Have a personal or library account? Click to login
Analyzing The Impact of Ai-Generated Email Marketing Content on Email Deliverability in Spam Folder Placement Cover

Analyzing The Impact of Ai-Generated Email Marketing Content on Email Deliverability in Spam Folder Placement

Open Access
|Jun 2024

References

  1. Adwan, A. Al, & Aladwan, R. (2022). Use of artificial intelligence system to predict consumers’ behaviors. International Journal of Data and Network Science, 6(4), 1223–1232. https://doi.org/10.5267/j.ijdns.2022.6.011
  2. Annadatha, A., & Stamp, M. (2018). Image spam analysis and detection. Journal of Computer Virology and Hacking Techniques, 14(1), 39–52. https://doi.org/10.1007/s11416-016-0287-x
  3. Arya, R., Antonisamy, B., & Kumar, S. (2012). Sample Size Estimation in Prevalence Studies. The Indian Journal of Pediatrics, 79(11), 1482–1488. https://doi.org/10.1007/s12098-012-0763-3
  4. Ayodele, T., & Zhou, S. (2008). Applying Machine learning Algorithms for Email Management. 2008 Third International Conference on Pervasive Computing and Applications, 339–344. https://doi.org/10.1109/ICPCA.2008.4783606
  5. Bergholz, A., De Beer, J., Glahn, S., Moens, M.-F., Paaß, G., & Strobel, S. (2010). New filtering approaches for phishing email. Journal of Computer Security, 18(1), 7–35. https://doi.org/10.3233/JCS-2010-0371
  6. Blanzieri, E., & Bryl, A. (2008). A survey of learning-based techniques of email spam filtering. Artificial Intelligence Review, 29(1), 63–92. https://doi.org/10.1007/s10462-009-9109-6
  7. Dada, E. G., Bassi, J. S., Chiroma, H., Abdulhamid, S. M., Adetunmbi, A. O., & Ajibuwa, O. E. (2019). Machine learning for email spam filtering: review, approaches and open research problems. Heliyon, 5(6), e01802. https://doi.org/10.1016/j.heliyon.2019.e01802
  8. Dedeturk, B. K., & Akay, B. (2020). Spam filtering using a logistic regression model trained by an artificial bee colony algorithm. Applied Soft Computing, 91, 106229. https://doi.org/10.1016/j.asoc.2020.106229
  9. Dredze, M., Wallach, H. M., Puller, D., Brooks, T., Carroll, J., Magarick, J., Blitzer, J., & Pereira, F. C. (2008). Intelligent Email: Aiding Users with AI. AAAI Conference on Artificial Intelligence. https://api.semanticscholar.org/CorpusID:7061032
  10. Duffy, S. (2007). A guide to email deliverability for B2C email marketers. Journal of Direct, Data and Digital Marketing Practice 2007 9:2, 9(2), 156–167. https://doi.org/10.1057/PALGRAVE.DDDMP.4350081
  11. Ejiyi, C. J., Deng, J., Ejiyi, T. U., Salako, A. A., Ejiyi, M. B., & Anomihe, C. G. (2021). Design and Development of Android Application for Educational Institutes. Journal of Physics: Conference Series, 1769(1), 012066. https://doi.org/10.1088/1742-6596/1769/1/012066
  12. Faris, H., Al-Zoubi, A. M., Heidari, A. A., Aljarah, I., Mafarja, M., Hassonah, M. A., & Fujita, H. (2019). An intelligent system for spam detection and identification of the most relevant features based on evolutionary Random Weight Networks. Information Fusion, 48, 67–83. https://doi.org/10.1016/j.inffus.2018.08.002
  13. Gangavarapu, T., Jaidhar, C. D., & Chanduka, B. (2020). Applicability of machine learning in spam and phishing email filtering: review and approaches. Artificial Intelligence Review, 53(7), 5019–5081. https://doi.org/10.1007/s10462-020-09814-9
  14. Gao, Y., & Liu, H. (2022). Artificial intelligence-enabled personalization in interactive marketing: a customer journey perspective. Journal of Research in Interactive Marketing, 1–18. https://doi.org/10.1108/JRIM-01-2022-0023
  15. Gkikas, D. C., & Theodoridis, P. K. (2019). Artificial Intelligence (AI) Impact on Digital Marketing Research (pp. 1251–1259). https://doi.org/10.1007/978-3-030-12453-3_143
