This study analyzed the Twitter accounts of government agencies in 24 EU countries to determine if their social media performance correlates with the countries' overall e-government and e-participation indexes. Twitter data was collected for central government accounts and several ministries from each country. Performance metrics like followers, retweets, and reach were analyzed and aggregated at the country level. Principal component analysis identified two factors related to account activity and networking. Correlation analysis found the factors and some individual metrics like tweets and retweets were positively correlated with the UN's e-government and e-participation indexes, suggesting greater social media engagement is aligned with higher online government services and civic participation nationally. The study provides evidence that social media can enhance e-government goals

1. K. Antoniadis, V. Vrana and
K. Zafiropoulos
Univ. of Macedonia-TEI of Central Macedonia,
Greece

2. Literature:Literature: Social media have changed the way citizens get informed
about government activities, global and national events and what is
happening in their communities
Literature:Literature: Social media help government agencies to connect better with
their stakeholders through engagement and interactivity
In 2012, 40% of the 193 United Nations Member States provide a
statement “follow us on Facebook or Twitter” in government portals
Previous research:Previous research: uses content analysis, Social Networking Analysis to:
congress members, local organizations, Ministries, services such as the
police, but not many comparative studies
FindingsFindings:: government agencies primarily relied on one-way
communication to inform and educate rather than two-way symmetrical
conversations. Findings:Findings: organizations primary use social media for
information sharing and rarely use them to create dialogue

3. A comparative study on EU countriesA comparative study on EU countries.
Cons:Cons: no content is studied, aggregate data used
Pros:Pros: a comparative study, new metrics used (used
before only in e-Business), correlations with e-
government and e-participation indexes
This research aims to find associations among EU
countries governmental Twitter accounts and the
general e-Government and e-Participation indexes
of EU countries:
Twitter performance (networking and activity
characteristics) are correlated with general e-
Government and e-Participation indexes of 24 EU
countries

4. 19-28 February 2013, accounts of 24 EU countries:
for each EU country, we searched the government central website
along with the ministries websites, to find out if they provide links
to Twitter accounts.
These accounts were then recorded for every EU country.
Recorded:
19 countries with central government Twitter accounts
17 countries with accounts for the Ministry of Foreign Affairs
9 for the Ministry of Finance-Economy
9 for the Ministry of Education
9 for the Ministry of Environment
8 for the Ministry of Development
8 for the Ministry of Health

5. Twitter performance indicators proposed in the literature:
followers, following, number of tweets and tweets per dayfollowers, following, number of tweets and tweets per day
Two new performance indexes: Topsy score, and TotalTopsy score, and Total
EffectiveEffective ReachReach
TopsyTopsy scorescore refers to retweets and mentions that matter for
a particular Twitter account as a measure of user’s
community involvement for this account (Topsy.com)
TotalTotal Effective ReachEffective Reach measures the total amount of people
who are exposed to a tweet or its retweets. It multiplies
users and each of the retweeting followers counts by their
calculated influence (the likelihood that the user will be
retweeted or mentioned) to determine a likely and realistic
representation of any user's reach in Twitter at any given
time (twtrland.com).
We summed up total effective reach for the 14 most popular
tweets of each account

6. Each country provides and uses a different
number of e-Government Twitter accounts,
so we calculated the average values of the Twitter
performance indexes (followers, following, tweets,
tweets per day, Topsy score, Total effective reach)
of the Twitter accounts for each country, in order
to have one value for each country.
Since number of followers, following and Totalfollowers, following and Total
effective reacheffective reach depend on each country’s
population, we adjusted the three indexes by
dividing them by the population of each country.
Principal Components Analysis (PCA) was used to
construct overall indexes of Twitter performance.

7. Two general e-Government and e-Participation
official indexes were recorded in order to be
associated with the Twitter performance
indexes: ee--Government development index, eGovernment development index, e--
Participation indexParticipation index ((UN, 2012UN, 2012))
By calculating the correlation coefficients
among the above indexes, we aimed to answer
the papers central question: is Twitter
performance in accordance with the general e-
Government and e-Participation indexes of the
EU countries?

8. The United Nations e-Government development index (2012,
EGDI) is a composite indicator measuring the willingness andmeasuring the willingness and
capacity of national administrations to use information andcapacity of national administrations to use information and
communication technology to deliver public services.communication technology to deliver public services. It is based
on a comprehensive survey of the online presence of all 193
Member States, which assesses the technical features of nationalassesses the technical features of national
websites as well as ewebsites as well as e--Government policies and strategies appliedGovernment policies and strategies applied
in general and by specific sectors for delivery of essential serin general and by specific sectors for delivery of essential servicesvices,
EGDI = (1/3 * online service index) +(1/3 * telecommunication
index) +(1/3 * human capital index)
The e-Participation questions which refer to e-Participation index,
as part of the eas part of the e--Government questionnaire, extend the dimensionGovernment questionnaire, extend the dimension
of the Survey by emphasizing quality in the connected presenceof the Survey by emphasizing quality in the connected presence
stage of estage of e--GovernmentGovernment. The e-Participation index is normalized
by taking their total score values for a given country subtracting
the lowest total score for any country in the Survey and dividing
by the range of total score values for all countries

