Giovanni Quattrone
ABSTRACT
Crowd-sourcing has become a popular form of computer mediated collaborative work and OpenStreetMap represents one of the most successful crowd-sourcing systems, where the goal of building and maintaining an accurate global map of the world is being accomplished by means of contributions made by over 1.2M citizens. However, within this apparently large crowd, a tiny group of highly active users is responsible for the mapping of almost all the content. One may thus wonder to what extent the information being mapped is biased towards the interests and agenda of this group of users. In this paper, we present a method to quantitatively measure content bias in crowd-sourced geographic information. We then apply the method to quantify content bias across a three-year period of OpenStreetMap mapping in 40 countries. We find almost no content bias in terms of what is being mapped, but significant geographic bias; furthermore, we find that bias in terms of meticulousness varies with culture.
- Arsanjani, J., Barron, C., Bakillah, M., and Helbich, M. Assessing the Quality of OpenStreetMap Contributors together with their Contributions. In Proc. of AGILE (2013).Google Scholar
- Boyd, D., and Crawford, K. Critical Questions for Big Data: Provocations for a Cultural, Technological, and Scholarly Phenomenon. Information, Communication & Society 15, 5 (2012), 662--679.Google ScholarCross Ref
- Brabham, D. Crowdsourcing. MIT Press, 2013. Google ScholarDigital Library
- Bryant, S., Forte, A., and Bruckman, A. Becoming Wikipedian: Transformation of Participation in a Collaborative Online Encyclopedia. In Proc. of GROUP, ACM (2005), 1--10. Google ScholarDigital Library
- Callahan, E., and Herring, S. Cultural Bias in Wikipedia Content on Famous Persons. Journal of the American Society for Information Science and Technology 62, 10 (2011), 1899--1915. Google ScholarDigital Library
- Cha, M., Kwak, H., Rodriguez, P., Ahn, Y., and Moon, S. I Tube, You Tube, Everybody Tubes: Analyzing the World's Largest User Generated Content Video System. In Proc. of IMC, ACM (2007), 1--14. Google ScholarDigital Library
- Chango, S., Kumar, V., Gilbert, E., and Terveen, L. Specialization, Homophily, and Gender in a Social Curation Site: Findings from Pinterest. In Proc. of CSCW, ACM (2014), 674--686. Google ScholarDigital Library
- Cohen, N. Define Gender Gap? Look Up Wikipedias Contributor List. The New York Times (January 2011).Google Scholar
- Dai, W., Jin, G. Z., Lee, J., and Luca, M. Optimal Aggregation of Consumer Ratings: An Application to Yelp.com. Tech. rep., National Bureau of Economic Research, 2012.Google ScholarCross Ref
- Fana, H., Zipfa, A., Fub, Q., and Neisa, P. Quality assessment for building footprints data on OpenStreetMap. International Journal of Geographical Information Science (IJGIS) 28, 4 (2014), 700--719. Google ScholarDigital Library
- Gallagher, S., and Savage, T. Cross-cultural analysis in online community research: A literature review. Computers in Human Behavior (2012). Google ScholarDigital Library
- Garcia-Gavilanes, R., Quercia, D., and Jaimes, A. Cultural Dimensions in Twitter: Time, Individualism, and Power. In Proc. of ICWSM (2013).Google Scholar
- Girres, J., and Touya, G. Quality assessment of the French OpenStreetMap dataset. Transactions in GIS 14, 4 (2010), 435--459.Google ScholarCross Ref
- Goodchild, M. Citizens as Sensors: the World of Volunteered Geography. GeoJournal 69, 4 (2007), 211--221.Google ScholarCross Ref
- Haklay, M. How good is volunteered geographical information? A comparative study of OpenStreetMap and Ordnance Survey datasets. Environment and Planning B: Planning and Design 37, 4 (2010), 682--703.Google ScholarCross Ref
- Haklay, M., Basiouka, S., Antoniou, V., and Ather, A. How Many Volunteers Does it Take to Map an Area Well? The Validity of Linus Law to Volunteered Geographic Information. The Cartographic Journal 47, 4 (2010), 315--322.Google ScholarCross Ref
- Halfaker, A., Geiger, R., Morgan, J., and Riedl, J. The Rise and Decline of an Open Collaboration System: How Wikipedia's reaction to sudden popularity is causing its decline. American Behavioral Scientist 57, 5 (2013), 664--688.Google ScholarCross Ref
- Halfaker, A., Kittur, A., Kraut, R., , and Riedl, J. A Jury of your Peers: Quality, Experience and Ownership in Wikipedia. In Proc. of WikiSym, ACM (2009). Google ScholarDigital Library
- Hecht, B., and Stephens, M. A Tale of Cities: Urban Biases in Volunteered Geographic Information. In Proc. of ICWSM 2014 (2014).Google Scholar
- Hofstede, G. Culture's Consequences: Comparing Values, Behaviors, Institutions and Organizations across Nations. SAGE Publications, 2001.Google Scholar
- Howe, J. The Rise of Crowdsourcing. Wired (2006).Google Scholar
- Hristova, D., Quattrone, G., Mashhadi, A., and Capra, L. The Life of the Party: Impact of Social Mapping in OpenStreetMap. In Proc. of ICWSM (2013).Google Scholar
- Hu, M., Lim, E., Sun, A., Lauw, H., and Vuong, B. Measuring Article Quality in Wikipedia: Models and Evaluation. In Proc. of CIKM, ACM (2007). Google ScholarDigital Library
- Ishida, K. Geographical Bias on Social Media and Geo-local Contents System with Mobile Devices. In Proc. of HICSS (2012), 1790--1796. Google ScholarDigital Library
