gendering the geoweb
TRANSCRIPT
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Gendering the GeoWeb Analysing demographic difference in user
generated geographic information
Monica Stephens, University of Arizona (USA) Antonella Rondinone, Università di Siena (Italy)
Annual Meeting New York, February 24 -28, 2012
Producing Web 2.0
United Kingdom
Poland
Germany
Netherlands
France
Russia
Spain
UkraineBEL
Italy
CZE
Switzerland
NOR
Austria
SWE
Romania
LTU
DNK
SVN
EST
Bulgaria
BIH
FIN
Serbia
Greece
HRV
SVKHUN
IRL
United States
Canada
Mexico
JapanIndia
ChinaAZETUR
ISR
Nepal
PAKIran PHL
IDN
THA
MMR
BGD
MYS
SouthAfrica
Kenya
ETHMali
Brazil
ARGChile
Africa27,666articles
North America and Caribbean342,297 articles
S. America26,812articles
Europe775,867articles
Asia124,365 articles
Australia NZLOceania 37,749 articles
Antarctica7,833 articles
size of20,000articles
1,000 5,000 articles per million people 100 999 articles per million people Fewer than 100 articles per million people
More than 5,000 articles per million people
Geotagged articles per person
Distribution of Wikipedia Articles
Geographic Distribution of User-Generated Content in Google
United States
Canada
Germany
United Kingdom
Netherlands
France
Poland
Italy
Russia
Spain Switzerland
BEL
SWE
Austria Hungry
Norway
Denmark
CZE
IRL
SVK
PRT
FIN
ROU
EST
GRC
HRV
UKR
LVA
BGR
ZAF
MexicoPeru
BrazilARGCHL
JapanKorea
China
Australia
IND
THA MYS
TUR
NZL
PHLIDN
1 millionlinks to
GeoreferencedContent
Fewer than 5,000 websitesper million people
*Nations with less than 60,000 hits were removed from this map.
Latin America& Caribbean
Africa
EuropeAsia &Pacific
More than 150,000 websites
per million people
Digital Divide Access to Technology
Distribution of Resources
Digital Literacy
Economic Divisions
“The enormous virtual dimension to place has been created by specific demographic
segments, and as a consequence many opinions 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?
Information is beautiful: Who rules the social web (2009)
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
Gender divisions in user-generated content
+ How are men and women contributing geographic information differently?
Geographic user-generated content Female Male
Tagged a picture on Flickr or Picasa? 47% 39%
Tagged a picture on a social network? 77% 68%
Female Male Uploaded a picture taken with an integrated GPS device to a social network 37% 46% Uploaded a picture taken with an integrated GPS device to a photosharing service 37% 27%
geotagged a picture on a social network 26% 41%
geotagged a picture on Flickr or Picasa 40% 30%
Female Male
Open Street Map - Create new maps 19% 34%
Google Maps - Create new maps 23% 19%
Open Street Map - Contribute to existing maps 19% 41%
Google Maps? - Contribute to existing maps 4% 8%
NON-GEOGRAPHIC: FEMALES CONTRIBUTE
WEB CARTOGRAPHIC DEVELOPMENT: MOSTLY MALE GENERATED CONTENT
WEB APPLICATIONS PRODUCING GEOGRAPHIC CONTENT: FEW FEMALES CONTRIBUTE
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] that
concerns the characterization of the geographic domain”
S. Elwood, M. Goodchild & D. Sui, 2011
“Voluntereed” Geographic Information
Digital footprints Users
unknowingly produce
geographic information
Toll Booth transponders, cell phones, IP
Mapping, Credit Cards, etc
Web applications that produce geolocalized information
Users unintentionally
produce geographic information
Social networks, Photosharing
etc.
Web cartographic application
Users intentionally
create or contribute to geographic information
OpenStreetMap, Google Maps, Wikimapia etc.
Categorized by degree of intention by those who generate it
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χ2 Unintentional VGI α = 0.01 χ2 Test statistic = 29.9536 Critical χ2 value = 20.51500 P-value = .00001
χ2 All user-generated content (cartographic and non-cartographic) α = 0.01 χ2 test statistic =103.168 Critical χ2 value = 26.1245 p-value = 0.00000
footprints cartographic non-cartographic
VGI Contributions by Gender
χ2 cartographic Information α = 0.01 χ2 test statistic = 53.2095 Critical χ2 value = 20.5150 p-value = 0.00000
I don't like the idea of annoynmous knowing where I am at any paticular moment.
Reasons for not contributing geotagged social data:
Female men
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 males and females participating in social networking sites
Reasons for not contributing to web-cartographic applications: Female Male
I 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 aware of cartographic opportunities in OSM and GoogleMap
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 those who have contributed to OpenStreetMap
I don't like the idea of annoynmous knowing where I am at any paticular moment.
Reasons for not contributing geotagged social data:
Female men
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 males and females participating in social networking sites
Reasons for not contributing to web-cartographic applications: Female Male
I 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 aware of cartographic opportunities in OSM and GoogleMap
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 those who have contributed to OpenStreetMap
“Private things should belong to private space and information once given to the internet can never be deleted.” – Anonymous female respondent explaining why she doesn’t contribute social information
“Because it is community created rather than a commercial product”--Anonymous male respondent explaining why he contributes to OpenStreetMap
“The exclusion and under-representation of information from
and about marginalized people and places in existing data records is linked to the ensuing exclusion of
their 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
Men are 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
Special 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