IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v190y2023ics0040162523000719.html
   My bibliography  Save this article

The power of big data analytics over fake news: A scientometric review of Twitter as a predictive system in healthcare

Author

Listed:
  • Cano-Marin, Enrique
  • Mora-Cantallops, Marçal
  • Sanchez-Alonso, Salvador

Abstract

Interest in healthcare has grown significantly worldwide, especially since the Covid-19 outbreak. Digitalisation has allowed users to interact on social networks through platforms like Twitter, collecting user interactions over time, resulting in the proliferation of fake news. This research aims to analyse, evaluate and classify the predictive potential of Twitter analytics in healthcare, identifying the latent knowledge insights and distinguishing them from related rumours and fake news. Thus, a systematic literature review (SLR) is carried out to identify and analyse the existing academic research and applications in Twitter in predicting healthcare. The most important predictive applications are detecting mental health issues and public health emergencies. Covid-19 has been the main topic of most of the studies linked to fake news and misinformation, and this research provides a practical contribution to the use of unstructured data from Twitter and raises awareness of the importance of this content applied to healthcare. Therefore, it is pertinent to focus on the advances offered by these data as a predictive tool in healthcare since it is essential, to this end, to evaluate the veracity of the information shared on Twitter.

Suggested Citation

  • Cano-Marin, Enrique & Mora-Cantallops, Marçal & Sanchez-Alonso, Salvador, 2023. "The power of big data analytics over fake news: A scientometric review of Twitter as a predictive system in healthcare," Technological Forecasting and Social Change, Elsevier, vol. 190(C).
    • Handle: RePEc:eee:tefoso:v:190:y:2023:i:c:s0040162523000719
    DOI: 10.1016/j.techfore.2023.122386
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162523000719
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.techfore.2023.122386?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. Aria, Massimo & Cuccurullo, Corrado, 2017. "bibliometrix: An R-tool for comprehensive science mapping analysis," Journal of Informetrics, Elsevier, vol. 11(4), pages 959-975.
    2. repec:igg:jcac00:v:11:y:2021:i:2:p:97-109 is not listed on IDEAS
    3. Vivek Kumar Singh & Prashasti Singh & Mousumi Karmakar & Jacqueline Leta & Philipp Mayr, 2021. "The journal coverage of Web of Science, Scopus and Dimensions: A comparative analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(6), pages 5113-5142, June.
    4. Gandomi, Amir & Haider, Murtaza, 2015. "Beyond the hype: Big data concepts, methods, and analytics," International Journal of Information Management, Elsevier, vol. 35(2), pages 137-144.
    5. Jalal S. Alowibdi & Abdulrahman A. Alshdadi & Ali Daud & Mohamed M. Dessouky & Essa Ali Alhazmi, 2021. "Coronavirus Pandemic (COVID-19): Emotional Toll Analysis on Twitter," International Journal on Semantic Web and Information Systems (IJSWIS), IGI Global, vol. 17(2), pages 1-21, April.
