Tweets from Justin Bieber's heart: the dynamics of the location field in user profiles

By Brent J. Hecht, Lichan Hong, Bongwon Suh, Ed H. Chi. 2011

576 citations recorded by the source corpus.

Subfields: Geography, Planning and Development, Statistical and Nonlinear Physics, Transportation, Natural Language Processing

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Citations in the corpus

YFCC100M (2015, methodology): “Even understanding styles and habits have been used to reverse lookup authors online [10].”
#Earthquake: Twitter as a Distributed Sensor System (2013, background): “…of GPS-equipped smartphones, and to cultural acceptance of the location information option in Twitter (Java et al. 2009, Miller and Wortham 2010, Hecht et al. 2011) Twitter users in their study provided some location information in the corresponding entry of their profiles (either coordinates…”
Twitter as Data (2018, background): “, 2013) to 66% (Hecht et al., 2011) of tweets have location information, the vast majority of which are at the city level.”
Beyond Trending Topics: Real-World Event Identification on Twitter (2011, background): “While the location as reported by Twitter users is not always accurate, it does provide a reliable approximation [11].”
Socio-Spatial Properties of Online Location-Based Social Networks (2011, background): “Then, user location information in these services is often more accurate than text-based descriptions usually available in other online systems (Hecht et al. 2011), as it is acquired through sensing devices whenever users willingly check-in, that is when they share with their friends information…”
OMG, I Have to Tweet that! A Study of Factors that Influence Tweet Rates (2012, background): “Unfortunately, the user-provided profile locations are in general not easily interpretable (Hecht et al. 2011).”
Everyone's Invited: A New Paradigm for Evaluation on Non-Transferable Datasets (2015, background): “For example, less than 1% of Twitter posts come with GPS locations (Hecht et al. 2011).”
Web Data Extraction, Applications and Techniques: A Survey (2012, background): “For instance, [59] provided an approach to finding user location on the basis of user tweets.”
The Effect of Population and "Structural" Biases on Social Media-based Algorithms: A Case Study in Geolocation Inference Across the Urban-Rural Spectrum (2017, methodology): “Priedhorsky [6,27,37,43,52,53]) while Jurgens’ is representative of network-based approaches (e.g., [3,10,33,45,54]).”
We know what @you #tag: does the dual role affect hashtag adoption? (2012, methodology): “Hecht et al. [17] predicted location information through users’ tweets.”
The Twitter of Babel: Mapping World Languages through Microblogging Platforms (2012, background): “While the research community is on a continuous quest to understand how to mine and geocode this data, doing so brings about many challenges [33].”
Semi-supervised User Geolocation via Graph Convolutional Networks (2018, background): “…information, and have to rely on public sources of geolocation information such as the proﬁle location ﬁeld, which is noisy and difﬁcult to map to a location (Hecht et al., 2011), or geotagged tweets, which are publicly available for only 1% of tweets (Cheng et al., 2010; Morstat-ter et al., 2013).”
Exploring Millions of Footprints in Location Sharing Services (2011, background): “User behavior with regard to the location field in Twitter user profiles has been studied in (Hecht et al. 2011).”
Population Bias in Geotagged Tweets (2015, background): “However, these findings come from interpretations of distributions and county-level cartograms, rather than from statistical testing, and they rely on the user-defined 'location' field, which has been shown to have many inconsistencies (Graham, Hale, and Gaffney 2014; Hecht et al. 2011).”
Tweeting is believing?: understanding microblog credibility perceptions (2012, background): “Maintaining a topical focus also increases credibility, as does geographic closeness between the author and tweet topic, so users tweeting on geographically-specific events should enable locationstamping on their mobile devices and/or update their bio to accurately identify location, which is often ”