  16. Gongwen, X., Xiaomei, L., Zhijun, Z., & Na, X. L. (2016). Web Spam Detection Based On Link Diversity and Content Features. International Journal of Security and Its Applications, 10(7), 363–372. https://doi.org/10.14257/ijsia.2016.10.7.32
  17. Google. (2023a). Email sender guidelines - Gmail Help. https://support.google.com/mail/answer/81126?hl=en. Accessed October 11, 2023
  18. Google. (2023b). Google Search’s guidance about AI-generated content | Google Search Central Blog | Google for Developers. https://developers.google.com/search/blog/2023/02/google-search-and-ai-content?hl=en. Accessed October 11, 2023
  19. Goralski, W. (2017). SMTP and Email. In The Illustrated Network (pp. 637–659). Elsevier. https://doi.org/10.1016/B978-0-12-811027-0.00025-4
  20. Kaczmarczyk, A., & Zabierowski, W. (2021). The Comparison of Native and Hybrid Mobile Applications for Android System. 2021 28th International Conference on Mixed Design of Integrated Circuits and System, 290–293. https://doi.org/10.23919/MIXDES52406.2021.9497558
  21. Karim, A., Azam, S., Shanmugam, B., Kannoorpatti, K., & Alazab, M. (2019). A Comprehensive Survey for Intelligent Spam Email Detection. IEEE Access, 7, 168261–168295. https://doi.org/10.1109/ACCESS.2019.2954791
  22. Khan, S. I. (2022). Impact of artificial intelligence on consumer buying behaviors. International Journal of Health Sciences, 8121–8129. https://doi.org/10.53730/ijhs.v6nS2.7025
  23. Kim, J., Shin, S., Bae, K., Oh, S., Park, E., & del Pobil, A. P. (2020). Can AI be a content generator? Effects of content generators and information delivery methods on the psychology of content consumers. Telematics and Informatics, 55, 101452. https://doi.org/10.1016/j.tele.2020.101452
  24. Kuang, A. (2022). Construction of Personalized Advertising Accuracy Model Based on Artificial Intelligence. 2022 International Conference on Artificial Intelligence and Autonomous Robot Systems (AIARS), 395–398. https://doi.org/10.1109/AIARS57204.2022.00095
  25. Kumar Deb, S., Jain, R., & Deb, V. (2018). Artificial Intelligence ―Creating Automated Insights for Customer Relationship Management. 2018 8th International Conference on Cloud Computing, Data Science & Engineering (Confluence), 758–764. https://doi.org/10.1109/CONFLUENCE.2018.8442900
  26. Kumar, V., Rajan, B., Venkatesan, R., & Lecinski, J. (2019). Understanding the Role of Artificial Intelligence in Personalized Engagement Marketing. California Management Review, 61(4), 135–155. https://doi.org/10.1177/0008125619859317
  27. Maarek, Y. (2014). When machines dominate humans. Proceedings of the 23rd International Conference on World Wide Web, 605–606. https://doi.org/10.1145/2567948.2578602
  28. Microsoft. (2023a). Microsoft Anti-Spam Policy - Microsoft Support. https://support.microsoft.com/en-us/topic/microsoft-anti-spam-policy-e4506f97-694f-49bc-8231-cac4369afcb8?ui=en-us&rs=en-us&ad=us. Accessed October 11, 2023
  29. Microsoft. (2023b). Sender Support in Outlook.com - Microsoft Support. https://support.microsoft.com/en-us/office/sender-support-in-outlook-com-05875e8d-1950-4d89-a5c3-adc355d0d652. Accessed October 11, 2023
  30. Naing, L., Winn, T., & Rusli, B. N. (2006). Practical issues in calculating the sample size for prevalence studies. Archives of Orofacial Sciences, 1, 9–14.
  31. Najork, M. (2016). Using Machine Learning to Improve the Email Experience. Proceedings of the 25th ACM International on Conference on Information and Knowledge Management, 891–891. https://doi.org/10.1145/2983323.2983371
  32. Nhavkar, V. K. (2023). Impact of Generative AI on IT Professionals. International Journal for Research in Applied Science and Engineering Technology, 11(7), 15–18. https://doi.org/10.22214/ijraset.2023.54515