    6. Scott, John, 1988. "Social Network Analysis and Intercorporate Relations," Hitotsubashi Journal of commerce and management, Hitotsubashi University, vol. 23(1), pages 53-68, December.
    7. Wamba, Samuel Fosso & Gunasekaran, Angappa & Akter, Shahriar & Ren, Steven Ji-fan & Dubey, Rameshwar & Childe, Stephen J., 2017. "Big data analytics and firm performance: Effects of dynamic capabilities," Journal of Business Research, Elsevier, vol. 70(C), pages 356-365.
    8. Mathieu Jacomy & Tommaso Venturini & Sebastien Heymann & Mathieu Bastian, 2014. "ForceAtlas2, a Continuous Graph Layout Algorithm for Handy Network Visualization Designed for the Gephi Software," PLOS ONE, Public Library of Science, vol. 9(6), pages 1-12, June.
    9. Wang, Yuxi & McKee, Martin & Torbica, Aleksandra & Stuckler, David, 2019. "Systematic Literature Review on the Spread of Health-related Misinformation on Social Media," Social Science & Medicine, Elsevier, vol. 240(C).
    10. Stieglitz, Stefan & Mirbabaie, Milad & Ross, Björn & Neuberger, Christoph, 2018. "Social media analytics – Challenges in topic discovery, data collection, and data preparation," International Journal of Information Management, Elsevier, vol. 39(C), pages 156-168.
    11. Ozbay, Feyza Altunbey & Alatas, Bilal, 2020. "Fake news detection within online social media using supervised artificial intelligence algorithms," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    12. Cynthia Chew & Gunther Eysenbach, 2010. "Pandemics in the Age of Twitter: Content Analysis of Tweets during the 2009 H1N1 Outbreak," PLOS ONE, Public Library of Science, vol. 5(11), pages 1-13, November.
    13. Ribeiro-Navarrete, Samuel & Saura, Jose Ramon & Palacios-Marqués, Daniel, 2021. "Towards a new era of mass data collection: Assessing pandemic surveillance technologies to preserve user privacy," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    14. Sophie E. Jordan & Sierra E. Hovet & Isaac Chun-Hai Fung & Hai Liang & King-Wa Fu & Zion Tsz Ho Tse, 2018. "Using Twitter for Public Health Surveillance from Monitoring and Prediction to Public Response," Data, MDPI, vol. 4(1), pages 1-20, December.
    15. Ashish K. Rathore & Arpan K. Kar & P. Vigneswara Ilavarasan, 2017. "Social Media Analytics: Literature Review and Directions for Future Research," Decision Analysis, INFORMS, vol. 14(4), pages 229-249, December.
    16. Piñeiro-Chousa, Juan & López-Cabarcos, M. Ángeles & Ribeiro-Soriano, Domingo, 2021. "The influence of financial features and country characteristics on B2B ICOs’ website traffic," International Journal of Information Management, Elsevier, vol. 59(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Kim, Jong Min & Park, Keeyeon Ki-cheon & Mariani, Marcello & Wamba, Samuel Fosso, 2024. "Investigating reviewers' intentions to post fake vs. authentic reviews based on behavioral linguistic features," Technological Forecasting and Social Change, Elsevier, vol. 198(C).

