Your SlideShare is downloading. ×
Associating e-government and e-participation indexes with governmental twitter accounts performance in eu-countries
Upcoming SlideShare
Loading in...5
×

Thanks for flagging this SlideShare!

Oops! An error has occurred.

×

Saving this for later?

Get the SlideShare app to save on your phone or tablet. Read anywhere, anytime - even offline.

Text the download link to your phone

Standard text messaging rates apply

Associating e-government and e-participation indexes with governmental twitter accounts performance in eu-countries

516
views

Published on

Copyright Kostas Zafiropoulos at CeDEM14

Copyright Kostas Zafiropoulos at CeDEM14


0 Comments
1 Like
Statistics
Notes
  • Be the first to comment

No Downloads
Views
Total Views
516
On Slideshare
0
From Embeds
0
Number of Embeds
4
Actions
Shares
0
Downloads
0
Comments
0
Likes
1
Embeds 0
No embeds

Report content
Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
No notes for slide

Transcript

  • 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…