2019 | 46 | 67-89
Article title

Czy więcej znaczy lepiej? Badania ilościowe w geografii społeczno-ekonomicznej ery Big Data

Title variants
Does more mean better? Quantitative research in the socio-economic geography in the age of Big Data
Languages of publication
Wielkie zbiory danych typu Big Data są obecnie nieodłącznym elementem badań w wielu dziedzinach nauki – w tym w geografii społeczno-ekonomicznej. Znajdują one szereg zastosowań, zarówno wnosząc możliwość analizy nowych danych w klasycznych problemach badawczych, jak i same w sobie będąc nowym przedmiotem badań oraz pozwalając na badanie cyfrowych geografii. Jednocześnie Big Data krytykuje się za niejednorodność, brak reprezentatywności, nierówność reprezentacji czy też problemy etyczne. Z tego powodu zwracamy uwagę na szereg dylematów związanych z obecnością Big Data w praktyce badawczej, sugerując istotną rolę krytycznego podejścia do ich zastosowania w praktyce badawczej.
Big Data are inseparable part of the current research methodology in many scientific disciplines – including socio-economic geography. They are being used as a new data in old research problems, as a new research objects and as a means to investigate digital geographies. Big Data are being criticized for lack of representativeness and problematic representation, heterogeneity, and ethical issues. Despite these problems, their presence as a part of the geographical research methodology is increasingly frequent. We propose a set of recommendations that in our view allows a researcher to critically assess the validity of utilizing Big Data in a given research project.
Physical description
  • Abbas R., Michael K., Michael M.G. 2014. The regulatory considerations and ethical dilemmas of location-based services (LBS): A literature review. Information Technology & People, 27: 2–20.
  • Al Nuaimi E., Al Neyadi H., Mohamed N., Al-Jaroodi J. 2015. Applications of big data to smart cities. Journal of Internet Services and Applications, 6: 25.
  • Anderson Ch. 2008. “Essay: The Data Deluge Makes the Scientific Method Obsolete”. Wired Magazine, 10–12.
  • Andrejevic M. 2014. The Big Data Divide. International Journal of Communication 8(1): 1673–1689.
  • Arribas-Bel D. 2014. Accidental, open and everywhere: Emerging data sources for the understanding of cities. Applied Geography, 49: 45–53.
  • Barnes T.J. 2013. Big Data, Little History. Dialogues in Human Geography, 3(3): 297–302.
  • Batty M. 2013. Big data, smart cities and city planning. Dialogues in Human Geography, 3: 274–279.
  • Birkin M. 2019. Spatial data analytics of mobility with consumer data. Journal of Transport Geography, 76: 245–253.
  • Brooker P., Barnett J., Cribbin T., Sharma S. 2016. Have We Even Solved the First ’Big Data Challenge?’ Practical Issues Concerning Data Collection and Visual Representation for Social Media Analytics. [W:] H. Snee, Ch. Hine, Y. Morey, S. Roberts, H. Watson (red.), Digital Methods for Social Science. An Interdisciplinary Guide to Research Innovation. Palgrave Macmillan, New York, s. 17–33.
  • Bruns A., Burgess J. 2016. Methodological Innovation in Precarious Spaces: The Case of Twitter. [W:] H. Snee, Ch. Hine, Y. Morey, S. Roberts, H. Watson (red.), Digital Methods for Social Science. An Interdisciplinary Guide to Research Innovation, Palgrave Macmillan, New York, s. 17–33.
  • Burrows R. 2013. The new gilded ghettos: The geodemographics of the super-rich. Sociology, 41(5): 885–899.
  • Burns R. 2015. Rethinking big data in digital humanitarianism: Practices, epistemologies, and social relations. GeoJournal, 80(4): 477–490.
  • Coleman D.J., Georgiadou Y., Labonte J. 2009. Volunteered geographic information: The nature and motivation of produsers. International Journal of Spatial Data Infrastructures Research, 4: 332– 358.
