Have a personal or library account? Click to login
Unveiling Trends of Chatbot and Conversational Agents: A Bibliometric Study Cover

Unveiling Trends of Chatbot and Conversational Agents: A Bibliometric Study

Open Access
|Dec 2024

References

  1. S. Singh and H. Beniwal, “A survey on near-human conversational agents,” Journal of King Saud University-Computer and Information Sciences, vol. 34, no. 10, pp. 8852–8866, Nov. 2022. https://doi.org/10.1016/j.jksuci.2021.10.013
  2. S. Kusal, S. Patil, J. Choudrie, K. Kotecha, S. Mishra, and A. Abraham, “AI-based conversational agents: A scoping review from technologies to future directions,” IEEE Access, vol. 10, pp. 92337–92356, Aug. 2022. https://doi.org/10.1109/ACCESS.2022.3201144
  3. B. Luo, R. Y. K. Lau, C. Li, and Y. Si, “A critical review of state‐of‐the‐ art chatbot designs and applications,” Wiley Interdiscip. Rev. Data Min. Knowl. Discov., vol. 12, no. 1, Nov. 2022, Art. no. e1434. https://doi.org/10.1002/widm.1434
  4. A. Piyatumrong, C. Sangkeettrakarn, S. Witdumrong, and J. Cherdgone, “Chatbot technology adaptation to reduce the information gap in R&D center: A case study of an IT research organization,” in 2018 Portland international conference on management of engineering and technology (PICMET), Honolulu, HI, USA, Aug. 2018, pp. 1–9. https://doi.org/10.23919/PICMET.2018.8481988
  5. C.-H. Li, K. Chen, and Y.-J. Chang, “When there is no progress with a task-oriented chatbot: A conversation analysis,” in Proceedings of the 21st International Conference on Human-Computer Interaction with Mobile Devices and Services, Oct. 2019, Art. no. 59. https://doi.org/10.1145/3338286.3344407
  6. J. Chen, F. Guo, Z. Ren, X. Wang, and J. Ham, “Human-chatbot interaction studies through the lens of bibliometric analysis,” Universal Access in the Information Society, pp. 1–20, Oct. 2023. https://doi.org/10.1007/s10209-023-01058-y
  7. A. Ahmed, N. Ali, M. Alzubaidi, W. Zaghouani, A. Abd-Alrazaq, and M. Househ, “Arabic chatbot technologies: A scoping review,” Computer Methods and Programs in Biomedicine Update, vol. 2, 2022, Art. no. 100057. https://doi.org/10.1016/j.cmpbup.2022.100057
  8. F. X. R. Baskara, “Bridging the culture gap: Challenges and limitations of using chatbots in intercultural education,” in NATIONAL SEMINAR OF PBI (English Language Education), 2023.
  9. A. Alsharhan, M. Al-Emran, and K. Shaalan, “Chatbot adoption: A multiperspective systematic review and future research agenda,” IEEE Transactions on Engineering Management, vol. 71, pp. 10232–10244, Aug. 2023. https://doi.org/10.1109/TEM.2023.3298360
  10. M. Verma, “Novel study on AI-based chatbot (ChatGPT) impacts on the traditional library management,” International Journal of Trend in Scientific Research and Development (IJTSRD), vol. 7, no. 1, pp. 961– 964, Feb. 2023. https://www.researchgate.net/publication/368608640_Novel_Study_on_AI-Based_Chatbot_ChatGPT_Impacts_on_the_Traditional_Library_Management
  11. S. K. Abbas, Z. Szabó, and A. Kő, “Current trends of development in chatbot systems,” Specialusis Ugdymas, vol. 1, no. 43, pp. 1157–1168, May 2022. http://sumc.lt/index.php/se/article/view/134
  12. M. W. Ashfaque, “Analysis of different trends in chatbot designing and development: A review,” ECS Transactions, vol. 107, no. 1, 2022, Art. no. 7215. https://doi.org/10.1149/10701.7215ecst
  13. A. Sarkar, H. Wang, A. Rahman, W. H. Memon, and L. Qian, “A bibliometric analysis of sustainable agriculture: based on the Web of Science (WOS) platform,” Environmental Science and Pollution Research, vol. 29, pp. 38928–38949, Mar. 2022. https://doi.org/10.1007/s11356-022-19632-x
  14. E. Garfield and I. H. Sher, “New factors in the evaluation of scientific literature through citation indexing,” American Documentation, vol. 14, no. 3, pp. 195–201, Jul. 1963. https://doi.org/10.1002/asi.5090140304
  15. O. Ellegaard and J. A. Wallin, “The bibliometric analysis of scholarly production: How great is the impact?” Scientometrics, vol. 105, pp. 1809–1831, Jul. 2015. https://doi.org/10.1007/s11192-015-1645-z
