IDEAS home Printed from https://ideas.repec.org/a/pal/palcom/v11y2024i1d10.1057_s41599-024-02611-7.html
   My bibliography  Save this article

Comparison and positioning of NGOs aimed at children from the perspective of social marketing on Twitter

Author

Listed:
  • Araceli Galiano-Coronil

    (University of Cadiz)

  • Marina Yong Alcedo-Velázquez

    (University of Cadiz)

  • Sofía Blanco-Moreno

    (University of Leon)

  • Luis Bayardo Tobar Pesántez

    (Politecnica Salesiana University of Ecuador)

Abstract

The role of Non-Governmental Organizations (NGOs) in disseminating and protecting children’s rights is fundamental by increasing society’s knowledge about the reality that children face, thus mobilizing citizen attention. In this paper, we present an original study on social media data, specifically Twitter, to analyze childhood NGOs, evaluating the success of their content (through the likes obtained by publications) from the perspective of social marketing and prospective theory. In addition, it examines the positioning of organizations concerning the types of messages identified. The methodological approach is based on data mining, content analysis, and simple correspondence analysis through which the typology of the messages and positioning map are determined. The results suggest that these organizations generate predictable communication by publishing on specific topics and only increasing the number of tweets in emergencies when they are requiring urgent help. Some tweets show an immediate risk to which children are exposed if they do not receive help, which aligns with one of the premises of the Prospect Theory. Furthermore, a more significant number of posts does not necessarily imply a greater number of likes. Three types of messages have been determined: informative tweets that point out risks (type 1), impartial dialogue tweets (type 2), and action tweets that highlight benefits (type 3), confirmed through the Kruskal-Wallis test to have a relationship with impact. The positioning map shows that type 3 messages, which World Vision Spain opts for, are the most popular, followed by type 1, which Educo leans towards. Finally, there are those of type 2, with which UNICEF Spain is associated. The main implication is that our analysis validates the use of social media such as Twitter to analyze NGOs and proposes these social media platforms to be an important tool in mobilizing the community. In addition, this study offers parameters when constructing the messages for use in social marketing campaigns according to decisions that involve risk or certainty.