  • Coletta C., Kitchin R. 2017. Algorhythmic governance: Regulating the ’heartbeat’ of a city using the Internet of Things. Big Data & Society, 4: 2053951717742418.
  • Connors J.P., Lei S., Kelly M. 2012. Citizen science in the age of neogeography: Utilizing volunteered geographic information for environmental monitoring. Annals of the Association of American Geographers, 102(6), 1267–1289.
  • Dalton C., Taylor L., Thatcher J. 2016. Critical Data Studies: A Dialog on Data and Space. Big Data & Society, June: 1–9.
  • Dalton C., Thatcher J. 2015. Inflated Granularity: Spatial ’Big Data’ and Geodemographics. Big Data & Society, December: 1–15.
  • Deville P., Linard C., Martin S., Gilbert M., Stevens F.R., Gaughan A.E., Blondel V.D., Tatem A.J. 2014. Dynamic population mapping using mobile phone data. Proceedings of the National Academy of Sciences, 111: 15888–15893.
  • Dijck J. van 2014. Datafication, Dataism and Dataveillance: Big Data between Scientific Paradigm and Ideology. Surveillance and Society, 12(2): 197–208.
  • Dobson J.E., Fisher P.F. 2007. The Panopticon’s Changing Geography. Geographical Review, 97: 307– 323
  • Elwood S. 2008. Volunteered geographic information: key questions, concepts and methods to guide emerging research and practice. GeoJournal, 72: 133–135.
  • Evans L. 2011. Location-based services: transformation of the experience of space. Journal of Location Based Services, 5: 242–260.
  • Flanagin A.J., Metzger M.J. 2008. The credibility of volunteered geographic information. GeoJournal, 72: 137–148.
  • Gadziński J. 2017. Wykorzystanie telefonów komórkowych w badaniach zachowań transportowych ludności. Prace Komisji Geografii Komunikacji PTG, 20(4): 7–19.
  • Gadziński J. 2018. Perspectives of the use of smartphones in travel behaviour studies: Findings from a literature review and a pilot study. Transportation Research Part C: Emerging Technologies, 88: 74–86.
  • Galí N., Donaire J.A. 2015. Tourists taking photographs: the long tail in tourists’ perceived image of Barcelona. Current Issues in Tourism, 18: 893–902.
  • Goodchild M.F. 2007. Citizens as sensors: the world of volunteered geography. GeoJournal, 69: 211– 221.
  • Gorman S.P. 2013. The Danger of a Big Data Episteme and the Need to Evolve. Geographic Information Systems, 3(3): 285–291.
  • Graham M., Shelton T. 2013. Geography and the Future of Big Data, Big Data and the Future of Geography. Dialogues in Human Geography, 3(3): 255–261.
  • Haklay M. 2010. How good is volunteered geographical information? A comparative study of OpenStreetMap and Ordnance Survey datasets. Environment and Planning, B, Planning & Design, 37: 682.
  • Hancke G.P., de Carvalho e Silva B., Hancke G.P, Jr. 2013. The role of advanced sensing in smart cities. Sensors, 13(1), 393–425.
  • Hawelka B., Sitko I., Beinat E., Sobolevsky S., Kazakopoulos P., Ratti C. 2014. Geo-located Twitter as proxy for global mobility patterns. Cartography and Geographic Information Science 41, 260–271.
  • Hey T., Tansley S., Tolle K. 2009. The Fourth Paradigm: Data-Intensive Scientific Discovery. Microsoft Research, Redmond.
  • Hochman N., Manovich L. 2013. Zooming into an Instagram City: Reading the local through social media. First Monday, 18.
  • Hochman N., Schwartz R. 2012. Visualizing instagram: Tracing cultural visual rhythms. [W:] Proceedings of the Workshop on Social Media Visualization (SocMedVis) in Conjunction with the Sixth International AAAI Conference on Weblogs and Social Media (ICWSM-12), s. 6–9.
