Activity patterns, socioeconomic status and urban spatial structure: what can social media data tell us?

International Journal of Geographical Information Science

Volumn 30, Issue 9, 2016, Pages 1873-1898

  Huang, Qunying ^a   Wong, David W S ^b,c  

^a UNIVERSITY OF WISCONSIN MADISON   (United States)

^b GEORGE MASON UNIVERSITY   (United States)

^c UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

activity zones; social networks; Socioeconomic status; spatial clustering; Twitter; urban spatial structure

Indexed keywords

SOCIAL NETWORK; SOCIOECONOMIC STATUS; URBAN AREA; URBAN SOCIETY; WORLD WIDE WEB;

DISTRICT OF COLUMBIA; UNITED STATES; WASHINGTON [DISTRICT OF COLUMBIA];

EID: 84959049026     PISSN: 13658816     EISSN: 13623087     Source Type: Journal    
DOI: 10.1080/13658816.2016.1145225     Document Type: Article

References (74)

1. R.Beecham,, J.Wood,, and A.Bowerman,, 2014. Studying commuting behaviours using collaborative visual analytics. Computers, Environment and Urban Systems, 47, 5–15. doi:10.1016/j.compenvurbsys.2013.10.007
2. K.Buchin,, M.Buchin,, and J.Gudmundsson,, 2010. Constrained free space diagrams: a tool for trajectory analysis. International Journal of Geographical Information Science, 24 (7), 1101–1125. doi:10.1080/13658810903569598
3. M.Buchin,, S.Dodge,, and B.Speckmann,, 2014. Similarity of trajectories taking into account geographic context. Journal of Spatial Information Science, 9, 101–124.
4. R.N.Buliung, and P.S.Kanaroglou,, 2006a. A GIS toolkit for exploring geographies of household activity/travel behavior. Journal of Transport Geography, 14 (1), 35–51. doi:10.1016/j.jtrangeo.2004.10.008
5. R.N.Buliung, and P.S.Kanaroglou,, 2006b. Urban form and household activity-travel behavior. Growth and Change, 37 (2), 172–199. doi:10.1111/grow.2006.37.issue-2
6. B.Chaix,, et al., 2012. An interactive mapping tool to assess individual mobility patterns in neighborhood studies. American Journal of Preventive Medicine, 43 (4), 440–450. doi:10.1016/j.amepre.2012.06.026
7. S.Chandra,, L.Khan,, and F.B.Muhaya,, 2011. Estimating twitter user location using social interactions–a content based approach. In: Privacy, Security, Risk and Trust (PASSAT) and 2011 IEEE Third Inernational Conference on Social Computing (SocialCom), 2011, Boston, MA. IEEE, 838–843.
8. J.Chen,, et al., 2011. Exploratory data analysis of activity diary data: a space–time GIS approach. Journal of Transport Geography, 19, 394–404. doi:10.1016/j.jtrangeo.2010.11.002
9. Z.Cheng,, J.Caverlee,, and K.Lee,, 2010. You are where you tweet: a content-based approach to geo-locating twitter users. In: Proceedings of the 19th ACM international conference on Information and knowledge management, Toronto, ON. ACM, 759–768.
10. S.Cohn, and M.Fossett,, 1996. What spatial mismatch? The proximity of blacks to employment in Boston and Houston. Social Forces, 75 (2), 557–573. doi:10.1093/sf/75.2.557
11. W.K.D.Davies, and R.A.Murdie,, 1993. Measuring the social ecology of cities. In: L.S.Bourne and D.F.Ley, eds. The changing social geography of Canadian cities. Montreal, Quebec: McGill-Queen’s University Press, 52–75.
12. E.Delmelle,, et al., 2013. Methods for space-time analysis and modeling: an overview. International Journal of Applied Geospatial Research, 4 (4), 1–18. doi:10.4018/IJAGR
13. L.Downey,, 2003. Spatial measurement, geography and urban racial inequality. Social Forces, 81 (3), 937–952. doi:10.1353/sof.2003.0031
14. F.Echenique, and R.G.FryerJr.,, 2007. A measure of segregation based on social interactions. The Quarterly Journal of Economics, 122 (2), 441–485. doi:10.1162/qjec.122.2.441
15. M.Ester,, et al., 1996. A density-based algorithm for discovering clusters in large spatial databases with noise. In: the second International Conference on Knowledge Discovery and Data Mining (KDD-96), 2-4 August Portland, Oregon. California: AAAI Press, 226–231.