  16. R. Freire and C. J. Nicol, “A bibliometric analysis of past and emergent trends in animal welfare science,” Animal Welfare, vol. 28, no. 4, pp. 465–485, Nov. 2019. https://doi.org/10.7120/09627286.28.4.465
  17. E. Raparelli and S. Bajocco, “A bibliometric analysis on the use of unmanned aerial vehicles in agricultural and forestry studies,” Int. Journal of Remote Sensing, vol. 40, no. 24, pp. 9070–9083, Jan. 2019. https://doi.org/10.1080/01431161.2019.1569793
  18. J. A. Moral-Muñoz, E. Herrera-Viedma, A. Santisteban-Espejo, and M. J. Cobo, “Software tools for conducting bibliometric analysis in science: An up-to-date review,” Profesional de la Información, vol. 29, no. 1, Jan. 2020. https://doi.org/10.3145/epi.2020.ene.03
  19. W. Li, R. Jiang, Y. Zhao, J. Xie, J. Zhu, and R. Cao, “Water ecological environment protection under changing environment: a systematic review and bibliometric analysis,” Journal of Coastal Research, vol. 93, no. sp1, pp. 9–15, 2019. https://doi.org/10.2112/SI93-002.1
  20. J. Rowley and F. Slack, “Conducting a literature review,” Management Research News, vol. 27, no. 6, pp. 31–39, Jun. 2004. https://doi.org/10.1108/01409170410784185
  21. B. Fahimnia, J. Sarkis, and H. Davarzani, “Green supply chain management: A review and bibliometric analysis,” International Journal of Production Economics, vol. 162, pp. 101–114, Apr. 2015. https://doi.org/10.1016/j.ijpe.2015.01.003
  22. N. Elshaboury, E. M. Abdelkader, A. Al-Sakkaf, and T. Zayed, “A critical review and bibliometric analysis on applications of ground penetrating radar in science based on web of science database,” Engineering, vol. 4, no. 1, pp. 984–1008, Mar. 2023. https://doi.org/10.3390/eng4010059
  23. W. Liu et al., “Postural deformities in Parkinson’s disease: A bibliometric analysis based on web of science,” Heliyon, vol. 9, no. 3, Mar. 2023, Art. no. e14251. https://www.sciencedirect.com/science/article/pii/S2405844023014585
  24. T. Talan and M. Demirbilek, “Bibliometric analysis of research on learning analytics based on Web of Science database,” Informatics in Education, vol. 22, no. 1, pp. 161–181, Mar. 2023. https://doi.org/10.15388/infedu.2023.02
  25. S. Huang et al., “A bibliometric analysis of the trends and evolution on inhalation injury research,” Journal of Burn Care & Research, vol. 45, no. 2, pp. 438–450, Mar. 2023. https://doi.org/10.1093/jbcr/irad172
  26. B.-Z. Yuan and J. Sun, “Bibliometric analysis of rice and climate change publications based on Web of Science,” Theoretical and Applied Climatology, vol. 150, no. 1–2, pp. 347–362, Aug. 2022. https://doi.org/10.1007/s00704-022-04169-3
  27. J. Weizenbaum, “ELIZA – a computer program for the study of natural language communication between man and machine,” Communications of the ACM, vol. 9, no. 1, pp. 36–45, Jan. 1966. https://doi.org/10.1145/365153.365168
  28. R. Gong, J. Xue, L. Zhao, O. Zolotova, X. Ji, and Y. Xu, “A bibliometric analysis of green supply chain management based on the Web of Science (WOS) platform,” Sustainability, vol. 11, no. 12, Jun. 2019, Art. no. 3459. https://doi.org/10.3390/su11123459
  29. C. Nass, J. Steuer, and E. R. Tauber, “Computers are social actors,” in Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, Apr. 1994, pp. 72–78. https://doi.org/10.1145/191666.191703
  30. K. Papineni, S. Roukos, T. Ward, and W.-J. Zhu, “Bleu: a method for automatic evaluation of machine translation,” in Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics, Jul. 2002, pp. 311–318. https://doi.org/10.3115/1073083.1073135
  31. J. Zhang, J. Fei, X. Song, and J. Feng, “An improved Louvain algorithm for community detection,” Mathematical Problems in Engineering, vol. 2021, no. 1, Nov. 2021, Art. no. 1485592. https://doi.org/10.1155/2021/1485592
  32. J. Cassell and K. R. Thorisson, “The power of a nod and a glance: Envelope vs. emotional feedback in animated conversational agents,” Applied Artificial Intelligence, vol. 13, no. 4–5, pp. 519–538, Nov. 1999. https://doi.org/10.1080/088395199117360
