Working through paradoxes: Transnational migrants’ urban learning tactics using locative technology

Locative technology use in urban spaces

The popularization of locative technology has led scholars to revisit the meaning of local spaces. Whereas early mobile communication research concentrated on social connectivity across geographic distance, implying “disconnection” from the local, recent literatures emphasize the significance of local spaces as sites of social and information exchange (Gordon & de Souza e Silva, 2011). Bilandzic and Foth (2012) proposed that locative technology creates a digital layer on top of the physical world, affording new social practices that would not be possible otherwise. Echoing this, de Souza e Silva (2013) argued that locative technology allows users to add digital information to locations, which can in turn influence the characteristics of locations and users’ mobility patterns. With mobile technology enabling the incorporation of a range of data on user activities, locative technology plays a constitutive role in conceptualizations of the local.

In this vein, a number of researchers have examined emerging patterns of locative technology use and their impact on spatial awareness and urban mobility. Humphreys (2008) investigated how Dodgeball users’ location sharing affects processes of social coordination. Studies on location-aware mobile games also showed that geotagging allows individuals to enhance their awareness of others’ proximity, creating mediated public spaces and engineering future courses of encounters (Licoppe & Guillot, 2006; Licoppe & Inada, 2010). Gaming elements of Foursquare also offer a lens through which users read their surroundings (e.g., a place to unlock a badge), which may alter their mobility patterns (Frith, 2013). In terms of urban awareness, Bilandzic, Foth, and De Luca (2008) found that location-based comments were viewed by newcomers as valuable information sources for exploring unfamiliar environments, suggesting locative technology may facilitate new means of social navigation. Humphreys and Liao (2011) also argued that mobile geotagging can build social familiarity with urban environments through communicating about places with others.

Another line of work focuses more on the interrelations between extant social/physical structures and emerging locative technology use. De Souza e Silva and Frith (2010) proposed that locative mobile social networks may construct a different spatial logic, facilitating relationships between users and spaces, while acknowledging that locative technology use is shaped by existing cultural, social, and economic contexts. Similarly, Sutko and de Souza e Silva (2011) elucidated tensions around the use of locative technology: whereas technology may challenge the traditional notion of urban sociability, it may not necessarily increase spatial awareness when the usage patterns still rely on established social norms. Frith (2014) also revealed that Foursquare provides affordances for coordination, even as this coordination is limited by extant social and geographical constraints. Given that scholars have pointed out the adoption of locative technology does not necessarily lead to enhanced urban awareness, we analyze sociotechnical practices of transnational migrants to generate an in-depth, nuanced understanding of the spatial and sensemaking roles of locative technology.

Transnational migrants and urban learning

Given our interest in locative technology in terms of becoming familiar with and gathering information about urban spaces among city newcomers, we draw on urban informatics scholarship related to migration. Foth, Choi, and Satchell (2011) defined urban informatics as “the study, design, and practice of urban experiences across different urban contexts that are created by new opportunities of real-time, ubiquitous technology and the augmentation that mediates the physical and digital layers of people networks and urban infrastructures” (n.p.). Locative technology is arguably the most representative example of real-time, ubiquitous technology that shapes both physical and virtual spatial interactions. In terms of everyday practices, locative technology is increasingly important in understanding urban information tasks.

Locative technology may complement a range of other technologies used by transnational migrants in their day-to-day lives as newcomers, both in preparation for moving and postmigration (for a review, see Caidi, Allard, & Quirke, 2010). Transnational migrants rely on social media to locate resources and expand social relationships, which may contribute to fostering social inclusion (Fisher, Durrance, & Bouch Hinton, 2004). Komito (2011) argued that migrants display increased dependence on the Internet as an information source; in particular, the use of social media platforms enables passive monitoring and ambient awareness of others’ activities, which may facilitate promoting migrants’ social capital and transnational mobility. Yet in terms of how this sense of inclusion relates to space, Lingel (2015) illustrated how city newcomers benefit from using locative technology to explore urban environments, while also noting that technological aids can result in tradeoffs between short-term convenience and long-term familiarity with city space.

