Race, Religion and the City: Twitter Word Frequency Patterns Reveal Dominant Demographic Dimensions in the United States
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József Stéger | Gábor Vattay | Eszter Bokányi | Dániel Kondor | István Csabai | László Dobos | Tamás Sebők
[1] Filippo Menczer,et al. Traveling trends: social butterflies or frequent fliers? , 2013, COSN '13.
[2] A. Tatem,et al. Dynamic population mapping using mobile phone data , 2014, Proceedings of the National Academy of Sciences.
[3] János Szüle,et al. Spatial Fingerprints of Community Structure in Human Interaction Network for an Extensive Set of Large-Scale Regions , 2015, PloS one.
[4] Manuel Cebrián,et al. Social Media Fingerprints of Unemployment , 2014, PloS one.
[5] Carlo Ratti,et al. Cities through the Prism of People’s Spending Behavior , 2015, PloS one.
[6] Margaret L. Kern,et al. Personality, Gender, and Age in the Language of Social Media: The Open-Vocabulary Approach , 2013, PloS one.
[7] Yi Ma,et al. Robust principal component analysis? , 2009, JACM.
[8] Carlo Ratti,et al. Towards a comparative science of cities: using mobile traffic records in New York, London and Hong Kong , 2014, ArXiv.
[9] T. Landauer,et al. Indexing by Latent Semantic Analysis , 1990 .
[10] Tobias Preis,et al. Quantifying crowd size with mobile phone and Twitter data , 2015, Royal Society Open Science.
[11] D. Brockmann,et al. The Structure of Borders in a Small World , 2010, PLoS ONE.
[12] Peter Z. Kunszt,et al. Indexing the Sphere with the Hierarchical Triangular Mesh , 2007, ArXiv.
[13] Carlo Ratti,et al. Geo-located Twitter as proxy for global mobility patterns , 2013, Cartography and geographic information science.
[14] Dino Pedreschi,et al. Understanding the patterns of car travel , 2013 .
[15] Brendan T. O'Connor,et al. From Tweets to Polls: Linking Text Sentiment to Public Opinion Time Series , 2010, ICWSM.
[16] T. Landauer,et al. A Solution to Plato's Problem: The Latent Semantic Analysis Theory of Acquisition, Induction, and Representation of Knowledge. , 1997 .
[17] David Brain. From Good Neighborhoods to Sustainable Cities: Social Science and the Social Agenda of the New Urbanism , 2005 .
[18] R. Mare,et al. Neighborhood Choice and Neighborhood Change1 , 2006, American Journal of Sociology.
[19] Soong Moon Kang,et al. Structure of Urban Movements: Polycentric Activity and Entangled Hierarchical Flows , 2010, PloS one.
[20] R. Sampson,et al. Disparity and diversity in the contemporary city: social (dis)order revisited. , 2009, The British journal of sociology.
[21] Christopher M. Danforth,et al. The Geography of Happiness: Connecting Twitter Sentiment and Expression, Demographics, and Objective Characteristics of Place , 2013, PloS one.
[22] G. Sapiro,et al. A collaborative framework for 3D alignment and classification of heterogeneous subvolumes in cryo-electron tomography. , 2013, Journal of structural biology.
[23] M. Barthelemy,et al. From mobile phone data to the spatial structure of cities , 2014, Scientific Reports.
[24] István Csabai,et al. Race, religion and the city: twitter word frequency patterns reveal dominant demographic dimensions in the United States , 2015, Palgrave Communications.
[25] Joseph Ferreira,et al. Activity-Based Human Mobility Patterns Inferred from Mobile Phone Data: A Case Study of Singapore , 2017, IEEE Transactions on Big Data.
[26] Steve Renals,et al. Document space models using latent semantic analysis , 1997, EUROSPEECH.
[27] Kyumin Lee,et al. You are where you tweet: a content-based approach to geo-locating twitter users , 2010, CIKM.
[28] Alessandro Vespignani,et al. The Twitter of Babel: Mapping World Languages through Microblogging Platforms , 2012, PloS one.
