) sensory engagements; and (3) time out. The study contributes fresh perspectives, both conceptually and in relation to data-collection approach, to a small literature on the lived experience of pleasure in sport, exercise and physical cultures.
Strava is the largest online social network for athletes. We used Strava’s big data to investigate how runners in the same virtual Strava club influenced each other’s running behavior. We hypothesized that receiving kudos on recorded activities would spur exercise rates, and that the running behavior of clubmates to whom ego gave kudos would serve as a motivational example. We focused on five different Strava clubs that functioned as a virtual extension of real-life Dutch running clubs with a total of 329 members. Using data on kudos and recorded activities, we constructed a longitudinal dataset of complete networks and behavior over 11 periods with a one-month time window. We tested our hypotheses using SIENA. We found that receiving kudos induced runners to run more and more often. Moreover, athletes tended to adjust their running behavior to that of their ‘kudos-friends’ (i.e., those to whom they gave kudos). Contrary to our expectation, kudos-friends who ran more and more often than ego were not the most influential. If anything, the reverse was true; athletes were more likely to come to resemble the running behavior of their kudos-friends who ran less and less often.
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Can data-driven innovations, working across an internet of connected things, personalize health insurance prices? The emergence of self-tracking technologies and their adoption and promotion in health insurance products has been characterized as a threat to solidaristic models of healthcare provision. If individual behaviour rather than group membership were to become the basis of risk assessment, the social, economic and political consequences would be far-reaching. It would disrupt the distributive, solidaristic character that is expressed within all health insurance schemes, even in those nominally designated as private or commercial. Personalized risk pricing is at odds with the infrastructures that presently define, regulate and deliver health insurance. Self-tracking can be readily imagined as an element in an ongoing bio-political redistribution of the burden of responsibility from the state to citizens but it is not clear that such a scenario could be delivered within existing individual private health insurance operational and regulatory infrastructures. In what can be gleaned from publicly available sources discussing pricing experience in the individual markets established by the Patient Protection and Affordable Care Act 2010 (ACA), widely known as ‘Obamacare’, it appears unlikely that it can provide the means to personalize price. Using the case of Oscar Health, a technology driven start-up trading in the ACA marketplaces, I explore the concepts, politics and infrastructures at work in health insurance markets.
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Young people’s engagement with digital health technologies is dominated by risk narratives. Yet, there are very limited understandings, from the perspectives of young people, about the health-related issues and opportunities generated by digital health technologies. This article presents new evidence on the types of health-related apps and devices young people find, select and use, and the reasons for their choices. Data were generated from a participatory mixed method design with 245 young people (age 13–18). The data were analysed using a content-led pedagogical framework. The data illustrate, vividly, young people’s agency in digital health contexts and the complexity and fluidity of young people’s decision-making. Schools, PE lessons and sport, as well as family members and peers, were powerful influencers on young people’s digital health-related knowledge and behaviours. It is argued that better understanding young people’s agency in digital health contexts offers important insights into developing effective health-related pedagogies.
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A Response to Colin Bennett's 'In Defence of Privacy'
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An international evidence-base demonstrates that healthy lifestyle digital technologies, like exergames, health-related mobile applications (‘apps’) and wearable health devices are being used more and more within educational settings. Despite this, there is a lack of in-depth empirical evidence on young people’s experiences and uses of healthy lifestyle technologies. In this article we focus on young people’s uses of a wearable health device – Fitbit – and the associated health app. Informed by the work of Foucault, the purpose is to investigate the surveillance, self-surveillance and resistance that occur by young people. One hundred 13–14 years olds (53 females, 47 males), from five physical education classes in two UK schools participated. Data were generated through 8 focus group interviews, and the nominal interview group technique was applied. Data were analyzed using key concepts from Foucault’s theoretical framework. The results demonstrated that, the daily 10,000 step and calorie burning targets set by the Fitbit device encouraged the young people to do more physical activity. Increases in physical activity occurred because of the self-surveillant practices promoted by the Fitbit through; (i) the monitoring and recording of steps and calories burned, and (ii) peer comparison (or monitoring). Surveillance and self-surveillance practices, however, were clearly connected to health equating to fitness and being ‘fit’ or not being ‘fat’. These narrow interpretations of health, equally, underpinned resistance. Daily step and calorie burning targets, (i) did not sustain young people’s engagement with the device beyond a few weeks, (ii) promoted negative feelings, and (iii) the device was resisted because it did not record physical activity accurately as part of young people’s daily lives. In turn, the young people resisted the educational value of the Fitbit and demonstrated a sceptical stance toward introducing health devices in school and physical education settings.