As research on locative technology use among city newcomers is still nascent, this study provides a detailed understanding of how transnational migrants employ locative technology to glean various informational and social resources. To this end, we hone in on the experiences of city newcomers who can offer insights into the process of familiarizing new environments, which leads to the following research question: How do transnational city newcomers interact with locative technology to build knowledge of their urban surroundings? Given the increasing incorporation of locative technology into massively popular social media platforms like Facebook and Instagram, there is a pressing need to understand how individuals interact with locative technology to explore urban environments and share their location-related information with others. Responding to this call, we investigate locative technology use through a holistic analysis of practices, advantages, and drawbacks of mobile, locative technology.

Our approach to analyzing the sociospatial relationships surrounding locative technology is a multifaceted one, accounting for both benefits and drawbacks associated with this technology. Broadly speaking, we view technology and social practices as mutually constitutive, emerging in a relationship that is dialectic rather than deterministic in nature. With this approach to sociotechnical practices as a guiding lens, we delve into the use of locative technology among transnational migrants to capture contradictory experiences and practices. By identifying and analyzing tensions surrounding usage patterns and outcomes, we aim to offer a holistic yet dynamic account of the interactions between city migrants, locative technology, and urban environments.

Searching versus browsing

For many participants, locative technology was a primary information source for learning to navigate New York. Gina stated that she used Google Maps “almost every time I get out of unless I’m going to school or a place like that” even after almost 2 years living in the city. Among reasons for this degree of technological reliance on searching, two explanations emerged. First, many interviewees had few or no “native” friends able to provide first-hand knowledge about their new surroundings. Having an established social network can facilitate urban learning through being part of local activities or gaining access to local knowledge. Elaine’s remark, “I don’t need to use my phone to find a place in Chinatown [whereas I use it in other neighborhoods],” shows the role of social networks in an ironic way: she familiarized herself with the Chinese enclave much faster than other parts of New York, despite her job as an intern at a marketing agency that would seemingly provide a source of local knowledge. Other participants echoed her comments reflecting the impact of social embeddedness and cultural resources on urban learning.

Second, several participants viewed their smartphones as a way of concealing their lack of spatial familiarity. As Sue illustrates:

I don’t know if I’m comfortable with the paper map anymore because that’s kind of a sign that I’m a tourist. So to hide that, I just use my smartphone to pretend [that I am] the native person in that area. . . . I don’t want to be seen as a tourist in any city, that’s why . . . I rely on mobile technology. And avoiding asking some person, any person on the spot.

Since smartphone use is not considered a noticeable sign of being a tourist (as opposed to using guidebooks or asking others), Sue deployed locative technology both to find information and to hide her lack of spatial knowledge as well as her status as a newcomer. A sociotechnical complexity emerges here in that participants viewed emic city knowledge of streets and neighborhoods as highly desirable, even as their continued reliance on locative technology to navigate the city ultimately meant that they were less likely to develop an ingrained sense of familiarity with city space, which we clarify through a comparison between searching and browsing.

In traditional information theory, searching and browsing refer to distinct approaches in learning. The former refers to a query presented by a user to an information system, which returns results that can be evaluated in terms of a specific query; the latter refers to an approach in which the user encounters a system that is evaluated for information resources as one progresses through the system (Bates, 1989). In participants’ descriptions of their locative technology use, we noted a marked tendency toward searching, where participants valued its efficiency, even as this focus on efficiency reduces their engagement with city spaces. Gina’s comment encapsulates participants’ interest in time-saving and immediacy: “Even [if it’s] just 5 minute walking distance, I’m like, what’s the most efficient way to get there—let’s ask Google Maps.” Livy also repeatedly referred to her use of locative technology mentioning terms like “convenience,” “the fastest way” and “time-saving.” Livy further explained that, thanks to Yelp, she frequently made judgment calls on particular places without actually visiting, and other participants echoed this report of either visiting or avoiding venues based on locative technology search results. Locative technology thus may deprive city newcomers of an opportunity to explore the neighborhood as they preemptively exclude certain places from the range of their choices. Dev’s search tactic next illustrates how locative technology use can shape decisions on where to go:

I open Yelp, and type in what I’m looking for, and choose a filter. Distance as the first thing, and the second thing that I put would be the rating. Generally I go to places over four stars. The next step would be finding it on the map to get the directions.

