IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v185y2022ics0040162522005522.html
   My bibliography  Save this article

AI-enabled talent training for the cross-cultural news communication talent

Author

Listed:
  • Shen, Guorong

Abstract

In the context of economic globalization, the demand for cross-cultural news communication talents is increasing. This study aims to analyze and optimize the training strategy of composite international talents (CITs) in news communication in the context of artificial intelligence (AI) to comprehensively improve the quality of talents. To organize the relevant research on AI and cross-cultural second language acquisition, a literature review is conducted. The advantages and disadvantages of the present training mechanism were then systematically summarized by evaluating the current situation of CIT training in news communication. Subsequently, the radial basis function neural network (RBFNN) model was applied to ameliorate the CIT training strategy for news dissemination. The analysis of the CIT talent training strategy for news communication demonstrates that the number of talents predicted by the model remained optimal through the model's iteration over six data lists. The RBFNN model proposed herein also outperforms other models with two experimental data sets. The model registers a recognition accuracy of 70 % and precision of 80 % at the 100th iteration. The recognition accuracy and precision improves significantly to 82.3 % and 83.6 %, respectively, after the 600th iteration. This study can further enhance the effects of CIT training in news communication and can serve as a reference for the digital intelligence of the news communication industry.

Suggested Citation

  • Shen, Guorong, 2022. "AI-enabled talent training for the cross-cultural news communication talent," Technological Forecasting and Social Change, Elsevier, vol. 185(C).
    • Handle: RePEc:eee:tefoso:v:185:y:2022:i:c:s0040162522005522
    DOI: 10.1016/j.techfore.2022.122031
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162522005522
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.techfore.2022.122031?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. Faris A. Almalki & Maha Aljohani & Merfat Algethami & Ben Othman Soufiene, 2022. "Incorporating Drone and AI to Empower Smart Journalism via Optimizing a Propagation Model," Sustainability, MDPI, vol. 14(7), pages 1-24, March.
    2. Wei, Hao & Yuan, Ran & Zhao, Laixun, 2020. "International talent inflow and R&D investment: Firm-level evidence from China," Economic Modelling, Elsevier, vol. 89(C), pages 32-42.
    3. Nisreen Ameen & Ali Tarhini & Alexander Reppel & Amitabh Anand, 2021. "Customer experiences in the age of artificial intelligence," Post-Print halshs-03045430, HAL.
    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. Shuya Wang & Xinjia Tian & Hui Wang & Chang Liu & Zhilin Wang & Qiuhua Song, 2023. "Forecasting and Coupled Coordination Analysis of Supply and Demand for Sustainable Talent in Chinese Agriculture," Sustainability, MDPI, vol. 15(9), pages 1-18, April.

