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WEBOMETRICSINSTITUTE
Geo-information and Twitter Use
An Analysis of Top Twitterians’ Profiles
Yon Soo Lim, Jiyoung Park, Jiyoung Kim, Han Woo ParkWCU Webometrics Institutute
Yeungnam [email protected]
International Conference on e-CASE & e-Tech 2011, Tokyo, Japan
Introduction The growth of social network sites (SNSs)
Facebook, Myspace, Cyworld, Mixi, Orkut, etc
Internet as social media: Interactive communication Expansion of social networks / Diffusion and sharing
of information
New SNSs platform, Twitter Micro-blogging service Since launched in 2006, Twitter currently has more
than 100 million users across the world.
Introduction Twitter is becoming a major research topic in
Internet studies, but it is still in a beginning stage.
This study aims to explore a pattern of Twitter use regarding top twittarians.
Specifically, it examines the relationships be-tween twitter use and users’ profiles.
Theoretical arguments on SNSs use Self-disclosure
A key factor SNSs use is sociability. Sociability is related to extraversion (human char-
acteristic). Extraverted users are more willing to self-disclose
than introverted ones. Also, they may be more active communicators in
SNS environment. Knowledge gap (digital divide)
Regarding new technology adoption and diffusion, Urban area > rural area Metropolitan area > small city area
Twitter Features Twitter profile can be modified by users.
Some people disclose everything to the public. Other people hide themselves.
User difference can be easily identified by the existence of Location.
Also, the geo-information can indicate area size (#population) in which users lives.
Twitter Features Although the profiles are different, other fea-
tures (#followers, #following, #tweets) are automatically provided by Twitter.com.
Twitter use #followers: popularity #following: social networking #tweets: communication activity
Research Questions
Regarding Twitter use,
[Self-disclosure] RQ1. What are the differences
between geographically identified users and
non-identified users?
[Digital divide] RQ2. What are the differences
between great metropolitan area and small
city area?
Method Data
Source: Social Media Rank for Twitter from spinn3r (http://spinn3r.com/rank)
Top 1,000 twitterian list were generated on June 13, 2009.
964 twitterians were considered for this study 36 twitter accounts were disappeared.
Gathering user profiles Twitter scraper: an API-based program by WWI
Location, #following, #follower, #tweet Manual coding
(Metropolitan) area population for each user Reference: each country’s national statistics
Method Location info.
Non-identified: 324 users Identified: 640 users
Great metropolitan area: 317 users Other city area: 323 users
(Criterion population#: 5,000,000: sample me-dian)
Analysis strategy Mann-Whitney U test Identify the relationships between geographic in-
formation and twitter use (#following, #follower, #tweet)
ResultsCountry Count Australia 2 Belgium 1 Bosnia and Herzegovina 1 Canada 11 China 1 Czech 1 Dubai 1 France 3 Germany 4 India 1 Iran 3 Italy 4 Japan 1 Jordan 1 Mexico 1 Netherlands 2 Slovenia 1 Sweden 1 Switzerland 1 UK 48 USA 551 Total 640
Country City Count
Canada Toronto 3
China Nanjing 1
France Paris 3
Germany Berlin 1
München 1
India Bangalore 1
Iran Tehran 3
Japan Tokyo 1
UK London 28
USA Atlanta 3
Chicago 13
Dallas 6
Houston 2
Los Angeles 91
Miami 1
New York City 126
Philadelphia 5
Washington DC 28
Total 317
Geo-info by coun-
try
Great metro area
Results
Results of the Mann-Whitney U test regarding geographic information
Geo-info N Mean U test
Rank χ 2 p
Follower Non-Geo 324 438.66 3.478 0.001
Identified 640 504.69
Following Non-Geo 324 381.02 8.052 0.000
Identified 640 533.87
Tweet Non-Geo 324 405.12 6.139 0.000
Identified 640 521.67
Results
Results of the Mann-Whitney U test regarding local area size
Area size N Mean U test
Rank χ 2 p
Follower Great-metro 317 366.94 6.295 0.000
Small 323 274.92
Following Great-metro 317 292.26 -3.827 0.000
Small 323 348.21
Tweet Great-metro 317 303.14 -2.353 0.019
Small 323 337.54
Discussion This study examined the relationships be-
tween top Twitter users’ geo-information and their usage.
Findings US citizens are dominated in top ranked twittari-
ans. Users who provide location info. are more actively
use of Twitter. Users in great metropolitan area have more popu-
larity (#followers) than users in other city area. Users in other city area are more active to make
social relationships (#following) and communicate with others (#tweets) than users in great metro-politan area.
Discussion From these findings, this study suggest:
Self-disclosure can be a key factor in Twitter use.
City size in which users lives can be a determi-nant of Twitter use.
Regarding Twitter use, geographic digital divide and information dependency should be more examined in future research.
