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An Unsupervised Approach to Identify Location Based on the Content of User’s Tweet History
16 references·1 citing·35 second hop
An Unsupervised Approach to Identify Location Based on the Content of User’s Tweet History (2014)An Unsupervised Approach to Identify Loca…A Multi-Indicator Approach for Geolocalization of Tweets (2021)A Multi-Indicator Approach fo…Where in the World Are You? Geolocation and Language Identification in Twitter (2014)Where in the World Are You? G…Where's @wally? (2013)Where's @wally?Geo-Location Estimation of Flickr Images: Social Web Based Enrichment (2012)Geo-Location Estimation of Fl…Finding your friends and following them to where you are (2012)Finding your friends and foll…Twitter mood predicts the stock market (2011)Twitter mood predicts the sto…Tweets from Justin Bieber's heart (2011)Tweets from Justin Bieber's h…Geotagging Tweets Using Their Content. (2011)Geotagging Tweets Using Their…Geo‐parsing Messages from Microtext (2011)Geo‐parsing Messages from Mic…"I'm eating a sandwich in Glasgow" (2011)"I'm eating a sandwich in Gla…You are where you tweet (2010)You are where you tweetPredicting Elections with Twitter: What 140 Characters Reveal about Political Sentiment (2010)Predicting Elections with Twi…Find me if you can (2010)Find me if you canYou Are Where You Edit: Locating Wikipedia Contributors through Edit Histories (2009)You Are Where You Edit: Locat…Mapping the world's photos (2009)Mapping the world's photosGeolocating Blogs From Their Textual Content (2009)Geolocating Blogs From Their …Evaluating residential location inference of twitter users at district level: focused on Seoul city (2016)Evaluating residential locati…The political blogosphere and the 2004 U.S. election (2005)The Psychological Meaning of Words: LIWC and Computerized Text Analysis Methods (2009)Birds of the Same Feather Tweet Together: Bayesian Ideal Point Estimation Using Twitter Data (2014)Network analysis reveals open forums and echo chambers in social media discussions of climate change (2015)The Development and Psychometric Properties of LIWC2015 (2015)Social media and loneliness: Why an Instagram picture may be worth more than a thousand Twitter words (2016)Exploiting innocuous activity for correlating users across sites (2013)Who, where, when and what (2013)Gaining insights from social media language: Methodologies and challenges. (2016)An Empirical Study of Geographic User Activity Patterns in Foursquare (2021)Reality mining: sensing complex social systems (2005)Limits of Predictability in Human Mobility (2010)Friendship and mobility (2011)Mining User Mobility Features for Next Place Prediction in Location-Based Services (2012)Revisiting User Mobility and Social Relationships in LBSNs: A Hypergraph Embedding Approach (2019)Measuring nominal scale agreement among many raters. (1971)Volunteered Geographic Information and Crowdsourcing Disaster Relief: A Case Study of the Haitian Earthquake (2010)Socializing in emergencies—A review of the use of social media in emergency situations (2015)Chatter on the red (2010)Microblogging during two natural hazards events (2010)Finding and assessing social media information sources in the context of journalism (2012)Tweeting is believing? (2012)The end of geography or the explosion of place? Conceptualizing space, place and information technology (1998)Human mobility: Models and applications (2018)Prospect Theory: An Analysis of Decision under Risk (1979)Prospect theory: An analysis of decision under risk (1988)Personality, Gender, and Age in the Language of Social Media: The Open-Vocabulary Approach (2013)Text as Data (2019)Online Social Networks: Threats and Solutions (2014)Processing Social Media Messages in Mass Emergency (2015)Exploring Millions of Footprints in Location Sharing Services (2021)Measuring human perceptions of a large-scale urban region using machine learning (2018)Hierarchical Discriminative Classification for Text-Based Geolocation (2014)Event classification and location prediction from tweets during disasters (2017)Mining location from social media: A systematic review (2018)
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References

  • 2011Twitter mood predicts the stock market5,204 cited
  • 2010Predicting Elections with Twitter: What 140 Characters Reveal about Political Sentiment2,649 cited
  • 2010You are where you tweet1,069 cited
  • 2009Mapping the world's photos782 cited
  • 2010Find me if you can705 cited
  • 2011Tweets from Justin Bieber's heart466 cited
  • 2012Finding your friends and following them to where you are343 cited
  • 2014Where in the World Are You? Geolocation and Language Identification in Twitter319 cited
  • 2011"I'm eating a sandwich in Glasgow"234 cited
  • 2021A Multi-Indicator Approach for Geolocalization of Tweets158 cited
  • 2011Geo‐parsing Messages from Microtext130 cited
  • 2013Where's @wally?119 cited
  • 2009You Are Where You Edit: Locating Wikipedia Contributors through Edit Histories55 cited
  • 2011Geotagging Tweets Using Their Content.44 cited
  • 2009Geolocating Blogs From Their Textual Content32 cited
  • 2012Geo-Location Estimation of Flickr Images: Social Web Based Enrichment25 cited

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Cited by

  • 2016Evaluating residential location inference of twitter users at district level: focused on Seoul city5 cited