16. R.Ewing, and R.Cervero,, 2001. Travel and the built environment: A synthesis. Transportation Research Record: Journal of the Transportation Research Board, 1780, 87–114. doi:10.3141/1780-10
17. S.Farber,, A.Páez,, and C.Morency,, 2012. Activity spaces and the measurement of clustering and exposure: A case study of linguistic groups in Montreal. Environment and Planning A, 44 (2), 315–332. doi:10.1068/a44203
18. L.Gobillon,, H.Selod,, and Y.Zenou,, 2007. The mechanisms of spatial mismatch. Urban Studies, 44 (12), 2401–2428. doi:10.1080/00420980701540937
19. S.Hanson,, 1982. The determinants of daily travel-activity patterns: relative location and sociodemographic factors. Urban Geography, 3 (3), 179–202. doi:10.2747/0272-3638.3.3.179
20. G.-S.Hong,, A.M.Morrison,, and L.A.Cai,, 1996. Household expenditure patterns for tourism products and services. Journal of Travel & Tourism Marketing, 4 (4), 15–40. doi:10.1300/J073v04n04_02
21. F.E.Horton, and D.R.Reynolds,, 1971. Effects of urban spatial structure on individual behavior. Economic Geography, 47 (1), 36–48. doi:10.2307/143224
22. Q.Huang,, G.Cao,, and C.Wang,, 2014. From where do tweets originate? - A GIS approach for user location inference. In: Proceedings of the 7th ACM SIGSPATIAL International Workshop on Location-Based Social Networks (LBSN ‘14), 4–7November, Dallas, TX, USA. New York, NY: ACM, 1–8.
23. Q.Huang, and D.Wong,, 2015. Modeling and visualizing regular human mobility patterns with uncertainty: an example using Twitter data. Annals of the Association of American Geographers, 105, 1179–1197. forthcoming. doi:10.1080/00045608.2015.1081120
24. O.Järv,, et al., 2014. Ethnic differences in activity spaces as a characteristic of segregation: A study based on mobile phone usage in Tallinn, Estonia. Urban Studies. doi:10.1177/0042098014550459
25. R.J.Johnston,, 1976. Residential area characteristics: research methods for identifying urban sub-areas – social area analysis and factorial ecology. In: D.T.Herbert and R.J.Johnston, eds. Social areas in cities. Chichester: Wiley, 193–235.
26. M.Jones, and A.R.Pebley,, 2014. Redefining neighborhoods using common destinations: social characteristics of activity spaces and home census tracts compared. Demography, 51, 727–752. doi:10.1007/s13524-014-0283-z
27. J.F.Kain,, 1992. The spatial mismatch hypothesis: three decades later. Housing Policy Debate, 3 (2), 371–460. doi:10.1080/10511482.1992.9521100
28. M.-P.Kwan,, 1998. Space-time and integral measures of individual accessibility: a comparative analysis using a point-based framework. Geographical Analysis, 30 (3), 191–216.
29. M.-P.Kwan,, 2000. Interactive geovisualization of activity travel patterns using three-dimensional geographical information systems: a methodological exploration with a large dataset. Transportation Research Part C: Emerging Technologies, 8, 185–203. doi:10.1016/S0968-090X(00)00017-6
30. M.-P.Kwan,, 2008. From oral histories to visual narratives: re-presenting the post-September 11 experiences of the Muslim women in the USA. Social and Cultural Geography, 9 (6), 653–669.
31. M.-P.Kwan,, 2013. Beyond space (as we knew it): toward temporally integrated geographies of segregation, health, and accessibility. Annals of the Association of American Geographers, 103 (5), 1078–1086. doi:10.1080/00045608.2013.792177
32. P.Laube, and R.S.Purves,, 2006. An approach to evaluating motion pattern detection techniques in spatio-temporal data. Computers, Environment and Urban Systems, 30 (3), 347–374. doi:10.1016/j.compenvurbsys.2005.09.001
33. R.Li,, et al., 2012. Towards social user profiling: unified and discriminative influence model for inferring home locations. In: Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining, Beijing. ACM, 1023–1031.