As mentioned in the previous lines, certain places are “filtered out” as his search goals are geared towards proximity and popularity, in that Dev used preset cut points to define search criteria for distance (e.g., two blocks) and rating (e.g., four stars). This practice allowed him to find quickly a desirable, nearby venue, determined by automatic suggestions and crowdsourced information; and, in turn, locative technology guides him there with a display of the most effective route. For Dev, who moved to New York hoping to start a career as a filmmaker, finding a place for a quick bite between tight filming schedules was crucial.

Although locative technology offers an on-site solution for given circumstances, it does not necessarily enhance awareness of urban environments in the long run. Dev further elaborated on his routines:

[B]ecause I know that I can just quickly find out a place, I’m looking down on my phone and walking, so I look on my phone a lot more than looking around the city. I am just looking on the screen. So maybe I just look on the screen towards the place because of Yelp. I might pass some places that I could’ve found, but I just miss them.

This quote captures the paradoxical nature of technological aid. Although Dev can find a place in real-time, he loses opportunities for wandering or “browsing” the neighborhood, to the extent that he may not recognize the street that he just walked along. Emphasizing the degree of dependence on locative technology, Young described, “I normally just follow the arrows. Also, I think it’s so cool that you can see yourself walking, you know? . . . I just leave it on and look at it.” Interestingly, neither of them were able to recall specific places that they had discovered through locative technology, suggesting that those applications function as temporary guidance, rather than long-term awareness. The following comment by Gina succinctly compares experiences of exploring the city with and without a smartphone:

[Google Maps is] useful, so you kind of just don’t get lost, but sometimes I forget even to look around. When I was here actually 2 years ago, before having a smartphone and I was just a tourist, I literally walked from Midtown all the way to the Met. . . . And I found my way around.

Gina’s description illustrates contrasting approaches to urban learning. Whereas the continued ability to locate herself on mobile map had effectively eliminated Gina’s fear of lostness, she noted that the very same function hinders her from browsing the city, which had previously helped her create her own cognitive map of the area (see Frith, 2015). Although locative technology plays a central role in participants’ information seeking, their stories also demonstrate complex outcomes of locative technology use, reflecting tradeoffs between task-oriented searching and potential opportunities for browsing.

Awareness versus surveillance

A second theme that emerged from participants’ accounts revolves around a shared interest in enhancing awareness of urban activities. In addition to active searching, passive monitoring of location-aware applications facilitates vicarious learning about the city. Check-ins and geotagging information on social media, along with status updates, provided a proxy resource for city newcomers to extend their urban information seeking through the everyday routines evident within their networks. Especially given fast-changing cityscapes, population density, and the variety of local activities in New York, participants were keen to develop a repertoire of distinctive local establishments, as well as keep abreast of their friends’ city lives and urban activities. Participants reported sharing their local visits, newly found places, and social gatherings through social media using geotagging and people-tagging features. By sharing (and monitoring) popular spots and events within their networks, they try to achieve “being in the know,” which cannot be supported by individual mobile searching.

Participants valued highly local information about the city shared through social media. Elly argued that “there are so many underground places in New York,” and friends’ check-ins were vital for locating such spots, where the output of keyword-based search engine queries were insufficient for a richer understanding of city life. Sue referenced having “a real New Yorker,” among her Korean friends, whose check-ins on Foursquare and Facebook informed her of “hip places.” Contrary to other locative technology use, participants’ descriptions about check-ins were often associated with the notion of “coolness,” which indicates a unique role of check-ins in urban learning and spatial characterization. For some participants who often hang out in New York, check-ins and people tagging on Facebook have become popular ways of sharing their urban activities; in turn, those posts may imply their connections to “cool places” or “insider information.” When Sue noted, “I don’t check in at Starbucks because it’s uncool,” she points to a practice of selectively sharing check-ins based on the perceived association between places and status. Taking this status-based association with venues to an extreme, some participants referenced “Foursquare jumpers” who falsely check-in to pretend that they are in a cool place or event. Since check-in and geotagging features are integrated into social media platforms, participants (and their peers) shared specific places and local events that may appeal to their networks. The perceived notion of coolness shapes the impression of places (see Frith, 2015); in turn, check-ins have become a channel for urban information seeking particularly for the places well-regarded among their peers.

