Tweets on the Road

Lenormand, Maxime; Tugores, Antònia; Colet, Pere; Ramasco, José J.

doi:10.1371/journal.pone.0105407

Cited by 49 publications

(37 citation statements)

References 33 publications

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“…Further research has been conducted on utilizing Twitter in traffic management. This can be found in 14% of reviewed studies (Kosala and Adi 2012, Wakamiya and Lee 2012, Lenormand et al 2014. Another area which seems to be quite popular is research on Twitter data for disease/ health management adding up to another 5% of the reviewed studies (Lampos and Cristianini 2010, Veloso and Ferraz 2011, Sofean and Smith 2012.…”

Section: Application Domains Of Social Media Analysesmentioning

confidence: 98%

Research on social media feeds – A GIScience perspective

Steiger¹,

Westerholt²,

Zipf³

2016

European Handbook of Crowdsourced Geographic Information

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Section: Application Domains Of Social Media Analysesmentioning

confidence: 98%

Research on social media feeds – A GIScience perspective

Steiger¹,

Westerholt²,

Zipf³

2016

European Handbook of Crowdsourced Geographic Information

View full text Add to dashboard Cite

“…This is oftentimes used as data basis for movement analysis and activity detection. Examples of these data sources include sport and fitness apps, such as Endomondo or Strava [22]; photo-sharing applications, such as Flickr or Panoramio [23][24][25]; business apps, such as Foursquare/Swarm [26]; or social media platforms, such as Twitter [17,27]. Tweets contain besides the message itself a rich set of metadata about the tweet (e.g., creation date) and the user (e.g., set language).…”

Section: Related Workmentioning

confidence: 99%

Analyzing Refugee Migration Patterns Using Geo-tagged Tweets

Hübl

Cvetojevic

Hochmair

et al. 2017

IJGI

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Abstract:Over the past few years, analysts have begun to materialize the "Citizen as Sensors" principle by analyzing human movements, trends and opinions, as well as the occurrence of events from tweets. This study aims to use geo-tagged tweets to identify and visualize refugee migration patterns from the Middle East and Northern Africa to Europe during the initial surge of refugees aiming for Europe in 2015, which was caused by war and political and economic instability in those regions. The focus of this study is on exploratory data analysis, which includes refugee trajectory extraction and aggregation as well as the detection of topical clusters along migration routes using the V-Analytics toolkit. Results suggest that only few refugees use Twitter, limiting the number of extracted travel trajectories to Europe. Iterative exploration of filter parameters, dynamic result mapping, and content analysis were essential for the refinement of trajectory extraction and cluster detection. Whereas trajectory extraction suffers from data scarcity, hashtag-based topical clustering draws a clearer picture about general refugee routes and is able to find geographic areas of high tweet activities on refugee related topics. Identified spatio-temporal clusters can complement migration flow data published by international authorities, which typically come at the aggregated (e.g., national) level. The paper concludes with suggestions to address the scarcity of geo-tagged tweets in order to obtain more detailed results on refugee migration patterns.

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“…Backstrom, Sun, and Marlow (2010) developed an algorithm to identify the location of individuals based on Facebook networks among friends. Lenormand, Tugores, Colet, and Ramasco (2014) analyzed tweets along highway and railway segments in 39 European countries to illustrate variations in social media use in association with these transportation modes. Some researchers have explored social media data in tourism and hospitality services industries (Miguens, Baggio, & Costa, 2008;Verma, Stock, & McCarthy, 2012).…”

Section: Background and Literature Reviewmentioning

confidence: 99%

Photos, tweets, and trails: Are social media proxies for urban trail use?

Wood

Fisher

et al. 2017

JTLU

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Decision makers need information on the use of, and demand for, public recreation and transportation facilities. Innovations in monitoring technologies and diffusion of social media enable new approaches to estimation of demand. We assess the feasibility of using geo-tagged photographs uploaded to the image-sharing website Flickr and tweets from Twitter as proxy measures for urban trail use. We summarize geo-tagged Flickr uploads and tweets along 80 one-mile segments of the multiuse trail network in Minneapolis, Minnesota, and correlate results with previously published estimates of annual average daily trail traffic derived from infrared trail monitors. Although heat maps of Flickr images and tweets show some similarities with maps of variation in trail traffic, the correlation between photographs and trail traffic is moderately weak (0.43), and there is no meaningful statistical correlation between tweets and trail traffic. Use of a simple log-log bivariate regression to estimate trail traffic from photographs results in relatively high error. The predictor variables included in published demand models for the same trails explain roughly the same amount of variation in photo-derived use, but some of the neighborhood socio-demographic and built-environment independent variables have different effects. Taken together, these findings show that both Flickr images and tweets have limitations as proxies for demand for urban trails, and that neither can be used to develop valid, reliable estimates of trail use. These results differ from previously published results that indicate social media may be useful in assessing relative demand for recreational destinations. This difference may be because urban trails are used for multiple purposes, including routine commuting and shopping, and that trail users are less inclined to use social media on trips for these purposes.

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Tweets on the Road

Cited by 49 publications

References 33 publications

Research on social media feeds – A GIScience perspective

Research on social media feeds – A GIScience perspective

Analyzing Refugee Migration Patterns Using Geo-tagged Tweets

Photos, tweets, and trails: Are social media proxies for urban trail use?

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