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This article develops and mobilises the concept of ‘mundane data’ as an analytical entry point for understanding Big Data. We call for in-depth investigation of the human experiences, routines, improvisations and accomplishments which implicate digital data in the flow of the everyday. We demonstrate the value of this approach through a discussion of our ethnographic research with self-tracking cycling commuters. We argue that such investigations are crucial in informing our understandings of how digital data become meaningful in mundane contexts of everyday life for two reasons: first because there is a gap in our understanding of the contingencies and specificities through which big digital data sets are produced, and second because designers and policy makers often seek to make interventions for change in everyday contexts through the presentation of mundane data to consumers but with little understanding of how people produce, experience and engage with these data.
The impact of the Quantified Self (QS) movement, or the digital quantification of the body for the purposes of self-betterment, on leisure has been well-established within the literature. Drawing on the experiences of ten women who self-track while running, this project extends the literature on running and place, and lived experiences of the QS, by considering the role of fitness tracking on embodiment and emplacement. First, I trouble the notion that running data is an objective replication of a runner’s activities, illustrating instead that fitness tracking is an accomplishment of human and non-human agencies and that this accomplishment does not always go according to the runner’s plan. Second, I complicate the idea that personal data collection is a disembodying act that turns visceral sensations into impersonal numbers. Instead, I argue that running data collection is often intertwined with visceral and experiential aspects of running, thus maintaining a connection between the body and the data that is collected on that body. In so doing, I contribute to digital leisure studies efforts to characterise the lived experiences of self-tracking, pointing in particular to the role of non-humans and place in those lived experiences.
The widespread use of Fitbits, Garmins and Apple Watches is emblematic of the ‘Quantified Self’ (QS) movement, where participants utilise digital self-tracking devices to generate a broad range of data on their health and fitness for the purposes of self-improvement. Gendered expectations for beauty and health have led to women becoming disproportionately represented amongst fitness tracker wearers, as weight loss and self-discipline for the purposes of beauty are often considered women’s endeavours. To examine the gendered ways in which wearable technologies are utilised in fitness practices, I look to ‘running interviews’ and semi-structured interviews with 10 women who identify as self-tracking runners to better apprehend the ways in which self-surveillance through a fitness tracking device is both accommodated and resisted. Drawing on a Foucauldian conceptual framework of surveillance, discipline and technologies of femininity, I describe four strategies of resistance to datafication: labelling some data as excessive, not tracking every run or every day, invoking one’s humanity and fallibility as a way of limiting disappointment from unfavourable data, and re-valuing feelings over data. While these self-trackers have undergone this process of problematisation and deemed this level of self-surveillance to be an important part of what they see as a healthy lifestyle, they do not fully accept practices of dataism, optimisation and technologies of femininity, entirely.
The fitness industry is experiencing a new boom characterized by the proliferation of interactive and customizable technology, from exercise-themed video games to smartphone apps to wearable fitness trackers. This new technology presents the possibility of boundless self-tracking, generating highly personalized data for self-assessment and for sharing among friends. While this may be beneficial - for example, in encouraging physical activity - the new fitness boom also raises important questions about the very nature of our relationship with technology. This is the first book to examine these questions through a critical scholarly lens. Addressing key themes such as consumer experience, gamification, and surveillance, Fitness, Technology and Society argues that fitness technologies - by 'datafying' the body and daily experience - are turning fitness into a constant pursuit. The book explores the origins of contemporary fitness technologies, considers their implications for consumers, producers, and for society in general, and reflects on what they suggest about the future of fitness experience. Casting new light on theories of technology and the body, this is fascinating reading for all those interested in physical cultural studies, technology, and the sociology of sport.