+ Annual Meeting New York, February 24 -28, 2012 Monica Stephens, University of Arizona (USA)Antonella Rondinone, Università di Siena (Italy) Gendering the GeoWeb Analysing demographic difference in user generated geographic information
Distribution of Wikipedia Articles FIN MMR SWE Nepal TUR AZECanada China BGD THA ISR Iran PAK PHL NOR MYS India IDN Asia 124,365 articles Japan United Kingdom DNK Russia EST Australia NZL IRL Netherlands Oceania 37,749 articles LTU Antarctica 7,833 articles Poland Ukraine BEL Germany CZE SVK HUN Switzerland Austria SVN Romania HRV Serbia Bulgaria Europe Spain France Italy BIH 775,867 GreeceUnited States articlesNorth America and Caribbean342,297 articles Mexico Mali ETH KenyaBrazil South Africa Fewer than 100 articles per million people ARG size of 100 999 articles per million people ChileS. America Africa 20,000 1,000 5,000 articles per million people 26,812articles 27,666 articles articles More than 5,000 articles per million people Geotagged articles per person
Geographic Distribution of User-Generated Content in Google Canada Norway FIN TUR United Kingdom Denmark SWE IRL Netherlands China IND Poland Russia Germany EST BEL CZE LVA Austria SVK Hungry UKR THA MYS IDN PHL ROU Korea Japan PRT HRV NZL France Italy BGR Spain Switzerland GRC Asia & Australia Europe Pacific ZAF Africa United States Mexico Peru 1 million Fewer than More than 5,000 websites 150,000 websites Brazil links to Latin America Georeferenced per million people per million people& Caribbean CHL ARG Content *Nations with less than 60,000 hits were removed from this map.
Digital Divide Access to Technology Digital Literacy Distribution of Resources Economic Divisions
“The enormous virtual dimension to place has been created by specific demographic segments, and as a consequence manyopinions and viewpoints have likely been left unsaid, just as many places remain virtually hidden and invisible.” M. Graham (2009)
+ How are men and women contributing information differently?
Gender divisions in user-generated content 42% of all American adults use Wikipedia for information (53% of internet users)1 Wikipedia readers (30.5% female, 69% male)2 Wikipedia contributors (12.6% female, 86.7% male)2 OpenStreetMap contributors (3% female, 96% male)3 Twitter users (55% female, 45% male)4 Facebook users (48->54% female, 42.5% male)5,7 Foursquare users (60% female, 40% male)6 Google+ (13% female, 87% male)8 Flickr (55% female, 45% male)9 Information is beautiful: Who rules the social web (2009)
+ How are men and women contributing geographic information differently?
Geographic user-generated content NON- Female Male GEOGRAPHIC: FEMALES Tagged a picture on Flickr or Picasa? 47% 39% CONTRIBUTE Tagged a picture on a social network? 77% 68% WEB Female Male APPLICATIONS Uploaded a picture taken with an integrated GPS device to PRODUCING a social network 37% 46% GEOGRAPHIC Uploaded a picture taken with an integrated GPS device to 37% 27% CONTENT: FEW a photosharing service FEMALES geotagged a picture on a social network 26% 41% CONTRIBUTE geotagged a picture on Flickr or Picasa 40% 30% Female Male WEB CARTOGRAPHIC Open Street Map - Create new maps 19% 34% DEVELOPMENT: Google Maps - Create new maps 23% 19% MOSTLY MALE GENERATED Open Street Map - Contribute to existing maps 19% 41% CONTENT Google Maps? - Contribute to existing maps 4% 8%Based on a survey of 1175 responses; 557 men, 548 women, 70 other; slight bias towards higher education
We define VGI as “that subset of [user-generated content] thatconcerns the characterization of the geographic domain” S. Elwood, M. Goodchild & D. Sui, 2011
“Voluntereed” Geographic Information Categorized by degree of intention by those who generate it Users Toll Booth unknowingly transponders,Digital footprints produce geographic cell phones, IP Mapping, Credit information Cards, etc Web applications Users that produce unintentionally produce Social networks, Photosharing geolocalized geographic etc. information information Users intentionallyWeb cartographic create or OpenStreetMap, Google Maps, application contribute to geographic Wikimapia etc. information
+ VGI Contributions by Gender χ2 All user-generated content (cartographic and non-cartographic) α = 0.01 χ2 Unintentional VGI χ2 test statistic =103.168 α = 0.01 Critical χ2 value = 26.1245 χ2 Test statistic = 29.9536 p-value = 0.00000 Critical χ2 value = 20.51500 P-value = .00001 χ2 cartographic Information α = 0.01 χ2 test statistic = 53.2095 Critical χ2 value = 20.5150 p-value = 0.00000 footprints cartographic non-cartographic
Of males and females participating in social networking sites Reasons for not contributing geotagged social Female men data: Privacy 24% 16% Do not know how to do ‘it’ 28% 15% No need/no interest 37% 46% Lack of technology 5% 11% Other 7% 12%Of those aware of cartographic opportunities in OSM and GoogleMapReasons for not contributing to web-cartographicapplications: Female MaleI don’t know what to do with it 18% 6%I don’t need it 16% 4%I don’t have time 5% 3% Of those who have contributed to OpenStreetMap Reasons for contributing to OpenStreetMap: Female Male It is useful for me 82% 80% It can be useful to somebody else 25% 51% It is fun to contribute 36% 51%
Of males and females participating in social networking sites Reasons for not contributing geotagged social Female men data:“Private things should belong to Privacy 24% 16% Do not know how to do ‘it’ 28% 15%private space and information No need/no interest 37% 46%once given to the internet can Lack of technology Other 5% 7% 11% 12%never be deleted.” – Anonymous femaleOf those aware of cartographic opportunities in OSM and GoogleMapReasons for not contributingwhy she doesn’t contribute respondent explaining to web-cartographic socialapplications: Female MaleinformationI don’t know what to do with it 18% 6%I don’t need it 16% 4%“Because it is community createdI don’t have time 5% 3% Of those who have contributed to OpenStreetMaprathercontributing to commercial Female MaleReasons for than a OpenStreetMap:product”--Anonymous male respondent explaining It is useful for me It can be useful to somebody else 82% 25% 80% 51%why he contributeIt is fun to contributes to OpenStreetMap 36% 51%
“The exclusion and under- representation of information from and about marginalized people and places in existing data records is linked to the ensuing exclusion oftheir needs and priorities from policy and decision making processes” S. Elwood, 2008
Results: User generated content is unevenly distributed geographically This has implication on how places are represented Women are volunteering non geographic social information on the internet but are not intentionally volunteering geographic information even within a social context Menare the primary constructors of the world view that is represented by volunteered geographic information Women are loosing in this contest of describing/ constructing the material world in virtual space
firstname.lastname@example.org email@example.comSpecial Thanks: School of Geography & Development, University of Arizona Graduate and Professional Student Council, University of Arizona Università di Siena, Italy Università di Firenze, Italy Vespucci Initiative for Volunteered Geographic Information, Italy New Mappings Collaboratory, University of Kentucky