  • Hollenstein L., Purves R. 2010. Exploring place through user-generated content: Using Flickr tags to describe city cores. Journal of Spatial Information Science, 21–48.
  • Huang H., Gartner G. 2018. Current Trends and Challenges in Location-Based Services. ISPRS International Journal of Geo-Information, 7: 199.
  • Huang Q., Wong D.W.S. 2016. Activity patterns, socioeconomic status and urban spatial structure: what can social media data tell us? International Journal of Geographical Information Science, 30: 1873–1898.
  • Iwasiński Ł. 2016. Społeczne zagrożenia danetyzacji rzeczywistości. [W:] B. Sosińska-Kalata, N. Przastek (red.), Nauka o Informacji w okresie zmian. Informatologia i humanistyka cyfrowa. Wydanictwo SBP, s. 135–146.
  • Kitchin R. 2006. Positivistic Geographies and Spatial Science. [W:] C.A. Stuart, G. Valentine (red.), Approaches to Human Geography. Thousand Oaks, CA, Sage, s. 20–29.
  • Kitchin B. 2013. Big Data and Human Geography: Opportunities, Challenges and Risks. Dialogues in Human Geography 3(3): 262–67
  • Kitchin R. 2014. Big Data, New Epistemologies and Paradigm Shifts. Big Data & Society, 1(1): 205395171452848.
  • Kitchin R., McArdle G. 2016. What Makes Big Data, Big Data? Exploring the Ontological Characteristics of 26 Datasets. Big Data & Society, 3(1): 205395171663113.
  • Kulshrestha J., Kooti F., Nikravesh A., Gummadi P.K. 2012. Geographic Dissection of the Twitter Network. [W:] Proceedings of the Sixth International AAAI Conference on Weblogs and Social Media.
  • Krzysztofek K. 2012. Zmiana permanentna? Refleksje o zmianie społecznej w epoce technologii cyfrowych. Studia Socjologiczne, 4(207): 7–39.
  • Laney D. 2001. 3D data management: Controlling data volume, velocity and variety. [w:] Gartner Blog Network (
  • Lapowsky I. 2019. How Cambridge Analytica Sparked the Great Privacy Awakening. Wired 2019 (
  • Leszczynski A., Elwood S. 2015. Feminist geographies of new spatial media: Feminist geographies of new spatial media. The Canadian Geographer/Le Géographe canadien, 59: 12–28.
  • Li Z., Hu F., Schnase J.L., Duffy D.Q., Lee T., Bowen M.K., Yang C. 2017. A spatiotemporal indexing approach for efficient processing of big array-based climate data with MapReduce. International Journal of Geographical Information Science, 31(1): 17–35.
  • Li S., Dragicevic S., Castro F.A., Sester M., Winter S., Coltekin A., Pettit C., Jiang B., Haworth J., Stein A., Cheng T. 2016. Geospatial big data handling theory and methods: A review and research challenges. ISPRS Journal of Photogrammetry and Remote Sensing, 115: 119–133.
  • Liu J., Jie L., Li W., Wu J. 2016. Rethinking Big Data: A Review on the Data Quality and Usage Issues. ISPRS Journal of Photogrammetry and Remote Sensing, 115: 134–142.
  • Liu Y., Sui Z., Kang C., Gao Y. 2014. Uncovering patterns of inter-urban trip and spatial interaction from social media check-in data. PloS one, 9(1), e86026.
  • Macskassy S., Michelson M. 2011. Why Do People Retweet ? Anti-Homophily Wins the Day! [W] Proceedings of the Fifth International Conference on Weblogs and Social Media – ICWSM ’11, s. 209–216.
  • Majewska J., Napierała T., Adamiak M. 2016. Wykorzystanie nowych technologii i informacji do opisu przestrzeni turystycznej. Folia Turistica, 41: 309–339.
  • Markham A. 2018. Troubling the Concept of Data in Qualitative Digital Research. [W:] W. Flick (red.), The SAGE Handbook of Qualitative Data Collection. Sage Publications, s. 511–523.