Suggested Citation

  • Araceli Galiano-Coronil & Marina Yong Alcedo-Velázquez & Sofía Blanco-Moreno & Luis Bayardo Tobar Pesántez, 2024. "Comparison and positioning of NGOs aimed at children from the perspective of social marketing on Twitter," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-16, December.
  • Handle: RePEc:pal:palcom:v:11:y:2024:i:1:d:10.1057_s41599-024-02611-7
    DOI: 10.1057/s41599-024-02611-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/s41599-024-02611-7
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1057/s41599-024-02611-7?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. de Leeuw, Jan & Mair, Patrick, 2009. "Simple and Canonical Correspondence Analysis Using the R Package anacor," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 31(i05).
    2. Moro, Sérgio & Rita, Paulo & Vala, Bernardo, 2016. "Predicting social media performance metrics and evaluation of the impact on brand building: A data mining approach," Journal of Business Research, Elsevier, vol. 69(9), pages 3341-3351.
    3. Lei Huang & Amelia Clarke & Natalie Heldsinger & Wen Tian, 2019. "The communication role of social media in social marketing: a study of the community sustainability knowledge dissemination on LinkedIn and Twitter," Journal of Marketing Analytics, Palgrave Macmillan, vol. 7(2), pages 64-75, June.
    4. Balaji, M.S. & Jiang, Yangyang & Jha, Subhash, 2021. "Nanoinfluencer marketing: How message features affect credibility and behavioral intentions," Journal of Business Research, Elsevier, vol. 136(C), pages 293-304.
    5. Rodrigo Elías Zambrano & Gloria Jiménez-Marín & Araceli Galiano-Coronil & Rafael Ravina-Ripoll, 2021. "Children, Media and Food. A New Paradigm in Food Advertising, Social Marketing and Happiness Management," IJERPH, MDPI, vol. 18(7), pages 1-14, March.
    6. Gloria Jiménez-Marín & Rodrigo Elías Zambrano & Araceli Galiano-Coronil & Rafael Ravina-Ripoll, 2021. "Business and Energy Efficiency in the Age of Industry 4.0: The Hulten, Broweus and Van Dijk Sensory Marketing Model Applied to Spanish Textile Stores during the COVID-19 Crisis," Energies, MDPI, vol. 14(7), pages 1-10, April.
    7. Ester Guijarro & Cristina Santadreu-Mascarell & Beatriz Blasco-Gallego & Lourdes Canós-Darós & Eugenia Babiloni, 2021. "On the Identification of the Key Factors for a Successful Use of Twitter as a Medium from a Social Marketing Perspective," Sustainability, MDPI, vol. 13(12), pages 1-15, June.
    8. Araceli Galiano-Coronil & Juan José MierTerán-Franco, 2019. "The Use of Social Digital Networks by NGDO from a Social Marketing Perspective," Social Sciences, MDPI, vol. 8(6), pages 1-23, June.
    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. Norbert Bajkó & Zsolt Fülöp & Kinga Nagyné Pércsi, 2022. "Changes in the Innovation- and Marketing-Habits of Family SMEs in the Foodstuffs Industry, Caused by the Coronavirus Pandemic in Hungary," Sustainability, MDPI, vol. 14(5), pages 1-17, March.
    2. Konstantinos Salonitis, 2023. "Manufacturing Energy Efficiency and Industry 4.0," Energies, MDPI, vol. 16(5), pages 1-4, February.
    3. He, Yi & You, Ya & Chen, Qimei, 2020. "Our conditional love for the underdog: The effect of brand positioning and the lay theory of achievement on WOM," Journal of Business Research, Elsevier, vol. 118(C), pages 210-222.
    4. Mustofa Rochman Hadi, 2020. "Is Big Data Security Essential for Students to Understand?," HOLISTICA – Journal of Business and Public Administration, Sciendo, vol. 11(2), pages 161-170, August.
    5. Naomichi Makino, 2022. "Rotation in Correspondence Analysis from the Canonical Correlation Perspective," Psychometrika, Springer;The Psychometric Society, vol. 87(3), pages 1045-1063, September.
    6. Carmen Quiles‐Soler & Alba‐María Martínez‐Sala & Juan Monserrat‐Gauchi, 2023. "Fashion industry's environmental policy: Social media and corporate website as vehicles for communicating corporate social responsibility," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 30(1), pages 180-191, January.
    7. Shahbaznezhad, Hamidreza & Dolan, Rebecca & Rashidirad, Mona, 2021. "The Role of Social Media Content Format and Platform in Users' Engagement Behavior," Journal of Interactive Marketing, Elsevier, vol. 53(C), pages 47-65.
    8. Shianghau Wu, 2020. "A Fuzzy Association Rules Mining Analysis of the Influencing Factors on the Failure of oBike in Taiwan," Mathematics, MDPI, vol. 8(11), pages 1-18, October.
    9. Corina Pelau & Puiu Nistoreanu & Laura Lazar & Ruxandra Badescu, 2022. "Celebrity vs. Product: A Neuroscientific Approach to the Distractors in Food Advertising for Sustainable Marketing," Sustainability, MDPI, vol. 14(19), pages 1-15, October.
    10. Sabih Ahmad Khan & Hsien-Tsung Chang, 2019. "Comparative analysis on Facebook post interaction using DNN, ELM and LSTM," PLOS ONE, Public Library of Science, vol. 14(11), pages 1-26, November.
    11. Lauri Valkonen & Jouni Helske & Juha Karvanen, 2023. "Estimating the causal effect of timing on the reach of social media posts," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 32(2), pages 493-507, June.
    12. Schaefers, Tobias & Falk, Tomas & Kumar, Ashish & Schamari, Julia, 2021. "More of the same? Effects of volume and variety of social media brand engagement behavior," Journal of Business Research, Elsevier, vol. 135(C), pages 282-294.
    13. Renata V. Klafke & Paulo M. Gomes & Demétrio Mendonça Junior & Simone R. Didonet & Ana M. Toaldo, 2021. "Engagement in social networks: a multi-method study in non-profits organizations," International Review on Public and Nonprofit Marketing, Springer;International Association of Public and Non-Profit Marketing, vol. 18(2), pages 295-315, June.
    14. Li, Bin & Chen, Shuang & Zhou, Qi, 2023. "Empathy with influencers? The impact of the sensory advertising experience on user behavioral responses," Journal of Retailing and Consumer Services, Elsevier, vol. 72(C).
    15. Chawla, Yash & Chodak, Grzegorz, 2021. "Social media marketing for businesses: Organic promotions of web-links on Facebook," Journal of Business Research, Elsevier, vol. 135(C), pages 49-65.
    16. Rakshit, Sandip & Islam, Nazrul & Mondal, Sandeep & Paul, Tripti, 2022. "An integrated social network marketing metric for business-to-business SMEs," Journal of Business Research, Elsevier, vol. 150(C), pages 73-88.
    17. Gupta, Manjul & Uz, Irem & Esmaeilzadeh, Pouyan & Noboa, Fabrizio & Mahrous, Abeer A. & Kim, Eojina & Miranda, Graça & Tennant, Vanesa M. & Chung, Sean & Azam, Akbar & Peters, Anicia & Iraj, Hamideh &, 2018. "Do cultural norms affect social network behavior inappropriateness? A global study," Journal of Business Research, Elsevier, vol. 85(C), pages 10-22.
    18. Shakeel ul Rehman & Rafia Gulzar & Wajeeha Aslam, 2022. "Developing the Integrated Marketing Communication (IMC) through Social Media (SM): The Modern Marketing Communication Approach," SAGE Open, , vol. 12(2), pages 21582440221, May.
    19. Lorenzo-Seva, Urbano & van de Velden, Michel & Kiers, Henk A. L., 2009. "CAR: A MATLAB Package to Compute Correspondence Analysis with Rotations," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 31(i08).
    20. Xiaocui Li & Nengmin Wang & Bin Jiang & Tao Jia, 2023. "Institutional pressures and proactive environmental strategy: The mediating effect of top managerial environment attitude and the moderating effect of new media pressure," Business Strategy and the Environment, Wiley Blackwell, vol. 32(8), pages 6106-6123, December.

    More about this item

    Statistics

    Access and download statistics

    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:pal:palcom:v:11:y:2024:i:1:d:10.1057_s41599-024-02611-7. 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: https://www.nature.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.