    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. Chunlin Yuan & Shuman Wang & Yue Liu, 2023. "AI service impacts on brand image and customer equity: empirical evidence from China," Journal of Brand Management, Palgrave Macmillan, vol. 30(1), pages 61-76, January.
    2. Yuan, Chunlin & Zhang, Chenlei & Wang, Shuman, 2022. "Social anxiety as a moderator in consumer willingness to accept AI assistants based on utilitarian and hedonic values," Journal of Retailing and Consumer Services, Elsevier, vol. 65(C).
    3. TANASE, George Cosmin, 2024. "Understand AI Driven Marketing Capabilities: Empowering Customer Experience and Deliver Value with Intelligent Tools and Technologies," Romanian Distribution Committee Magazine, Romanian Distribution Committee, vol. 15(3), pages 26-32, September.
    4. Hongbin Hu & Yongbin Wang, 2022. "Research on Convergence Media Consensus Mechanism Based on Blockchain," Sustainability, MDPI, vol. 14(17), pages 1-27, September.
    5. Wang, Xueqin & Wong, Yiik Diew & Sun, Shanshan & Yuen, Kum Fai, 2022. "An investigation of self-service technology usage during the COVID-19 pandemic: The changing perceptions of ‘self’ and technologies," Technology in Society, Elsevier, vol. 70(C).
    6. Cheng, Jie & Huang, Dan & Wu, Yanling, 2023. "Managerial perception on competition and strategic R&D decisions1," Economic Modelling, Elsevier, vol. 123(C).
    7. Chaturvedi, Rijul & Verma, Sanjeev & Das, Ronnie & Dwivedi, Yogesh K., 2023. "Social companionship with artificial intelligence: Recent trends and future avenues," Technological Forecasting and Social Change, Elsevier, vol. 193(C).
    8. Yan Zhao & Hui Sun & Xuechao Xia & Dianyuan Ma, 2023. "Can R&D Intensity Reduce Carbon Emissions Intensity? Evidence from China," Sustainability, MDPI, vol. 15(2), pages 1-24, January.
    9. Chen Yang & Jing Hu, 2022. "When do consumers prefer AI-enabled customer service? The interaction effect of brand personality and service provision type on brand attitudes and purchase intentions," Journal of Brand Management, Palgrave Macmillan, vol. 29(2), pages 167-189, March.
    10. Sakib, S M Nazmuz, 2021. "The Role of Experience in the Digital Age and Its Purpose in the Value Creation Process," OSF Preprints vh7gz, Center for Open Science.
    11. Haseli, Gholamreza & Yaran Ögel, İlkin & Ecer, Fatih & Hajiaghaei-Keshteli, Mostafa, 2023. "Luxury in female technology (FemTech): Selection of smart jewelry for women through BCM-MARCOS group decision-making framework with fuzzy ZE-numbers," Technological Forecasting and Social Change, Elsevier, vol. 196(C).
    12. Rabassa, Valérie & Sabri, Ouidade & Spaletta, Claire, 2022. "Conversational commerce: Do biased choices offered by voice assistants’ technology constrain its appropriation?," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    13. Wang, Xueqin & Wong, Yiik Diew & Chen, Tianyi & Yuen, Kum Fai, 2022. "An investigation of technology-dependent shopping in the pandemic era: Integrating response efficacy and identity expressiveness into theory of planned behaviour," Journal of Business Research, Elsevier, vol. 142(C), pages 1053-1067.
    14. Aw, Eugene Cheng-Xi & Tan, Garry Wei-Han & Cham, Tat-Huei & Raman, Ramakrishnan & Ooi, Keng-Boon, 2022. "Alexa, what's on my shopping list? Transforming customer experience with digital voice assistants," Technological Forecasting and Social Change, Elsevier, vol. 180(C).
    15. Alraja, Mansour, 2022. "Frontline healthcare providers’ behavioural intention to Internet of Things (IoT)-enabled healthcare applications: A gender-based, cross-generational study," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    16. Geissler, Dominik & Beiderbeck, Daniel & Schmidt, Sascha L. & Schreyer, Dominik, 2024. "Emerging technologies and shifting consumer motives: Projecting the future of the top-tier sports media product," Technological Forecasting and Social Change, Elsevier, vol. 203(C).
    17. Roy, Sanjit K. & Singh, Gaganpreet & Sadeque, Saalem & Gruner, Richard L., 2024. "Customer experience quality with social robots: Does trust matter?," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
    18. Machkour Badr & Abriane Ahmed, 2024. "Entrepreneurship 4.0 and Success Factors in the Context of Industry 4.0: A literature review [Entrepreneuriat 4.0 et facteurs de succès dans le contexte de l'industrie 4.0 : Une revue de littératur," Post-Print hal-04704435, HAL.
    19. Rongbin Yang & Santoso Wibowo, 2022. "User trust in artificial intelligence: A comprehensive conceptual framework," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(4), pages 2053-2077, December.
    20. Birim, Şule Öztürk & Kazancoglu, Ipek & Kumar Mangla, Sachin & Kahraman, Aysun & Kumar, Satish & Kazancoglu, Yigit, 2022. "Detecting fake reviews through topic modelling," Journal of Business Research, Elsevier, vol. 149(C), pages 884-900.

    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:185:y:2022:i:c:s0040162522005522. 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.