IDEAS home Printed from https://ideas.repec.org/a/spr/qualqt/v51y2017i3d10.1007_s11135-016-0330-5.html
   My bibliography  Save this article

Rhetorical manifestation of institutional transformation

Author

Listed:
  • Stefano Sbalchiero

    (University of Padova)

  • Maria Stella Righettini

    (University of Padova)

Abstract

The present study proposes an analysis process to compare and contrast different approaches to content analysis. Moving from previous findings (Righettini and Sbalchiero, ICPP—international conference on public policy, 2015), related to consumer protection in the annual speeches of Italian Presidents of AGCOM, delivered between 2000 and 2015, statistical analyses of textual data are applied on the same set of texts in order to compare and contrast results and evaluate the opportunity of integrating different approaches to enrich the results. This review of results resorts to topic based methods for classification of context units (Reinert, Les Cah l’Anal Donnees 8(2):187–198, 1983), text clustering and lexical correspondence analysis (Lebart et al., Exploring textual data, 1998) in a general framework of content analysis and “lexical worlds” exploration (Reinert, Lang Soc 66:5–39, 1993), i.e., the identification of main topics and words used by AGCOM Presidents to talk about consumer protection. Results confirm the strengths and opportunities of topics detection approach and shed light on how quantitative methods might become useful to political scientists when available policy documents increase in number and size. One methodological innovation of this article is that it supplements the use of word categories in traditional content analysis with an automated topics analysis which exceeds the problems of reliability, replicability, and inferential circularity.