Constant sharing and monitoring practices, however, elicit tensions about surveillance. Although participants displayed varying levels of self-disclosure on social media, everyone expressed wariness of the potentiality for surveillance. Ironically, this anxiety about surveillance led to some hesitation or even refusal to sharing locations, even as they benefitted from sharing location information. Elly, who actively checks-in on Foursquare, explained that she never did the same on Facebook because “everybody is there [Facebook] . . . But here [Foursquare], it’s a lot less people. It’s more selective. They’re real friends.” Monitoring by a wider social circle discouraged her from posting her location on Facebook, despite the fact that location sharing with far-flung networks facilitates urban learning.

Because participants were aware that they are situated within a pervasive, real-time social stream, they strategically chose what to share depending on platforms, networks, and social situations. Related to issues of assigning status to check-ins, Milena was very cautious about location sharing. She could check-in at a park “because it was an innocent thing that I don’t feel like I’m going to show off anything, because the park is free, and I just want them to know that me and my brother were together.” In this case, she was concerned about how her friends in the home country would interpret her check-ins since she did not want to “show off” about living in New York. Since participants recognized being watched by different social networks, location sharing heightened concerns of impression management as shaped by not only their own posts but also the locations they documented. Given this possibility, participants have developed their own disclosure tactics ranging from selective disclosure to complete nondisclosure, affecting the extent of sharing spatial information.

Credibility/trust versus distrust

Even when participants already knew a venue’s location, they used locative technology to attain additional information (e.g., dress codes or price range), drawing on different layers of information such as comments, likes, tips, and reviews attached to check-ins. However, participants’ evaluations of credibility varied by their perceptions of locality, which could alternately refer to being a local in the current place of residence or being a local from one’s country of origin.

Like other forms of information, participants had their own means of assessing credibility. Source credibility is often structured by previous experiences and social assumptions (Tseng & Fogg, 1999; Wathen & Burkell, 2002), and in the case of transnational newcomers, the fact that they are not city natives affects perceived credibility. Specifically, participants’ general perceptions that most reviews are written by New York natives affected credibility in a contrasting way: insider information from city natives versus unreliable information from nonexperts. When participants determine the authors to be city natives, reviews are viewed as trustworthy. As Livy argued:

I guess usually the most popular ones come up first on the applications—those ones that have best reviews. And you can tell, from the reviews, whether people are from New York or they’re visiting New York. Or you can see something like “this is my favorite place in the neighborhood.” So I think, by the reviews, you can tell if it is popular among New Yorkers or not.

For Livy, knowing about specific places reputable among New Yorkers helps her determine optimal places nearby, because she views city natives as the most knowledgeable source of local information. In a contrasting scenario, other participants distrusted the information listed on location-aware applications for the very same reason, namely that people from the US are ill-equipped to comment on non-US-based cuisine or fashion. Young’s account demonstrates reasons for rejecting their reviews:

I think most Yelp users are American, right? Sometimes we have different tastes, so comments might not be so similar to our choices. Weibo is more reliable. Sometimes the posts are about specialties, Chinese flavors . . . they’ve never had that kind of food before, so their comments are not correct information about whether it is a similar taste to Chinese food.

The perceived lack of expertise prevented some participants from acting on information retrieved through locative technology, preferring to consult friends with shared tastes and interests from their country of origin. Although participants were concerned with building a deeper knowledge about their surroundings, trust in the information was not wholesale, reflecting an assessment of credibility based on shifting evaluations of locality.

In addition, interviews pointed to another tension regarding perceptions of information credibility: trustworthy information from friends versus nontrustworthy information from strangers. Some mobile applications, such as Foursquare, display friends’ activities (e.g., visiting frequencies and likes) next to the location information. This type of information may not be posted by their friends per se; rather, it is collective information determined algorithmically. Yet this information can convey a meaning similar to the information relayed by friends, as Elly illustrated:

I think Foursquare tailors what you like. It’s like more personalized . . . You can see where your friends are. Sometimes I don’t know where I should go, so I type “restaurants” there, and they give me suggestions because “your friends have been here three times.” So you can see their activities, so I’m like, “oh, okay, let me check out this place if they like it.” . . . I feel like it’s a friends’ suggestion.

When location information incorporates data about activities of one’s networks, credibility can increase as it is viewed as reflecting the preferences of one’s friends. Although algorithms may not ensure accuracy or representability, location information accompanied by friends’ activity logs can enhance participants’ perceived trustworthiness of the source, and in turn, of the information. In contrast, however, when they do not have “friends” on those applications, participants picture the reviewers as strangers who may upload false or biased information.

