2022
DOI: 10.1080/09654313.2022.2108312
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Revealing mobilities of people to understand cross-border regions: insights from Luxembourg using social media data

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Cited by 6 publications
(5 citation statements)
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“…By focusing on individuals’ subjective apprehension of time and heterogeneous border-crossings, mobile social media reconstructs the effect of “time-space compression” (Harvey, 1989, p. 240) that transcends spatial and temporal boundaries and thereby changes the transnational flow of migration (Chang & Gomes, 2020; Järv et al, 2022; Ling & Campbell, 2009). Accordingly, the border-crossing process of migrant students is not always homogeneous and symmetrical in spatial and temporal scales.…”
Section: Discussionmentioning
confidence: 99%
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“…By focusing on individuals’ subjective apprehension of time and heterogeneous border-crossings, mobile social media reconstructs the effect of “time-space compression” (Harvey, 1989, p. 240) that transcends spatial and temporal boundaries and thereby changes the transnational flow of migration (Chang & Gomes, 2020; Järv et al, 2022; Ling & Campbell, 2009). Accordingly, the border-crossing process of migrant students is not always homogeneous and symmetrical in spatial and temporal scales.…”
Section: Discussionmentioning
confidence: 99%
“…Recent research on mobile media and migration has captured the affordances of smartphones, mobile technologies, and mobile social media that provide migrants with homogenous space-time mobilities (e.g., Georgiou & Leurs, 2022; Järv et al, 2022; Xie, 2021), but little attention has been paid to the complicated spatial-temporal mobility landscape (re)constituted by mobile social media. On the one hand, mobile use of social media supplements migrants’ physical mobility based on its portability, locatability, and multimediality (Ling & Campbell, 2009; Marvin, 2013; Schrock, 2015), as smartphones are easy to carry and allow migrants to “virtually engage with physical environments through GPS tracking and can be used synchronously with other activities and applications” (Kuru et al, 2017, p. 104).…”
Section: Spatial-temporal Mobility In Mobile Social Mediamentioning
confidence: 99%
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“…Although qualitative analysis can reveal the underlying influencing factors of CBM, without quantitative analysis involving relatively large sample sizes, it often fails to test statistical relationships between the influencing factors and CBM, let alone the causality between them. Current studies on CBM based on quantitative analysis include descriptive statistics relating to mobility types or border crossers ( 11 ). These studies thus contribute to an evidence-based understanding of the occurrence of CBM and its health effects.…”
Section: Introductionmentioning
confidence: 99%