  • Miah S.J., Vu H.Q., Gammack J., McGrath M. 2017. A Big Data Analytics Method for Tourist Behaviour Analysis. Information & Management, Smart Tourism: Traveler, Business, and Organizational Perspectives, 54: 771–785.
  • Michael K., Michael M.G. 2011. The social and behavioural implications of location-based services. Journal of Location Based Services, 5: 121–137.
  • Miller H.J. 2010. The data avalanche is here. Shouldn’t we be digging? Journal of Regional Science, 50(1): 181–201.
  • Miller H.J., Goodchild M.F. 2015. Data-Driven Geography. GeoJournal, 80(4): 449–461.
  • Orellana D., Bregt A.K., Ligtenberg A., Wachowicz M. 2012. Exploring visitor movement patterns in natural recreational areas. Tourism Management, 33: 672–682.
  • Panelli R. 2009. Social Geography. [W:] R. Kitchin, N. Thrift (red.), International Encyclopedia of Human Geography. Elsevier, s. 185–194.
  • Piskorz-Ryń A. 2017. Inteligentne miasta jako wyzwanie dla samorządu terytorialnego. Przedsiębiorczość i Zarządzanie, s. 23–33.
  • Rae A., Singleton A. 2015. Putting big data in its place: a Regional Studies and Regional Science perspective. Regional Studies, Regional Science, 2: 1–5.
  • Robertson C., Feick R. 2016. Bumps and bruises in the digital skins of cities: unevenly distributed user-generated content across US urban areas. Cartography and Geographic Information Science, 43: 283–300.
  • Robinson A.C., Demšar U., Moore A.B., Buckley A., Jiang B., Field K., Kraak M.-J., Camboim S.P., Sluter C.R. 2017. Geospatial big data and cartography: research challenges and opportunities for making maps that matter. International Journal of Cartography, 3:sup1, 32–60.
  • Rodak O. 2017. Twitter jako przedmiot badań socjologicznych i źródło danych społecznych: perspektywa konstruktywistyczna. Studia Socjologiczne, 3(226): 209–236.
  • Ruggles S. 2014. Big Microdata for Population Research. Demography, 51: 287–297.
  • Rui J.R., Stefanone M.A. 2013. Strategic Image Management Online: Self-Presentation, Self-Esteem and Social Network Perspectives. Information Communication and Society 16 (8): 1286–1305.
  • Rzeszewski M. 2015a. Cyberpejzaż miasta w trakcie megawydarzenia: Poznań, Euro 2012 i Twitter. Studia Regionalne i Lokalne, 123–137.
  • Rzeszewski M. 2015b. Systemy lokalizacji satelitarnej w analizie zachowań przestrzennych użytkowników miasta. Rozwój Regionalny i Polityka Regionalna, 111–121.
  • Rzeszewski M., Luczys P. 2018. Care, Indifference and Anxiety – Attitudes toward Location Data in Everyday Life. ISPRS International Journal of Geo-Information, 7: 383.
  • Salesses P., Schechtner K., Hidalgo C.A. 2013. The Collaborative Image of The City: Mapping the Inequality of Urban Perception. PLOS ONE 8, e68400.
  • Shaw S.L., Tsou M.H., Ye X. 2016. Human dynamics in the mobile and big data era. International Journal of Geographical Information Science, 30(9): 1687–1693.
  • Shelton T., Poorthuis A., Graham M., Zook M. 2014. Mapping the data shadows of Hurricane Sandy: Uncovering the sociospatial dimensions of ’big data.’ Geoforum, 52: 167–179.
  • Shelton T., Poorthuis A. 2019. Atlanta’s Neighborhood Planning Unit system. Annals of the American Association of Geographers, 1–21.
  • Stefanidis A., Crooks A., Radzikowski J. 2013. Harvesting ambient geospatial information from social media feeds. GeoJournal, 78: 319–338.