34. S.Livingstone, and E.Helsper,, 2007. Gradations in digital inclusion: children, young people and the digital divide. New Media & Society, 9 (4), 671–696. doi:10.1177/1461444807080335
35. P.A.Longley,, M.Adnan,, and G.Lansley,, 2015. The geotemporal demographics of Twitter usage. Environment and Planning A, 47 (2), 465–484. doi:10.1068/a130122p
36. D.W.MacPherson,, and B.D.Gushulak,, 2001. Human mobility and population health: new approaches in a globalizing world. Perspectives in Biology and Medicine, 44 (3), 390–401.
37. J.Mahmud,, J.Nichols,, and C.Drews,, 2012. Where is this tweet from? Inferring home locations of Twitter users. ICWSM, 12, 511–514.
38. L.Manovich,, 2011. Trending: the promises and the challenges of big social data. Debates in the Digital Humanities, 2 (2011), 460–475.
39. S.A.Matthews, and T.-C.Yang,, 2013. Spatial polygamy and contextual exposures (SPACEs): promoting activity space approaches in research on place and health. American Behavioral Scientist, 57 (8), 1057–1081.
40. D.S.Massey, and N.A.Denton,, 1993. The American apartheid: Segregation and the making of the underclass. Cambridge, MA: Harvard University Press.
41. S.A.Matthews,, 2011. Spatial polygamy and the heterogeneity of place: studying people and place via egocentric methods. In: L.M.Burton, et al., eds. Communities, neighborhoods, and health: expanding the boundaries of place. New York, NY: Springer, 35–55.
42. S.McLafferty, and V.Preston,, 1996. Spatial mismatch and employment in a decade of restructuring. The Professional Geographer, 48 (4), 420–431. doi:10.1111/j.0033-0124.1996.00420.x
43. A.Mislove,, et al., 2011. Understanding the demographics of Twitter users. In: Proceedings of the 5th International AAAI Conference on Weblogs and Social Media (ICWSM’11), 17–21July Barcelona, Catalonia, Spain. Menlo Park, CA: AAAI Press, 554–557. http://www.aaai.org/ocs/index.php/ICWSM/ICWSM11/paper/viewFile/2816/3234
44. F.Morstatter,, et al., 2013. Is the sample good enough? Comparing data from Twitter’s streaming api with Twitter’s firehose. arXiv preprint arXiv:1306.5204.
45. National Research Council, 2002. Community and quality of life: data needs for informed decision making. Washington, DC: National Academy Press.
46. J.R.B.Palmer,, et al., 2013. New approaches to human mobility: using mobile phones for demographic research. Demography, 50, 1105–1128. doi:10.1007/s13524-012-0175-z
47. E.I.Pas,, 1984. The effect of selected sociodemographic characteristics on daily travel-activity behavior. Environment and Planning A, 16 (5), 571–581. doi:10.1068/a160571
48. T.F.Pettigrew,, 2008. Future directions for intergroup contact theory and research. International Journal of Intercultural Relations, 32, 187–199. doi:10.1016/j.ijintrel.2007.12.002
49. T.F.Pettigrew, and L.R.Tropp,, 2008. How does intergroup contact reduce prejudice? Meta-analytic tests of three mediators. European Journal of Social Psychology, 38, 922–934. doi:10.1002/ejsp.v38:6
50. S.F.Philipp,, 1993. Racial differences in the perceived attractiveness of tourism destinations, interests, and cultural resources. Journal of Leisure Research, 25 (3), 290–304.
51. S.F.Philipp,, 1994. Race and tourism choice: A legacy of discrimination? Annals of Tourism Research, 21 (3), 479–488. doi:10.1016/0160-7383(94)90115-5
52. V.Preston, and S.McLafferty,, 1999. Spatial mismatch research in the 1990s: progress and potential. Papers in Regional Science, 78, 387–402. doi:10.1007/s101100050033
53. F.Ren, and M.-P.Kwan,, 2007. Geovisualization of human hybrid activity-travel patterns. Transactions in GIS, 11 (5), 721–744. doi:10.1111/tgis.2007.11.issue-5
54. S.Schönfelder, and K.W.Axhausen,, 2003. Activity spaces: measures of social exclusion? Transport Policy, 10, 273–286. doi:10.1016/j.tranpol.2003.07.002