    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. Škare, Marinko & Blanco-Gonzalez-Tejero, Cristina & Crecente, Fernando & del Val, Maria Teresa, 2022. "Scientometric analysis on entrepreneurial skills - creativity, communication, leadership: How strong is the association?," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    2. Chae, Bongsug (Kevin), 2019. "A General framework for studying the evolution of the digital innovation ecosystem: The case of big data," International Journal of Information Management, Elsevier, vol. 45(C), pages 83-94.
    3. Ashrafi, Amir & Zare Ravasan, Ahad & Trkman, Peter & Afshari, Samira, 2019. "The role of business analytics capabilities in bolstering firms’ agility and performance," International Journal of Information Management, Elsevier, vol. 47(C), pages 1-15.
    4. Ramona Bran & Laurentiu Tiru & Gabriela Grosseck & Carmen Holotescu & Laura Malita, 2021. "Learning from Each Other—A Bibliometric Review of Research on Information Disorders," Sustainability, MDPI, vol. 13(18), pages 1-39, September.
    5. Juan J. Lull & Roberto Cervelló-Royo & José Luis Galdón, 2024. "Crossroads between Big Data and entrepreneurship: current key trends," International Entrepreneurship and Management Journal, Springer, vol. 20(4), pages 2763-2790, December.
    6. Irina Wedel & Michael Palk & Stefan Voß, 2022. "A Bilingual Comparison of Sentiment and Topics for a Product Event on Twitter," Information Systems Frontiers, Springer, vol. 24(5), pages 1635-1646, October.
    7. Ahmad Ibrahim Aljumah & Mohammed T. Nuseir & Md. Mahmudul Alam, 2021. "Traditional marketing analytics, big data analytics and big data system quality and the success of new product development," Post-Print hal-03538161, HAL.
    8. Cano-Marin, Enrique & Mora-Cantallops, Marçal & Sánchez-Alonso, Salvador, 2023. "Twitter as a predictive system: A systematic literature review," Journal of Business Research, Elsevier, vol. 157(C).
    9. de Camargo Fiorini, Paula & Roman Pais Seles, Bruno Michel & Chiappetta Jabbour, Charbel Jose & Barberio Mariano, Enzo & de Sousa Jabbour, Ana Beatriz Lopes, 2018. "Management theory and big data literature: From a review to a research agenda," International Journal of Information Management, Elsevier, vol. 43(C), pages 112-129.
    10. Lutfi, Abdalwali & Alrawad, Mahmaod & Alsyouf, Adi & Almaiah, Mohammed Amin & Al-Khasawneh, Ahmad & Al-Khasawneh, Akif Lutfi & Alshira'h, Ahmad Farhan & Alshirah, Malek Hamed & Saad, Mohamed & Ibrahim, 2023. "Drivers and impact of big data analytic adoption in the retail industry: A quantitative investigation applying structural equation modeling," Journal of Retailing and Consumer Services, Elsevier, vol. 70(C).
    11. Acharya, Abhilash & Singh, Sanjay Kumar & Pereira, Vijay & Singh, Poonam, 2018. "Big data, knowledge co-creation and decision making in fashion industry," International Journal of Information Management, Elsevier, vol. 42(C), pages 90-101.
    12. Dušan Nikolić & Dragan Ivanović & Lidija Ivanović, 2024. "An open-source tool for merging data from multiple citation databases," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(7), pages 4573-4595, July.
    13. Harkaran Kava & Konstantina Spanaki & Thanos Papadopoulos & Stella Despoudi & Oscar Rodriguez-Espindola & Masoud Fakhimi, 2021. "Data Analytics Diffusion in the UK Renewable Energy Sector: An Innovation Perspective," Post-Print hal-03781046, HAL.
    14. Oesterreich, Thuy Duong & Anton, Eduard & Teuteberg, Frank & Dwivedi, Yogesh K, 2022. "The role of the social and technical factors in creating business value from big data analytics: A meta-analysis," Journal of Business Research, Elsevier, vol. 153(C), pages 128-149.
    15. Md. Nazmus Sakib & Shah Ridwan Chowdhury & Mohammad Younus & Nehad Laila Sanju & Farhana Foysal Satata & Mahafuza Islam, 2024. "How HR analytics evolved over time: a bibliometric analysis on Scopus database," Future Business Journal, Springer, vol. 10(1), pages 1-22, December.
    16. Ling Pan & Zeshui Xu & Marinko Skare, 2023. "Sustainable business model innovation literature: a bibliometrics analysis," Review of Managerial Science, Springer, vol. 17(3), pages 757-785, April.
    17. Osama Musa Ali Al-Darras & Cem Tanova, 2022. "From Big Data Analytics to Organizational Agility: What Is the Mechanism?," SAGE Open, , vol. 12(2), pages 21582440221, June.
    18. Gabriel Alves Vieira & Jacqueline Leta, 2024. "biblioverlap: an R package for document matching across bibliographic datasets," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(7), pages 4513-4527, July.
    19. Miikka Blomster & Timo Koivumäki, 2022. "Exploring the resources, competencies, and capabilities needed for successful machine learning projects in digital marketing," Information Systems and e-Business Management, Springer, vol. 20(1), pages 123-169, March.
    20. Francesco Cappa & Stefano Franco & Federica Rosso, 2022. "Citizens and cities: Leveraging citizen science and big data for sustainable urban development," Business Strategy and the Environment, Wiley Blackwell, vol. 31(2), pages 648-667, February.

    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:eee:tefoso:v:190:y:2023:i:c:s0040162523000719. 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: Catherine Liu (email available below). General contact details of provider: http://www.sciencedirect.com/science/journal/00401625 .

    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.