IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v188y2023ics0040162522007909.html
   My bibliography  Save this article

An AI-enabled approach for improving advertising identification and promotion in social networks

Author

Listed:
  • Shi, Baisheng
  • Wang, Hao

Abstract

The rapid development of the social economy has considerably impacted the traditional advertising industry. In terms of identifying and recommending advertisements, improving the accuracy of advertisement promotion and identification is an urgent need. Artificial intelligence (AI) methods are of practical application to facilitate digital transformation in the advertising industry. Among the many AI methods, the network model based on the genetic algorithm back propagation (GABP) neural network is the most compatible with applications in the advertising industry. In this work, the GABP neural network is applied in the construction of social networks to predict the click-through rate (CTR) of website advertising applications through the optimization of advertising promotion strategies. In the processes of optimizing and improving the system model using AI methods, the technological focus is the accuracy of advertising promotion and identification for the developing advertising industry. First, background information on the era of internet and AI development is analyzed. The new media technology is discussed through AI research and traditional advertising industry literature. In addition, a CTR prediction model is created for advertising applications based on the GABP network. In the neural network improvement process, the performance of GABP is enhanced through multiple iterations by optimizing the application strategy of advertising scenarios according to the topology of network connections. The study results demonstrate that different algorithms' recognition accuracy and precision show an increasing trend as the number of model iterations increases. The recognition accuracy of GABP increases from 49 % to 72 %, and the recognition precision of the algorithm increases from 69 % to 86 %. In addition, the area under the curve (AUC) value of the GABP network is only 0.6 before the number of neurons increases. When the number of neurons is 400, the AUC value of the algorithm reaches 0.82, and the comprehensive diagnostic value of the system dramatically improves. This research has significant reference value for reforming the traditional advertising work mode, enhancing intellectual development and promoting resource efficiency in the advertising industry.