- Kittur, A., Chi, E., Pendleton, B., Suh, B., and Mytkowicz, T. Power of the Few vs. Wisdom of the Crowd: Wikipedia and the Rise of the Bourgeoisie. In Proc. of WWW (2007).Google Scholar
- L., J. R., Irani, Silberman, M., Zaldivar, A., and Tomlinson, B. Who are the Crowdworkers' Shifting Demographics in Mechanical Turk. In Proc. of CHI (2010). Google ScholarDigital Library
- Lam, S. T. K., Uduwage, A., Dong, Z., Sen, S., Musicant, D. R., Terveen, L., and Riedl, J. WP:Clubhouse- An Exploration of Wikipedias Gender Imbalance. In Proc. of WikiSym, ACM (2011), 1--10. Google ScholarDigital Library
- Ludwig, I., Voss, A., and Krause-Traudes, M. A Comparison of the Street Networks of Navteq and OSM in Germany. Advancing Geoinformation Science for a Changing World 1, 2 (2011), 65--84.Google Scholar
- Maceachren, A. M., Robinson, A., Gardner, S., Murray, R., Gahegan, M., and Hetzler, E. Visualizing Geospatial Information Uncertainty: What We Know and What We Need to Know. Information Science 32 (2005), 160.Google Scholar
- Mashhadi, A., Quattrone, G., Capra, L., and Mooney, P. On the Accuracy of Urban Crowd-Sourcing for Maintaining Large-Scale Geospatial Databases. In Proc. of WikiSym, ACM (2012). Google ScholarDigital Library
- Neis, P., Zielstra, D., and Zipf, A. Comparison of Volunteered Geographic Information Data Contributions and Community Development for Selected World Regions. Future Internet 5, 2 (2013), 282--300.Google ScholarCross Ref
- Neis, P., and Zipf, A. Analyzing the Contributor Activity of a Volunteered Geographic Information ProjectThe Case of OpenStreetMap. ISPRS International Journal of Geo-Information 1, 2 (2012), 146--165.Google ScholarCross Ref
- Panciera, K., Halfaker, A., and Terveen, L. Wikipedians Are Born, Not Made: a Study of Power Editors on Wikipedia. In Proc. of GROUP, ACM (2009), 51--60. Google ScholarDigital Library
- Pfeil, U., Zaphiris, P., and Ang, C. S. Cultural Differences in Collaborative Authoring of Wikipedia. Journal of Computer-Mediated Communication 12, 1 (2006), 88--113.Google ScholarCross Ref
- Priedhorsky, R., Lam, S., Panciera, K., Terveen, L., and Riedl, J. Creating, Destroying, and Restoring Value in Wikipedia. In Proc. of GROUP, ACM (2007), 259--268. Google ScholarDigital Library
- Priedhorsky, R., Masli, M., and Terveen, L. Eliciting and Focusing Geographic Volunteer Work. In Proc. of CSCW, ACM (2010), 61--70. Google ScholarDigital Library
- Quattrone, G., Mashhadi, A., and Capra, L. Mind the Map: The Impact of Culture and Economic Affluence on Crowd-Mapping Behaviours. In Proc. of CSCW, ACM (2014), 934--944. Google ScholarDigital Library
- Reinecke, K., Nguyen, M. K., Bernstein, A., Näf, M., and Gajos, K. Doodle Around the World: Online Scheduling Behavior Reflects Cultural Differences in Time Perception and Group Decision-Making. In Proc. of CSCW, ACM (2013), 45--54. Google ScholarDigital Library
- Rost, M., Barkhuus, L., Cramer, H., and Brown, B. Representation and Communication: Challenges in Interpreting Large Social Media Datasets. In Proc. of CSCW, ACM (2013), 357--362. Google ScholarDigital Library
- Shannon, C. A Mathematical Theory of Communication. The Bell System Technical Journal 27 (1948), 379--423 and 623--656.Google ScholarCross Ref
- Singhal, A. Modern Information Retrieval: A Brief Overview. Bulletin of the IEEE Computer Society Technical Committee on Data Engineering 24, 4 (2001), 35--43.Google Scholar
- Stephens, M. Gender and the GeoWeb: Divisions in the Production of User-Generated Cartographic Information. GeoJournal (2013), 1--16.Google Scholar
- Vasconcelos, M., Ricci, S., Almeida, J., Benevenuto, F., and Almeida, V. Tips, Dones and ToDos: Uncovering User Profiles in FourSquare. In Proc. of WSDM, ACM (2012), 653--662. Google ScholarDigital Library
- Zielstra, D., and Zipf, A. A Comparative Study of Proprietary Geodata and Volunteered Geographic Information for Germany. In Proc. of AGILE (2010).Google Scholar
Index Terms
- There's No Such Thing as the Perfect Map: Quantifying Bias in Spatial Crowd-sourcing Datasets
Recommendations
Mind the map: the impact of culture and economic affluence on crowd-mapping behaviours
CSCW '14: Proceedings of the 17th ACM conference on Computer supported cooperative work & social computingCrowd-mapping is a form of collaborative work that empowers citizens to collect and share geographic knowledge. OpenStreetMap (OSM) is a successful example of such paradigm, where the goal of building and maintaining an accurate global map of the ...
Work Always in Progress: Analysing Maintenance Practices in Spatial Crowd-sourced Datasets
CSCW '17: Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social ComputingCrowd-mapping is a form of collaborative work that empowers users to share geographic knowledge. Despite geographic information being intrinsically evolving, little research has so far gone into analysing maintenance practices in these domains. In this ...
Exploring Maintenance Practices in Crowd-Mapping
HT '16: Proceedings of the 27th ACM Conference on Hypertext and Social MediaCrowd-mapping is a form of collaborative work that empowers users to gather and share geographic knowledge. OpenStreetMap is one of the most successful examples of such paradigm, where the goal of building a global map of the world is collectively ...
Comments