  33. W.-L. Shiau, Y. K. Dwivedi, and H. S. Yang, “Co-citation and cluster analyses of extant literature on social networks,” International Journal of Information Management, vol. 37, no. 5, pp. 390–399, Oct. 2017. https://doi.org/10.1016/j.ijinfomgt.2017.04.007
  34. Y. Chen, Y. Liu, and K. Xu, “Characteristics and mechanism of agricultural transformation in typical rural areas of eastern China: A case study of Yucheng City, Shandong Province,” Chinese Geographical Science, vol. 20, pp. 545–553, Nov. 2010. https://doi.org/10.1007/s11769-010-0430-4
  35. J. N. Bailenson, K. Swinth, C. Hoyt, S. Persky, A. Dimov, and J. Blascovich, “The independent and interactive effects of embodied-agent appearance and behavior on self-report, cognitive, and behavioral markers of copresence in immersive virtual environments,” Presence, vol. 14, no. 4, pp. 379–393, Aug. 2005. https://doi.org/10.1162/105474605774785235
  36. J. D. Williams and S. Young, “Partially observable Markov decision processes for spoken dialog systems,” Computer Speech & Language, vol. 21, no. 2, pp. 393–422, Apr. 2007. https://doi.org/10.1016/j.csl.2006.06.008
  37. A. C. Graesser, P. Chipman, B. C. Haynes, and A. Olney, “AutoTutor: An intelligent tutoring system with mixed-initiative dialogue,” IEEE Transactions on Education, vol. 48, no. 4, pp. 612–618, Nov. 2005. https://doi.org/10.1109/TE.2005.856149
  38. E. Levin, R. Pieraccini, and W. Eckert, “A stochastic model of human-machine interaction for learning dialog strategies,” IEEE Transactions on Speech and audio Processing, vol. 8, no. 1, pp. 11–23, Aug. 2000. https://doi.org/10.1109/89.817450
  39. L. Ciechanowski, A. Przegalinska, M. Magnuski, and P. Gloor, “In the shades of the uncanny valley: An experimental study of human–chatbot interaction,” Future Generation Computer Systems, vol. 92, pp. 539–548, Mar. 2019. https://doi.org/10.1016/j.future.2018.01.055
  40. A. C. Graesser, K. VanLehn, C. P. Rosé, P. W. Jordan, and D. Harter, “Intelligent tutoring systems with conversational dialogue,” AI Magazine, vol. 22, no. 4, pp. 39–51, Dec. 2001. https://doi.org/10.1609/aimag.v22i4.1591
  41. S. Kopp, L. Gesellensetter, N. C. Krämer, and I. Wachsmuth, “A conversational agent as museum guide–design and evaluation of a real-world application,” in Intelligent Virtual Agents: 5th International Working Conference, IVA 2005, Kos, Greece, Sep. 2005, pp. 329–343. https://doi.org/10.1007/11550617_28
  42. L. Zhou, J. Gao, D. Li, and H.-Y. Shum, “The design and implementation of Xiaolce, an empathetic social chatbot,” Computational Linguistics, vol. 46, no. 1, pp. 53–93, Mar. 2020. https://doi.org/10.1162/coli_a_00368
  43. J. Law, S. Bauin, J. Courtial, and J. Whittaker, “Policy and the mapping of scientific change: A co-word analysis of research into environmental acidification,” Scientometrics, vol. 14, no. 3–4, pp. 251–264, Sep. 1988. https://doi.org/10.1007/BF02020078
  44. S. Zhou, J. Silvasstar, C. Clark, A. J. Salyers, C. Chavez, and S. S. Bull, “An artificially intelligent, natural language processing chatbot designed to promote COVID-19 vaccination: A proof-of-concept pilot study,” Digital Health, vol. 9, Mar. 2023. https://doi.org/10.1177/20552076231155679
  45. M. Karyotaki, A. Drigas, and C. Skianis, “Chatbots as cognitive, educational, advisory & coaching systems,” Technium Social Sciences Journal, vol. 30, no. 1, pp. 109–126, Apr. 2022. https://doi.org/10.47577/tssj.v30i1.6277
DOI: https://doi.org/10.2478/acss-2024-0019 | Journal eISSN: 2255-8691 | Journal ISSN: 2255-8683
Language: English
Page range: 30 - 42
Submitted on: Apr 15, 2024
Accepted on: Jul 15, 2024
Published on: Dec 6, 2024
Published by: Riga Technical University
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2024 Tasnim K. Alasali, Omar Dakkak, İlker Türker, published by Riga Technical University
This work is licensed under the Creative Commons Attribution 4.0 License.