There’s a lot of fake reviews there [Yelp], right? Not really trust [worthy], but we go there anyway? . . . Because sometimes people just put bad reviews for, or overly good reviews for something, just to, you know, divert people or whatever. (Cathy)

Although user-generated content on mobile applications may include useful information about urban space, some participants displayed lower levels of trust in terms of the impartiality and goodwill of reviewers, citing the possibility of incorrect or partial information. Participants with higher levels of trust, however, rely more on locative technology to collect diverse information about places. Participants’ varying perceptions about information credibility, shaped by very different scales of locality, affect their information acceptance, use, and evaluation, which in turn shape ways of urban learning.

Ambivalent outcomes of locative technology

Robey and Boudreau (1999) suggested a logic of opposition, rather than a logic of enabling (or determination), as a way to theorize consequences of technology use that may promote or hinder change. The findings of this study suggest that locative technology use has paradoxical implications in the sense that the same functions can both facilitate and hamper individuals’ engagement with unfamiliar environments. Paradoxes emerge when “one calls for or carries out actions that are in opposition to the very goal(s) one is trying to accomplish” (Stohl & Cheney, 2001, p. 354). When users’ interactions with urban spaces are mediated through locative technology, they create new ways of information seeking that may also yield conflicting outcomes. For instance, when users self-track their location on their smartphone screen to get to a new place, they may narrow or dull engagement with their urban surroundings, even as locative technology is intended to assist in navigating city space. Several participants voiced concerns of a tradeoff in locative technology use between short-term information related to a route or destination and long-term familiarity with surroundings, the result of steadily accruing information via casual observance of surroundings. Wandering and looking around can lead to a more comprehensive understanding of urban environments, as people gain knowledge about spatial relations through observations (Lingel, 2011), compared with relying on “shortcuts” offered by locative technology. Indeed, the process of creating cognitive maps includes active encoding and retrieval of spatial information (Ozkul & Gauntlett, 2014), a process that may be hampered by heavy reliance on locative technology (Frith, 2015). These issues are likely not limited to transnational migrants, but rather urban newcomers who are intra- as well as international. Being new in a neighborhood always requires a process of sensemaking; in terms of how locative technology plays a role in this process, the crucial tradeoff here is in terms of short-term versus long-term objectives of familiarity.

Similarly, another tradeoff emerged around pressures to reveal versus pressures to conceal (Petronio, 2002). Despite the prevalence of sharing locative data, all participants expressed privacy concerns. As participants became increasingly aware of the pervasive and persistent nature of social media (Treem & Leonardi, 2012), several attempted to reduce others’ awareness on their activities by selectively sharing their check-ins, which may in turn limit others’ knowledge of urban activities. Here the tradeoff that takes shape pits the individual desire to maintain control over flows of personal data against the collective interest in accruing as many data points as possible. In this case, stakes may be somewhat divergent for different experiences of migration. Without wanting to essentialize cultural norms as universal to a particular nation, cultural differences certainly matter when it comes to norms of disclosure and privacy, with important consequences for crowdsourced data. When participants describe shifting levels of comfort with documenting their everyday lives (including location) via social media, these shifts are partly tied to how their spatial movements are read by a transnational audience. This is not to say that someone moving from, say, a rural area in California to Jackson Heights in Queens would not experience similar reflexivity in how to communicate her everyday life to her online social network, only that these experiences of online presentation as they relate to space are inflected with cultural and linguistic differences, which should be taken up more explicitly in future research.

In addition, participants’ accounts on locative technology use provide a useful starting point for discussions on the growing power of algorithms in shaping individuals’ information-gathering and decision-making processes. A host of information on locative technology—search results (often retrieved on site for real-time information seeking), rankings, friends’ activity logs, recommended places, as well as suggested deals and discounts—is organized by specific algorithms that are designed to guide people’s decision making. These algorithms, which classify or filter the information about certain locations and users, may help individuals locate useful information, yet they also prioritize particular information, orienting users to a certain direction. Some participants described checking in at certain places because of suggested deals or discounts, indicating the influence of algorithms on consumer decisions. Our data illustrate how location information and search results are selectively delivered and how decisions are shaped by predetermined filters. Although filters arguably provide a convenient way to cull out subpar places especially when users do not have knowledge about their surroundings, filtering also relies on arbitrary criteria such as auto-set distance. These algorithms are neither transparent nor directly alterable, meaning that even if users are aware of these technical interventions, they are neither able to see the specific factors shaping the results of a query nor directly request that those factors be altered. As Introna and Nissenbaum (2000) argued, search engines systematically give prominence to certain sites at the expense of others. Search functions on locative technology operate in a similar way that may narrow the access to information (see Pariser, 2011). These dual outcomes of algorithms should be further investigated to shed light on paradoxical relationships between the role of algorithms and human information behaviors.