9. Country Number of
Twitter
accounts
surveyed
Total
effective
reach
(average)
Topsy score
(average)
E-Government
development
index
E-Participation
index
UK 8 816,763 4,035 0.9 0.92
Spain 7 149,311 1,017 0.78 0.5
Greece 7 29,049 58 0.69 0.34
Latvia 7 9,682 201 0.66 0.21
Poland 6 32,395 118 0.64 0.18
Netherlands 5 29,552 496 0.91 1
France 4 28,560 701 0.86 0.58
Finland 4 11,770 102 0.85 0.74
Germany 4 133,783 382 0.81 0.76
Ireland 4 19,892 243 0.71 0.13
Belgium 3 17,754 59 0.77 0.13
Slovenia 3 6,399 170 0.75 0.21
Sweden 2 20,060 118 0.86 0.68
Estonia 2 1,474 24 0.8 0.76
Italy 2 84,666 2,380 0.72 0.26
Romania 2 2,159 12 0.61 0.08
Denmark 1 15,080 305 0.89 0.55
Lithuania 1 1,209 10 0.73 0.53
Portugal 1 16,166 2 0.72 0.37
Hyngary 1 478 41 0.72 0.45
Malta 1 174 12 0.71 0.26
Cyprus 1 185 26 0.65 0.08
Czech
Republic
1 4,786 35 0.65 0.26
Bulgaria 1 2,243 84 0.61 0.03

10. Most countries have 1 to 4 Twitter accounts,
Six countries (UK, Netherlands, Spain, Greece, Latvia and
Poland) have more than four accounts.
Eight accounts for UK.
Countries not recorded (erecorded (e--governmentgovernment developmentdevelopment
indexes):indexes): Luxemburg (0.80), Austria (0.78), Croatia (Luxemburg (0.80), Austria (0.78), Croatia (0.73),0.73),
Slovakia (0.63Slovakia (0.63))
It remains to be explored what their Twitter performance
will be and if it will be in accordance to e-Government and
e-Participation indexes.
A remind:A remind: Number of followers, following and total
effective reach are subject to the population of each country,
while number of tweets is associated with the age of an
account, in the sense that older accounts have more tweets.

11. Principal Component Analysis (PCA) with
Varimax rotation was used for the indexes:
followers, following, tweets, and tweets per day,
Topsy score and Total effective reach:
TwoTwo PC were extractedPC were extracted emplaning 49% and 27% of
the total variance respectively (total 76%).
The first PC is associated with the account activityaccount activity
as recorded by total number of tweets and tweetsas recorded by total number of tweets and tweets
per day, and the citizensper day, and the citizens’’ community activity as itcommunity activity as it
is recorded by indexes of retweeting and spreadingis recorded by indexes of retweeting and spreading
the information.the information.
The second PC is associated with numbernumber ofof
following and followersfollowing and followers.

12. PC 1
account activity
PC 2
networking
Tweets .881.881 .150
Topsy score .874.874 .008
Tweets per day .822.822 -.080
Total Eff Reach .794.794 .332
Following -.094 .876.876
Followers .266 .833.833

13. E-Government
development index
E-Participation
index
Followers .284 (.178) .250 (.239)
Following .015 (.946) -.125 (.562)
Tweets .477 (.018*) .480 (.018*)
Tweets per day .198 (.353) .193 (.367)
Total Effective
Reach
.396 (.055) .355 (.089)
Topsy score .371 (.074) .360 (.084)
PC 1 .419 (.042*) .421 (.040*)
PC 2 .150 (.484) .047 (.827)

14. Twitter usage in general complies with the general countries e-
government and e-participation indexes
Activity and performance on Twitter is in a one-one relation with
the general e-Government and e-Participation development
(sounds obvious but remains to be recoded and documented)
Official e-government and e-participation indexes are constructed
only by considering information regarding government services
and not by taking into account the citizens’ involvement and in
any case not considering Twitter, in our case it is this account’s
and citizens’ involvement and activity, which are significantly
correlated with e-Government and e-Participation
so, performanceso, performance of the Twitter accounts is not only a matter ofof the Twitter accounts is not only a matter of
Twitter accounts (the medium) appearance; it is mainly a matterTwitter accounts (the medium) appearance; it is mainly a matter ofof
citizenscitizens’’ activeactive participationparticipation

15. Limitations:Limitations: Aggregate level of data analysis. (ecological
analysis,… ecological fallacy?) - Content?
Can not prove that the performance of Twitter or other
media, used by governments, is a result (or a cause) of the
general e-Government and e-Participation level of a country.
However, there is evidence that this might not be excluded
from any conclusions drawn:
Twitter does not fail to provide information and to promote
e-Government services and it does not only retain a role of
must-have technological improvement, regardless of its
actual usefulness
Might suggest that e-Government and e-Participation
indexes could be expanded to include such measures and
metrics of citizens’ involvement and activity, regarding
Twitter, and possibly other social media, usage in e-
Government services provision▄

16. Thank you…