2018
DOI: 10.1007/s11528-018-0313-6
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Tweet, and We Shall Find: Using Digital Methods to Locate Participants in Educational Hashtags

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Cited by 13 publications
(13 citation statements)
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References 17 publications
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“…We used the geographical location of each individual in the networks to assign the adoption status of each individual's state as a variable to each individual with this data available. To identify the location of participants, we access the location field from each individual's profile, which has been shown to lead to accurate or approximate results for around 80% of Twitter participants (Greenhalgh, Staudt Willet, Rosenberg, & Koehler, 2018). We then used the Google Maps API to geocode the participants' location.…”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…We used the geographical location of each individual in the networks to assign the adoption status of each individual's state as a variable to each individual with this data available. To identify the location of participants, we access the location field from each individual's profile, which has been shown to lead to accurate or approximate results for around 80% of Twitter participants (Greenhalgh, Staudt Willet, Rosenberg, & Koehler, 2018). We then used the Google Maps API to geocode the participants' location.…”
Section: Methodsmentioning
confidence: 99%
“…We considered Early NGSS‐aligned and Late NGSS‐aligned to be the adoption of NGSS‐ aligned standards (but not the official NGSS) for those same periods. Because of the uncertainty inherent to geocoding (Greenhalgh et al, 2018), we used this measure only in a descriptive manner and to understand the distribution of participants' locations, rather than as independent variables in analyses.…”
Section: Methodsmentioning
confidence: 99%
“…To understand the forms of social and human capital available through Twitter, we first geocoded individuals' self-reported locations (from Twitter profiles) using the mapsapi R package [33]. We could obtain locations for 194 of the individuals who participated in #mathathome using a geocoding method determined to be sufficiently accurate for identifying the state (and therefore the country) participants are from [34]. We created a map with the geocodes of users' locations (see details in Results), and then used this map to aid our interpretation of the geographic location of active participants, as well as these users' professional roles.…”
Section: Quantitative Analysis Of Tweetsmentioning
confidence: 99%
“…The amount of research related to social media in teaching and learning within higher education is exhaustive (Bista, 2015;DiVall & Kirwin, 2012;Xi, Hui, de Pablos, Lytras, & Yongqiang, 2016;Lin, Hoffman, & Borengasser, 2013). Researchers have focused on understanding: how different platforms can be used in varying learning experiences (Alzouebi & Isakovic, 2014;Bista, 2015;DiVall & Kirwin, 2012;Evans, 2014;Tuten & Marks, 2012), how and when informal learning can occur within these environments (Lin et al, 2013;Tess, 2013), how social media can serve to enhance professional development (Luo, Sickel, & Cheng, 2017;Romero-Hall, 2017), the types of content and connections that occur when using social media for teaching and learning (Guidry & Pasquini, 2013), the culture-specific parameters that have an effect on learning experiences with social media communities (Atkins, Koroluk, & Stranach, 2017), the locations of the knowledge sharing activities (Greenhalgh, Staudt Willet, Rosenberg, & Koehler, 2018), the learning experiences that field-specific students encounter when using social media (Evans, 2014;Myers, Jeffery, Nimmagadda, Werthman, & Jordan, 2015;Pham, 2014; 15 Spallek et al, 2015) and the tensions and uncertainties that scholars who use social media experience themselves (Kimmons & Veletsianos, 2016;Veletsianos & Stewart, 2016), amongst other topics.…”
Section: Social Media In Higher Educationmentioning
confidence: 99%