Mobile technology and urban mobility

Smartphones operate as an intimate interface that guides the exploration of urban spaces; for transnational newcomers who lack alternate means of acquainting themselves with their surroundings, smartphones offer particularly advantageous means of orienting themselves, finding directions, and discovering new places. This study, offering a granular understanding of locative technology use for urban learning among migrants, lays groundwork for future research on the role of mobile technology in urban information seeking. Specifically, locative technology use can be understood in relation to implications for urban mobility. Wood and Graham (2006) proposed the idea of “automatic sorting of mobilities” orchestrated by technologies and codes, where technological systems are used to automate flows and manage boundaries that are permeable only to certain groups of people. Although their work concentrates mainly on technologies directly associated with traffic, such as road systems or Internet routers, their idea can be extended to the context of mobile technology use. Those who own a smartphone may have differential mobilities compared with others; for instance, Google Maps provide selected geodesic routes based on real-time data, which in turn affects user mobility. Such technology operates drawing on critical, time-sensitive information such as traffic conditions, accidents information, or road construction situations so that users can obtain this type of information in real time while on the move. Also, a number of locative mobile applications are accompanied by navigation functions that incorporate real-time data and directly guide one’s interactions with urban environments. In this scenario, locative technology functions as a passage to enhanced mobility.

From this perspective, having access to smartphones and various location-aware applications is regarded as a privilege that secures differential mobilities. This divide is tied to new types of urban sociability, mobility, and exclusion, leading to a new form of splintered urbanism (Frith, 2012; Graham & Marvin, 2001). It is thus crucial to examine how this differential access serves as a means of limiting mobilities of certain groups or segregating urban spaces. However, the discussions on mobile technology use and urban mobility needs to be further advanced—as noted in our findings, even when users are able to utilize locative technology fluently, their spatial interactions are still shaped by varied features and algorithms. The implications of locative technology use for urban information seeking and mobility should be examined further to generate in-depth knowledge of how one’s interactions with technological systems can engineer mobility differently.

Limitations and future directions

We acknowledge that our study has limitations, as is the case with any study. We focused on a specific population of young and educated transnational migrants living in an urban area. As such, this study has an emphasis on urban environments rather than rural, and our participant pool, although ethnically diverse, was homogenous in terms of socioeconomic class. This is not to say that participants were affluent: many were living on internships, student stipends, and low/mid-range salaries. Although by no means representative of undocumented workers in the informal economy, neither were participants elite HB1 visa holders with high-income, high-status jobs. Given that our analysis concentrated on issues of leveraging mobile technologies to learn about their surroundings, we feel that our analysis draws on an appropriate sample that reveals insights into sensemaking that span a range of transnational experiences.

With these limitations in mind, we call for future research along three axes. First, investigating information-seeking practices by transnational migrants who do not own a smartphone may provide significant insight into differential mobilities among various groups. Also, examining differences in locative technology use across various socioeconomic backgrounds and ethnicities can help us understand how different populations develop their own urban learning tactics, depending on differential access and resources. Second, future studies could take a comparative approach, analyzing differences in spatial relationships and technology use between city newcomers and natives, allowing for a narrower consideration of reliability and status in terms of describing and representing city space. This approach will elucidate which factors become more salient in a specific urban information-seeking context. Finally, future studies may take a closer look into the role of algorithms in urban information seeking to capture its growing impact on human information behavior. As “search engine bias” that skews search results can affect information seeking and retrieval (Goldman, 2005), future research may examine what kinds of biases exist in locative technology and how they shape urban learning processes. In aggregate, pursuing these goals in the future, we hope to contribute to a holistic understanding of complex relationships between technological systems, users, and urban environments.