55. S.L.Shaw, and H.Yu,, 2009. A GIS-based time-geographic approach of studying individual activities and interactions in a hybrid physical–virtual space. Journal of Transport Geography, 17 (2), 141–149.
56. S.-L.Shaw,, H.Yu,, and L.S.Bombom,, 2008. A space–time GIS approach to exploring large individual-based spatiotemporal datasets. Transactions in GIS, 12 (4), 425–441. doi:10.1111/tgis.2008.12.issue-4
57. M.Sheller, and J.Urry,, 2006. The new mobilities paradigm. Environment and Planning A, 38 (2), 207–226.
58. Y.Shen,, M.-P.Kwan,, and Y.Chai.,, 2013. Investigating commuting flexibility with GPS data and 3D geovisualization: a case study of Beijing, China. Journal of Transport Geography, 32, 1–11. doi:10.1016/j.jtrangeo.2013.07.007
59. S.Silm, and R.Ahas,, 2014. Ethnic differences in activity spaces: A study of out-of-home nonemployment activities with mobile phone data. Annals of the Association of American Geographers, 104 (3), 542–559. doi:10.1080/00045608.2014.892362
60. A.Stefanidis,, A.Crooks,, and J.Radzikowski,, 2013. Harvesting ambient geospatial information from social media feeds. GeoJournal, 78 (2), 319–338. doi:10.1007/s10708-011-9438-2
61. E.Steiger,, J.P.De Albuquerque,, and A.Zipf,, 2015. An advanced systematic literature review on spatiotemporal analyses of Twitter data. Transactions in GIS, 19, 809–834. doi:10.1111/tgis.12132
62. M.A.Stoll, and K.Covington,, 2012. Explaining racial/ethnic gaps in spatial mismatch in the US: the primacy of racial segregation. Urban Studies, 49 (11), 2501–2521. doi:10.1177/0042098011427180
63. B.D.Taylor, and P.M.Ong,, 1995. Spatial mismatch or automobile mismatch? an examination of race, residence and commuting in US metropolitan areas. Urban Studies, 32 (9), 1453–1473. doi:10.1080/00420989550012348
64. M.-H.Tsou,, et al., 2014. Mapping ideas from cyberspace to Realspace: visualizing the spatial context of keywords from web page search results. International Journal of Digital Earth, 7 (4), 316–335. doi:10.1080/17538947.2013.781240
65. D.Wang,, F.Li,, and Y.Chai,, 2012. Activity spaces and sociospatial segregation in Beijing. Urban Geography, 33 (2), 256–277. doi:10.2747/0272-3638.33.2.256
66. B.A.Weinberg,, 2000. Black residential centralization and the spatial mismatch hypothesis. Journal of Urban Economics, 48, 110–134. doi:10.1006/juec.1999.2159
67. D.R.Williams, and C.Collins,, 2001. Racial residential segregation: a fundamental cause of racial disparities in health. Public Health Reports, 116, 404–416. doi:10.1016/S0033-3549(04)50068-7
68. J.C.Witte, and S.E.Mannon,, 2010. The Internet and social inequalities. London, UK: Routledge.
69. D.W.S.Wong, and J.Lee,, 2005. Statistical analysis and modeling of geographic information. New York, NY: Wiley and Sons.
70. D.Wong, and S.-L.Shaw,, 2011. Measuring segregation: an activity space approach. Journal of Geographical Systems, 13, 127–145. doi:10.1007/s10109-010-0112-x
71. E.K.Wyly,, 1996. Race, gender, and spatial segmentation in the twin cities. The Professional Geographer, 48 (4), 431–444. doi:10.1111/j.0033-0124.1996.00431.x
72. C.Xu,, D.W.Wong,, and C.Yang,, 2013. Evaluating the “Geographical Awareness” of individuals: an exploratory analysis of Twitter data. Cartography and Geographic Information Science, 40 (2), 103–115. doi:10.1080/15230406.2013.776212
73. H.Yu,, 2007. Visualizing and analyzing activities in an integrated space-time environment: temporal geographic information system design and implementation. Transportation Research Record: Journal of the Transportation Research Board, 2024, 54–62.
74. C.Zhou,, et al., 2004. Discovering personal gazetteers: an interactive clustering approach. In: Proceedings of the 12th annual ACM international workshop on Geographic information systems. New York, NY: ACM, 266–273.