Suggested Citation

  • Stefano Sbalchiero & Maria Stella Righettini, 2017. "Rhetorical manifestation of institutional transformation," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(3), pages 1279-1296, May.
    • Handle: RePEc:spr:qualqt:v:51:y:2017:i:3:d:10.1007_s11135-016-0330-5
    DOI: 10.1007/s11135-016-0330-5
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11135-016-0330-5
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11135-016-0330-5?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Brian Everitt, 1980. "Cluster analysis," Quality & Quantity: International Journal of Methodology, Springer, vol. 14(1), pages 75-100, January.
    2. Michael Laver, 1998. "Party Policy in Britain 1997: Results from an Expert Survey," Political Studies, Political Studies Association, vol. 46(2), pages 336-347, June.
    3. Carl Roberts, 2000. "A Conceptual Framework for Quantitative Text Analysis," Quality & Quantity: International Journal of Methodology, Springer, vol. 34(3), pages 259-274, August.
    4. Efstathios Stamatatos, 2009. "A survey of modern authorship attribution methods," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(3), pages 538-556, March.
    5. Moshe Koppel & Jonathan Schler & Shlomo Argamon, 2009. "Computational methods in authorship attribution," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(1), pages 9-26, January.
    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. Matthew J. Schneider & Shawn Mankad, 2021. "A Two-Stage Authorship Attribution Method Using Text and Structured Data for De-Anonymizing User-Generated Content," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 8(3), pages 66-83, September.
    2. Kargin, Vladislav, 2016. "On variation of word frequencies in Russian literary texts," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 445(C), pages 328-334.
    3. Haoran Zhu & Lei Lei, 2022. "The Research Trends of Text Classification Studies (2000–2020): A Bibliometric Analysis," SAGE Open, , vol. 12(2), pages 21582440221, April.
    4. Silvia Corbara & Alejandro Moreo & Fabrizio Sebastiani, 2023. "Syllabic quantity patterns as rhythmic features for Latin authorship attribution," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 74(1), pages 128-141, January.
    5. de Arruda, Henrique F. & Marinho, Vanessa Q. & Lima, Thales S. & Amancio, Diego R. & Costa, Luciano da F., 2018. "An image analysis approach to text analytics based on complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 110-120.
    6. Jabbar, Amina M. & Abelson, Julia, 2011. "Development of a framework for effective community engagement in Ontario, Canada," Health Policy, Elsevier, vol. 101(1), pages 59-69, June.
    7. Armèn Hakhverdian, 2009. "Capturing Government Policy on the Left–Right Scale: Evidence from the United Kingdom, 1956–2006," Political Studies, Political Studies Association, vol. 57(4), pages 720-745, December.
    8. James Tilley & Christopher Wlezien, 2008. "Does Political Information Matter? An Experimental Test Relating to Party Positions on Europe," Political Studies, Political Studies Association, vol. 56(1), pages 192-214, March.
    9. Zeev Volkovich, 2020. "A Short-Patterning of the Texts Attributed to Al Ghazali: A “Twitter Look” at the Problem," Mathematics, MDPI, vol. 8(11), pages 1-16, November.
    10. Dalibor Stanimirovic & Eva Murko & Tadej Battelino & Urh Groselj & Mojca Zerjav Tansek, 2021. "Towards a Comprehensive Strategy for the Management of Rare Diseases in Slovenia: Outlining an IT-Enabled Ecosystemic Approach," IJERPH, MDPI, vol. 18(23), pages 1-17, November.
    11. Nils-Axel M?rner, 2018. "Evaluation of the Performance and Efficiency of the Automated Linguistic Features for Author Identification in Short Text Messages Using Different Variable Selection Techniques," Studies in Media and Communication, Redfame publishing, vol. 6(2), pages 83-102, December.
    12. Shern, David L. & Trochim, William M. K. & LaComb, Christina A., 1995. "The use of concept mapping for assessing fidelity of model transfer: An example from psychiatric rehabilitation," Evaluation and Program Planning, Elsevier, vol. 18(2), pages 143-153.
    13. Julia Gray & Jonathan Slapin, 2012. "How effective are preferential trade agreements? Ask the experts," The Review of International Organizations, Springer, vol. 7(3), pages 309-333, September.
    14. Lawrence, John D. & Kaylen, Michael S., 1990. "Risk Management For Livestock Producers: Hedging And Contract Production," Staff Papers 13496, University of Minnesota, Department of Applied Economics.
    15. Maryam Ebrahimpour & Tālis J Putniņš & Matthew J Berryman & Andrew Allison & Brian W-H Ng & Derek Abbott, 2013. "Automated Authorship Attribution Using Advanced Signal Classification Techniques," PLOS ONE, Public Library of Science, vol. 8(2), pages 1-12, February.
    16. Diego R Amancio, 2015. "Probing the Topological Properties of Complex Networks Modeling Short Written Texts," PLOS ONE, Public Library of Science, vol. 10(2), pages 1-17, February.
    17. Ocelík, Petr & Osička, Jan & Zapletalová, Veronika & Černoch, Filip & Dančák, Břetislav, 2017. "Local opposition and acceptance of a deep geological repository of radioactive waste in the Czech Republic: A frame analysis," Energy Policy, Elsevier, vol. 105(C), pages 458-466.
    18. Jaroslav Ráček & Jan Ministr, 2014. "Tools for Automatic Recognition of Persons and their Relationships in Unstructured Data [Nástroje pro automatické rozpoznávání entit a jejich vztahů v nestrukturovaných textech]," Acta Informatica Pragensia, Prague University of Economics and Business, vol. 2014(3), pages 280-287.
    19. Filosa Gita Sukmono & Fajar Junaed & Qholiva Yuni Fadilla & Mohammad Jafar Loilatu & Dani Fadillah, 2023. "News about the Sunda Strait Tsunami Disaster: From the Selection of News Sources to the Production Process," Studies in Media and Communication, Redfame publishing, vol. 11(4), pages 10-18, June.
    20. Rosas, Scott R. & Ridings, John W., 2017. "The use of concept mapping in measurement development and evaluation: Application and future directions," Evaluation and Program Planning, Elsevier, vol. 60(C), pages 265-276.

    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:spr:qualqt:v:51:y:2017:i:3:d:10.1007_s11135-016-0330-5. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.