  33. Olatunji, S. O. (2019). Improved email spam detection model based on support vector machines. Neural Computing and Applications, 31(3), 691–699. https://doi.org/10.1007/s00521-017-3100-y
  34. Patel, M., Porwal, R., Shukla, A., & Kotecha, R. (2019). Customized Automated Email Response Bot Using Machine Learning and Robotic Process Automation. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3367743
  35. PATHAK, R. R. (2013). Sample size: from formulae to concepts - II | International Journal of Basic & Clinical Pharmacology. International Journal of Basic & Clinical Pharmacology, 2(1), 94–95. https://www.ijbcp.com/index.php/ijbcp/article/view/1220
  36. Potti, N., Wendt, J. B., Zhao, Q., Tata, S., & Najork, M. (2018). Hidden in Plain Sight. Proceedings of the 2018 World Wide Web Conference on World Wide Web - WWW ’18, 1865–1874. https://doi.org/10.1145/3178876.3186167
  37. Prins, M. (2022). Improving content discovery and viewer engagement with AI. Proceedings of the 1st Mile-High Video Conference, 132–132. https://doi.org/10.1145/3510450.3517308
  38. Ramnarayan, S. (2021). Marketing and Artificial Intelligence (pp. 75–95). https://doi.org/10.4018/978-1-7998-5077-9.ch005
  39. Rose, S., Nightingale, J. S., Garfinkel, S., & Chandramouli, R. (2019). Trustworthy email. Gaithersburg, MD. https://doi.org/10.6028/NIST.SP.800-177r1
  40. Sakuraba, S., Yoda, M., Sei, Y., Tahara, Y., & Ohsuga, A. (2021). Sender Reputation Construction method using Sender Authentication. 2021 IEEE International Conference on Data Science and Computer Application (ICDSCA), 369–373. https://doi.org/10.1109/ICDSCA53499.2021.9650213
  41. Salman Ibrahim, D. (2018). Hybrid Approach to Detect Spam Emails using Preventive and Curing Techniques. Journal of Al-Qadisiyah for Computer Science and Mathematics, 10(3). https://doi.org/10.29304/jqcm.2018.10.3.417
  42. Sanz, E. P., Gómez Hidalgo, J. M., & Cortizo Pérez, J. C. (2008). Chapter 3 Email Spam Filtering (pp. 45–114). https://doi.org/10.1016/S0065-2458(08)00603-7
  43. Somosi, Z. (2022). The relationship between seo and artificial intelligence. Multidiszciplináris Tudományok, 12(3), 233–246. https://doi.org/10.35925/j.multi.2022.3.21
  44. Varshney, G., Misra, M., & Atrey, P. K. (2016). A survey and classification of web phishing detection schemes. Security and Communication Networks, 9(18), 6266–6284. https://doi.org/10.1002/sec.1674
  45. Vinitha, V. S., Renuka, D. K., & Bharathi, A. (2018). E-Mail Spam Classification Using Machine Learning in Distributed Environment. Journal of Computational and Theoretical Nanoscience, 15(5), 1688–1694. https://doi.org/10.1166/jctn.2018.7362
  46. Yahoo Inc. (2023). Deliverability: Sender Best Practices, Mail | Yahoo Developer Network. https://senders.yahooinc.com/best-practices/. Accessed October 11, 2023
  47. Yuniarthe, Y. (2017). Application of Artificial Intelligence (AI) in Search Engine Optimization (SEO). 2017 International Conference on Soft Computing, Intelligent System and Information Technology (ICSIIT), 96–101. https://doi.org/10.1109/ICSIIT.2017.15
DOI: https://doi.org/10.2478/hjbpa-2024-0006 | Journal eISSN: 2067-9785 | Journal ISSN: 2457-5720
Language: English
Page range: 96 - 106
Submitted on: Mar 1, 2024
Accepted on: May 1, 2024
Published on: Jun 8, 2024
Published by: Association Holistic Research Academic (Hora)
In partnership with: Paradigm Publishing Services
Publication frequency: 3 issues per year

© 2024 Nasser Bouchareb, Ismail Morad, published by Association Holistic Research Academic (Hora)
This work is licensed under the Creative Commons Attribution 4.0 License.