1. +
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

2. Producing Web 2.0

5. Distribution of Wikipedia Articles
FIN MMR
SWE Nepal
TUR AZE
Canada 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 Greece
United States articles
North America and Caribbean
342,297 articles
Mexico
Mali ETH
Kenya
Brazil
South
Africa
Fewer than 100 articles per million people
ARG size of
100 ­ 999 articles per million people
Chile
S. America Africa
20,000 1,000 ­ 5,000 articles per million people
26,812
articles
27,666
articles articles More than 5,000 articles per million people
Geotagged articles per person

6. 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.

7. Digital Divide
 Access to Technology  Digital Literacy
 Distribution of Resources  Economic Divisions

8. “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)

10. + How are men and women
contributing information
differently?

11. 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)

12. + How are men and women
contributing geographic
information differently?

13. 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

14. 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

15. “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
intentionally
Web cartographic create or
OpenStreetMap,
Google Maps,
application contribute to
geographic
Wikimapia etc.
information

16. + 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

17. 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 GoogleMap
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 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%

18. 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 female
Of those aware of cartographic opportunities in OSM and GoogleMap
Reasons for not contributingwhy she doesn’t contribute
respondent explaining to web-cartographic social
applications: Female Male
information
I don’t know what to do with it 18% 6%
I don’t need it 16% 4%
“Because it is community created
I don’t have time 5% 3%
Of those who have contributed to OpenStreetMap
rathercontributing to commercial Female Male
Reasons 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 contribute
It is fun to
contributes to OpenStreetMap 36% 51%

19. “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

20. 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

21. mstephe@email.arizona.edu
rondinone@unisi.it
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