[29] Peter Druschel,et al. Online social networks: measurement, analysis, and applications to distributed information systems , 2009 .
[30] Tobias Preis,et al. Quantifying the Impact of Scenic Environments on Health , 2015, Scientific Reports.
[31] Huan Liu,et al. Is the Sample Good Enough? Comparing Data from Twitter's Streaming API with Twitter's Firehose , 2013, ICWSM.
[32] M. Williams,et al. Who Tweets? Deriving the Demographic Characteristics of Age, Occupation and Social Class from Twitter User Meta-Data , 2015, PloS one.
[33] Harry Eugene Stanley,et al. Languages cool as they expand: Allometric scaling and the decreasing need for new words , 2012, Scientific Reports.
[34] Dino Pedreschi,et al. Returners and explorers dichotomy in human mobility , 2015, Nature Communications.
[35] Alexander S. Szalay,et al. Efficient classification of billions of points into complex geographic regions using hierarchical triangular mesh , 2014, SSDBM '14.
[36] Lars Backstrom,et al. Find me if you can: improving geographical prediction with social and spatial proximity , 2010, WWW '10.
[37] Ladislav Kristoufek,et al. Nowcasting Unemployment Rates with Google Searches: Evidence from the Visegrad Group Countries , 2014, PloS one.
[38] Matthew Zook,et al. The Technology of Religion: Mapping Religious Cyberscapes , 2012 .
[39] H Eugene Stanley,et al. Quantifying the semantics of search behavior before stock market moves , 2014, Proceedings of the National Academy of Sciences.
[40] István Csabai,et al. A multi-terabyte relational database for geo-tagged social network data , 2013, 2013 IEEE 4th International Conference on Cognitive Infocommunications (CogInfoCom).
[41] Paul A. Longley,et al. The Geotemporal Demographics of Twitter Usage , 2015 .
[42] D. Helbing,et al. Growth, innovation, scaling, and the pace of life in cities , 2007, Proceedings of the National Academy of Sciences.
[43] Tony E. Smith,et al. International Regional Science Review , 2014 .
[44] Christian Schneider,et al. Spatiotemporal Patterns of Urban Human Mobility , 2012, Journal of Statistical Physics.
[45] Vanessa Frías-Martínez,et al. Spectral clustering for sensing urban land use using Twitter activity , 2014, Engineering applications of artificial intelligence.
[46] Zbigniew Smoreda,et al. Delineating Geographical Regions with Networks of Human Interactions in an Extensive Set of Countries , 2013, PloS one.
[47] Jure Leskovec,et al. Friendship and mobility: user movement in location-based social networks , 2011, KDD.
[48] Lincoln Quillian,et al. Migration Patterns and the Growth of High‐Poverty Neighborhoods, 1970‐‐19901 , 1999, American Journal of Sociology.
[49] Vincent D. Blondel,et al. A survey of results on mobile phone datasets analysis , 2015, EPJ Data Science.
[50] Matjaz Perc,et al. Evolution of the most common English words and phrases over the centuries , 2012, Journal of The Royal Society Interface.
[51] Eric P. Xing,et al. Diffusion of Lexical Change in Social Media , 2012, PloS one.
[52] Robert Tibshirani,et al. Boolean implication networks derived from large scale, whole genome microarray datasets , 2008, Genome Biology.
[53] Gregory J. Park,et al. Psychological Language on Twitter Predicts County-Level Heart Disease Mortality , 2015, Psychological science.
[54] Albert-László Barabási,et al. Understanding individual human mobility patterns , 2008, Nature.
[55] T. Geisel,et al. The scaling laws of human travel , 2006, Nature.
[56] Rima Wilkes,et al. Does Socioeconomic Status Matter? Race, Class, and Residential Segregation , 2006 .
[57] Carlo Ratti,et al. Cellular Census: Explorations in Urban Data Collection , 2007, IEEE Pervasive Computing.
[58] Marta C. González,et al. A universal model for mobility and migration patterns , 2011, Nature.
[59] Kyumin Lee,et al. Exploring Millions of Footprints in Location Sharing Services , 2011, ICWSM.