  • Stephens M. 2013. Gender and the GeoWeb: divisions in the production of user-generated cartographic information. GeoJournal, 78: 981–996.
  • Stephens M., Poorthuis A. 2015. Follow thy neighbor: Connecting the social and the spatial networks on Twitter. Computers, Environment and Urban Systems, 53: 87–95.
  • Sun Y., Fan H., Helbich M., Zipf A. 2013. Analyzing Human Activities Through Volunteered Geographic Information: Using Flickr to Analyze Spatial and Temporal Pattern of Tourist Accommodation. [W:] J.M. Krisp (red.), Progress in Location-Based Services. Springer, Berlin, Heidelberg, s. 57–69.
  • Tao S., Corcoran J., Mateo-Babiano I., Rohde D. 2014. Exploring Bus Rapid Transit passenger travel behaviour using big data. Applied Geography, 53: 90–104.
  • Thatcher J. 2017. You are where you go, the commodification of daily life through ’location.’ Environment and Planning, A 49: 2702–2717.
  • Tomanek K. 2014. Analiza sentymentu – metoda analizy danych jakościowych: przykład zastosowania oraz ewaluacja słownika RID i metody klasyfikacji bayesa w analizie danych jakościowych. Przegląd Socjologii Jakościowej, 10(2): 118–36.
  • Tsou M.H. 2015. Research challenges and opportunities in mapping social media and Big Data. Cartography and Geographic Information Science, 42(1): 70–74.
  • Turner A. 2006. Introduction to neogeography. O’Reilly Media, Inc.
  • Waszewski J., Gurtowski M. 2015. Cyfrowy rasizm? Zautomatyzowane techniki nadzoru jako narzędzie segregacji i dyskryminacji. Transformacje, 1/2(84/85): 88–107.
  • Wilson M.W. 2015. Morgan Freeman is dead and other big data stories. Cultural Geographies, 22: 345–349.
  • Wójcik M., Suliborski A. 2014. Geografia społeczna w Polsce – geneza, koncepcje i zróżnicowanie problemowe, ze szczególnym uwzględnieniem studiów geograficzno-miejskich w ośrodku łódzkim. [W:] A. Suliborski, M. Wójcik (red.), Dysproporcje Społeczne i Gospodarcze w Przestrzeni Łodzi. Czynniki, Mechanizmy, Skutki. Wydawnictwo Uniwersytetu Łódzkiego, Łódź, s. 17–48.
  • Wu W., Wang J., Dai T. 2016. The geography of cultural ties and human mobility: Big data in urban contexts. Annals of the American Association of Geographers, 106(3): 612–630.
  • van Meeteren M., Poorthuis A. 2018. Christaller and “big data”: recalibrating central place theory via the geoweb. Urban Geography, 39: 122–148.
  • Yin L., Cheng Q., Wang Z., Shao Z. 2015. ’Big data’ for pedestrian volume: Exploring the use of Google Street View images for pedestrian counts. Applied Geography, 63: 337–345.
  • Zajadacz A. 2017. Dyssatysfakcja w przestrzeni turystycznej. Negatywne opinie użytkowników TripAdvisor na temat głównych atrakcji turystycznych wybranych miast w Polsce. Prace i Studia Geograficzne, 62(3): 63–88.
  • Zasina J. 2018. The Instagram Image of the City. Insights from Lodz, Poland. Bulletin of Geography. Socio-economic Series, 42: 213–225.
  • Zook M., Graham M., Shelton T., Gorman S. 2010. Volunteered geographic information and crowdsourcing disaster relief: a case study of the Haitian earthquake. World Medical & Health Policy, 2: 7–33.
  • Zook M. 2017. Crowd-sourcing the smart city: Using big geosocial media metrics in urban governance. Big Data & Society, 4: 205395171769438.
Document Type
Publication order reference
YADDA identifier
JavaScript is turned off in your web browser. Turn it on to take full advantage of this site, then refresh the page.