Suggested Citation

  • Shi, Baisheng & Wang, Hao, 2023. "An AI-enabled approach for improving advertising identification and promotion in social networks," Technological Forecasting and Social Change, Elsevier, vol. 188(C).
    • Handle: RePEc:eee:tefoso:v:188:y:2023:i:c:s0040162522007909
    DOI: 10.1016/j.techfore.2022.122269
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162522007909
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.techfore.2022.122269?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. Coccia, Mario, 2019. "The theory of technological parasitism for the measurement of the evolution of technology and technological forecasting," Technological Forecasting and Social Change, Elsevier, vol. 141(C), pages 289-304.
    2. Rumen Pozharliev & Matteo Angelis & Dario Rossi, 2022. "The effect of augmented reality versus traditional advertising: a comparison between neurophysiological and self-reported measures," Marketing Letters, Springer, vol. 33(1), pages 113-128, March.
    3. Yan, Yingchen & Zhao, Qiuhong & Qin, Zhongfeng & Sun, Gaoji, 2022. "Integration of development and advertising strategies for multi-attribute products under competition," European Journal of Operational Research, Elsevier, vol. 300(2), pages 490-503.
    4. Wei-Min Cheng & Sheng-Ming Wang, 2021. "Research on the General Algorithm and Benefit of Real-Time Positioning Advertising System—Based on the Use of 5G Base Station Data," Future Internet, MDPI, vol. 13(8), pages 1-23, July.
    5. Ting Cui & Chan Wang & Pu-yan Nie, 2021. "Advertising investment under switching costs," Economic Research-Ekonomska Istraživanja, Taylor & Francis Journals, vol. 34(1), pages 1676-1689, January.
    6. Flostrand, Andrew & Pitt, Leyland & Bridson, Shannon, 2020. "The Delphi technique in forecasting– A 42-year bibliographic analysis (1975–2017)," Technological Forecasting and Social Change, Elsevier, vol. 150(C).
    7. Syahrial Shaddiq & Wuri Handayani, 2021. "Communication And Interactive Marketing Management Through Internet Advertising," SMBJ: Strategic Management Business Journal, UPMI Management, vol. 1(02), pages 25-29.
    8. Anna E. Tuchman, 2019. "Advertising and Demand for Addictive Goods: The Effects of E-Cigarette Advertising," Marketing Science, INFORMS, vol. 38(6), pages 994-1022, November.
    9. Sarika Ahlluwalia & Seema Singh, 2022. "E-advertising: a conceptual framework of opportunities offered, and challenges posed to the consumers," International Journal of Business Excellence, Inderscience Enterprises Ltd, vol. 26(1), pages 1-19.
    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. Huo, Da & Zhang, Xiaotao & Qiao, Li & Tang, Aidi & Wang, Yunhan, 2024. "Live streaming economy and green consumer behavior of farming products: A psycholinguistic forecasting by using social computation," Technological Forecasting and Social Change, Elsevier, vol. 205(C).
    2. Hoffmann, Stefan & Lasarov, Wassili & Dwivedi, Yogesh K., 2024. "AI-empowered scale development: Testing the potential of ChatGPT," Technological Forecasting and Social Change, Elsevier, vol. 205(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. Prommer, Lisa & Tiberius, Victor & Kraus, Sascha, 2020. "Exploring the future of startup leadership development," Journal of Business Venturing Insights, Elsevier, vol. 14(C).
    2. Ghazinoory, Sepehr & Nasri, Shohreh & Afshari-Mofrad, Masoud & Taghizadeh Moghadam, Negin, 2023. "National Innovation Biome (NIB): A novel conceptualization for innovation development at the national level," Technological Forecasting and Social Change, Elsevier, vol. 196(C).
    3. Godart, Frédéric & Pistilli, Luca, 2024. "The multifaceted concept of disruption: A typology," Journal of Business Research, Elsevier, vol. 170(C).
    4. Cotti, Chad & Courtemanche, Charles & Maclean, Joanna Catherine & Nesson, Erik & Pesko, Michael F. & Tefft, Nathan W., 2022. "The effects of e-cigarette taxes on e-cigarette prices and tobacco product sales: Evidence from retail panel data," Journal of Health Economics, Elsevier, vol. 86(C).
    5. Ali Goli & Simha Mummalaneni & Pradeep K. Chintagunta & Sanjay K. Dhar, 2022. "Show and Sell: Studying the Effects of Branded Cigarette Product Placement in TV Shows on Cigarette Sales," Marketing Science, INFORMS, vol. 41(6), pages 1163-1180, November.
    6. Aparna A. Labroo & Natalie Mizik & Russell Winer, 2022. "Sparking conversations: Editors’ Pick with commentaries and thematic article compilations," Marketing Letters, Springer, vol. 33(1), pages 1-4, March.
    7. Ali Goli & Simha Mummalaneni & Pradeep K. Chintagunta, 2024. "Making a Smooth Exit? Menthol Bans and Cigarette Sales in Massachusetts," Marketing Science, INFORMS, vol. 43(3), pages 564-589, May.
    8. Bart J. Bronnenberg & Jean-Pierre Dubé & Chad Syverson, 2022. "Marketing Investment and Intangible Brand Capital," Journal of Economic Perspectives, American Economic Association, vol. 36(3), pages 53-74, Summer.
    9. Lee, Changyong, 2021. "A review of data analytics in technological forecasting," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
    10. Naoki Aizawa & You Suk Kim, 2020. "Public and Private Provision of Information in Market-Based Public Programs: Evidence from Advertising in Health Insurance Marketplaces," NBER Working Papers 27695, National Bureau of Economic Research, Inc.
    11. Henry Saffer & Daniel Dench & Michael Grossman & Dhaval Dave, 2020. "E-cigarettes and adult smoking: Evidence from Minnesota," Journal of Risk and Uncertainty, Springer, vol. 60(3), pages 207-228, June.
    12. Yi-Lin Tsai & Elisabeth Honka, 2021. "Informational and Noninformational Advertising Content," Marketing Science, INFORMS, vol. 40(6), pages 1030-1058, November.
    13. Kanungo, Rama Prasad & Gupta, Suraksha & Patel, Parth & Prikshat, Verma & Liu, Rui, 2022. "Digital consumption and socio-normative vulnerability," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    14. Michael E. Darden, 2024. "Optimal e-cigarette policy when preferences and internalities are correlated," Journal of Risk and Uncertainty, Springer, vol. 68(2), pages 107-131, April.
    15. Liu, Jun & Chang, Huihong & Forrest, Jeffrey Yi-Lin & Yang, Baohua, 2020. "Influence of artificial intelligence on technological innovation: Evidence from the panel data of china's manufacturing sectors," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    16. Piyush Anand & Vrinda Kadiyali, 2024. "Frontiers: Smoke and Mirrors: Impact of E-cigarette Taxes on Underage Social Media Posting," Marketing Science, INFORMS, vol. 43(3), pages 479-487, May.
    17. Harwood, Stephen & Eaves, Sally, 2020. "Conceptualising technology, its development and future: The six genres of technology," Technological Forecasting and Social Change, Elsevier, vol. 160(C).
    18. Sarkar, Biswajit & Dey, Bikash Koli, 2023. "Is online-to-offline customer care support essential for consumer service?," Journal of Retailing and Consumer Services, Elsevier, vol. 75(C).
    19. Yu Wang & Zongshuan Duan & Sherry L. Emery & Yoonsang Kim & Frank J. Chaloupka & Jidong Huang, 2021. "The Association between E-Cigarette Price and TV Advertising and the Sales of Smokeless Tobacco Products in the USA," IJERPH, MDPI, vol. 18(13), pages 1-14, June.
    20. Calof, Jonathan & Colton, Brian, 2024. "Developing foresight that impacts senior management decisions," Technological Forecasting and Social Change, Elsevier, vol. 198(C).

    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:188:y:2023:i:c:s0040162522007909. 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.