IDEAS home Printed from https://ideas.repec.org/a/gam/jftint/v8y2016i2p12-d68419.html
   My bibliography  Save this article

A Method for Assessing the Performance of e-Government Twitter Accounts

Author

Listed:
  • Konstantinos Antoniadis

    (Department of International and European Studies, University of Macedonia, Egnatia 156, Thessaloniki 54006, Greece)

  • Kostas Zafiropoulos

    (Department of International and European Studies, University of Macedonia, Egnatia 156, Thessaloniki 54006, Greece)

  • Vasiliki Vrana

    (Department of Business Administration, Technological Education Institute of Central Macedonia, Terma Magnesias, Serres 62124, Greece)

Abstract

This paper introduces a method for assessing the influence of Twitter accounts of central e-government agencies. It first stresses the importance of activity and popularity of the e-government accounts, and also the importance of community formation among followers-citizens, as the two main stages of e-government adoption. The proposed approach combines activity and popularity of the accounts and followers’ community characteristics in a ranking system, using an idea originally introduced to measure blogosphere authority. A Twitter Authority Index is produced. The method is demonstrated through an extended example: 56 Twitter accounts of ministries of EU countries are sorted according to their indexes in the proposed ranking system. Detailed values for the ministries’ accounts and average values for the countries that the ministries belong to are reported and commented.

Suggested Citation

  • Konstantinos Antoniadis & Kostas Zafiropoulos & Vasiliki Vrana, 2016. "A Method for Assessing the Performance of e-Government Twitter Accounts," Future Internet, MDPI, vol. 8(2), pages 1-18, April.
    • Handle: RePEc:gam:jftint:v:8:y:2016:i:2:p:12-:d:68419
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1999-5903/8/2/12/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1999-5903/8/2/12/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. repec:cup:cbooks:9780511771576 is not listed on IDEAS
    2. A. Barrat & M. Weigt, 2000. "On the properties of small-world network models," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 13(3), pages 547-560, February.
    3. Easley,David & Kleinberg,Jon, 2010. "Networks, Crowds, and Markets," Cambridge Books, Cambridge University Press, number 9780521195331.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Blazquez-Soriano, Amparo & Ramos-Sandoval, Rosmery, 2022. "Information transfer as a tool to improve the resilience of farmers against the effects of climate change: The case of the Peruvian National Agrarian Innovation System," Agricultural Systems, Elsevier, vol. 200(C).
    2. Martin L. Weitzman, 2015. "A Voting Architecture for the Governance of Free-Driver Externalities, with Application to Geoengineering," Scandinavian Journal of Economics, Wiley Blackwell, vol. 117(4), pages 1049-1068, October.
    3. Wei Zhong, 2017. "Simulating influenza pandemic dynamics with public risk communication and individual responsive behavior," Computational and Mathematical Organization Theory, Springer, vol. 23(4), pages 475-495, December.
    4. Guo Weilong & Minca Andreea & Wang Li, 2016. "The topology of overlapping portfolio networks," Statistics & Risk Modeling, De Gruyter, vol. 33(3-4), pages 139-155, December.
    5. Thomas J. Sargent & John Stachurski, 2022. "Economic Networks: Theory and Computation," Papers 2203.11972, arXiv.org, revised Jul 2022.
    6. Bernd (B.) Heidergott & Jia-Ping Huang & Ines (I.) Lindner, 2018. "Naive Learning in Social Networks with Random Communication," Tinbergen Institute Discussion Papers 18-018/II, Tinbergen Institute.
    7. Johannes M. Bauer & Michael Latzer, 2016. "The economics of the Internet: an overview," Chapters, in: Johannes M. Bauer & Michael Latzer (ed.), Handbook on the Economics of the Internet, chapter 1, pages 3-20, Edward Elgar Publishing.
    8. Kobayashi, Teruyoshi & Takaguchi, Taro, 2018. "Identifying relationship lending in the interbank market: A network approach," Journal of Banking & Finance, Elsevier, vol. 97(C), pages 20-36.
    9. Maness, Michael & Cirillo, Cinzia, 2016. "An indirect latent informational conformity social influence choice model: Formulation and case study," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 75-101.
    10. Bauer, Johannes M., 2014. "Platforms, systems competition, and innovation: Reassessing the foundations of communications policy," Telecommunications Policy, Elsevier, vol. 38(8), pages 662-673.
    11. Julia Neidhardt & Nataliia Rümmele & Hannes Werthner, 0. "Predicting happiness: user interactions and sentiment analysis in an online travel forum," Information Technology & Tourism, Springer, vol. 0, pages 1-19.
    12. OKUBO Toshihiro & ONO Yukako & SAITO Yukiko, 2014. "Roles of Wholesalers in Transaction Networks," Discussion papers 14059, Research Institute of Economy, Trade and Industry (RIETI).
    13. Glover, Dominic & Kim, Sung Kyu & Stone, Glenn Davis, 2020. "Golden Rice and technology adoption theory: A study of seed choice dynamics among rice growers in the Philippines," Technology in Society, Elsevier, vol. 60(C).
    14. Yue Chen & Xiaojian Niu & Yan Zhang, 2019. "Exploring Contrarian Degree in the Trading Behavior of China's Stock Market," Complexity, Hindawi, vol. 2019, pages 1-12, April.
    15. Daron Acemoglu & Victor Chernozhukov & Iván Werning & Michael D. Whinston, 2021. "Optimal Targeted Lockdowns in a Multigroup SIR Model," American Economic Review: Insights, American Economic Association, vol. 3(4), pages 487-502, December.
    16. Mark Braverman & Jing Chen & Sampath Kannan, 2016. "Optimal Provision-After-Wait in Healthcare," Mathematics of Operations Research, INFORMS, vol. 41(1), pages 352-376, February.
    17. Lomi, Alessandro & Fonti, Fabio, 2012. "Networks in markets and the propensity of companies to collaborate: An empirical test of three mechanisms," Economics Letters, Elsevier, vol. 114(2), pages 216-220.
    18. Zhang, Xuxi & Liu, Xianping & Lewis, Frank L. & Wang, Xia, 2020. "Bipartite tracking consensus of nonlinear multi-agent systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    19. Venkat Venkatasubramanian & Yu Luo, 2018. "How much income inequality is fair? Nash bargaining solution and its connection to entropy," Papers 1806.05262, arXiv.org.
    20. Bing Han & Liyan Yang, 2013. "Social Networks, Information Acquisition, and Asset Prices," Management Science, INFORMS, vol. 59(6), pages 1444-1457, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jftint:v:8:y:2016:i:2:p:12-:d:68419. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.