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HistoChatbot: Educating History by Generating Quizzes in Social Network Services

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Leveraging Generative Intelligence in Digital Libraries: Towards Human-Machine Collaboration (ICADL 2023)

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Abstract

Microblogging platforms can provide novel, attractive opportunities for communicating and disseminating content about important events from the past. We propose a novel framework for building interactive chatbot systems that post history-related content including automatic quizzes related to current temporal context and that take and assess user responses. The chatbot is currently available on Twitter sharing history-related quizzes in English (The code, quiz data and evaluation results are available at https://github.com/sumilab/programs/tree/master/histo_chatbot_quiz.). We are the first to propose guidelines for designing history-focused chatbot systems that aim at fulfilling educational and entertaining objectives in microblogging platforms.

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Notes

  1. 1.

    E.g., https://en.wikipedia.org/wiki/1998.

  2. 2.

    E.g., https://en.wikipedia.org/wiki/February_25.

  3. 3.

    We assume here that the HistoChatbot Developer denotes a real user.

  4. 4.

    https://mobile.twitter.com/i/lists/1256794745512185857.

  5. 5.

    https://mobile.twitter.com/cbcnewsbc/status/1449609372296953859.

  6. 6.

    Assuming for this example that the user lives in New Zealand.

  7. 7.

    In the future, we plan to apply named entity recognition tools to allow users to write arbitrary texts.

References

  1. Adamopoulou, E., Moussiades, L.: An overview of chatbot technology. In: Maglogiannis, I., Iliadis, L., Pimenidis, E. (eds.) AIAI 2020. IAICT, vol. 584, pp. 373–383. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-49186-4_31

    Chapter  Google Scholar 

  2. Cauvin, T.: The rise of public history: an international perspective. Historia Crítica No. 40 68, 3–26 (2018)

    Google Scholar 

  3. Chan, Y.H., Fan, Y.C.: A recurrent BERT-based model for question generation. In: Proceedings of the 2nd Workshop on Machine Reading for Question Answering, pp. 154–162. ACL, Hong Kong, China (2019)

    Google Scholar 

  4. Chen, W., Wang, X., Wang, W.Y.: A dataset for answering time-sensitive questions (2021)

    Google Scholar 

  5. Clavert, F., Majerus, B., Beaupré, N.: #ww1. twitter, the centenary of the first world war and the historian. Twitter for Research 2015

    Google Scholar 

  6. Cole, J.R., Chaudhary, A., Dhingra, B., Talukdar, P.: Salient span masking for temporal understanding. arXiv preprint arXiv:2303.12860 (2023)

  7. Davis, E.: Benchmarks for automated commonsense reasoning: a survey. arXiv preprint arXiv:2302.04752 (2023)

  8. Hong, J.C., Cheng, C.L., Hwang, M.Y., Lee, C.K., Chang, H.Y.: Assessing the educational values of digital games. J. Comput. Assist. Learn. 25(5), 423–437 (2009)

    Article  Google Scholar 

  9. Huang, W., Hew, K.F., Fryer, L.K.: Chatbots for language learning-are they really useful? a systematic review of chatbot-supported language learning. J. Comput. Assist. Learn. 38(1), 237–257 (2022)

    Article  Google Scholar 

  10. Jatowt, A., Hung, I.-C., Färber, M., Campos, R., Yoshikawa, M.: Exploding TV sets and disappointing laptops: suggesting interesting content in news archives based on surprise estimation. In: Hiemstra, D., Moens, M.-F., Mothe, J., Perego, R., Potthast, M., Sebastiani, F. (eds.) ECIR 2021. LNCS, vol. 12656, pp. 254–269. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-72113-8_17

    Chapter  Google Scholar 

  11. Jia, J.: CSIEC: a computer assisted English learning chatbot based on textual knowledge and reasoning. Knowl.-Based Syst. 22(4), 249–255 (2009)

    Article  Google Scholar 

  12. Joho, H., Jatowt, A., Roi, B.: A survey of temporal web search experience. In: Proceedings of the 22nd International Conference on World Wide Web, pp. 1101–1108 (2013)

    Google Scholar 

  13. Kanhabua, N., Nguyen, T.N., Niederée, C.: What triggers human remembering of events?: a large-scale analysis of catalysts for collective memory in Wikipedia, pp. 341–350. JCDL ’14, London, United Kingdom (2014)

    Google Scholar 

  14. Kanhabua, N., Niederée, C., Siberski, W.: Towards concise preservation by managed forgetting: research issues and case study. iPres’13, Lisbon, Portugal (2013)

    Google Scholar 

  15. Lim, S., Jatowt, A., Färber, M., Yoshikawa, M.: Annotating and analyzing biased sentences in news articles using crowdsourcing. In: Proceedings of the Twelfth Language Resources and Evaluation Conference, pp. 1478–1484 (2020)

    Google Scholar 

  16. Sato, M., Jatowt, A., Duan, Y., Campos, R., Yoshikawa, M.: Estimating contemporary relevance of past news. In: ACM/IEEE, JCDL 2021, pp. 70–79. IEEE (2021)

    Google Scholar 

  17. Sumikawa, Y., Jatowt, A.: Analyzing history-related posts in twitter. Int. J. Digit. Libr. 22(1), 105–134 (2021)

    Article  Google Scholar 

  18. Sumikawa, Y., Jatowt, A.: Designing chatbot systems for disseminating history-focused content in online social networks. D - IEICE TRANSACTIONS on Information and Systems (Japanese Edition) J104-D(5), 486–497 (2021), (in Japanese)

    Google Scholar 

  19. Wang, J., Jatowt, A., Yoshikawa, M.: ArchivalQA: a large-scale benchmark dataset for open-domain question answering over historical news collections. In: Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 3025–3035 (2022)

    Google Scholar 

  20. Wang, L., et al.: A survey on large language model based autonomous agents. arXiv preprint arXiv:2308.11432 (2023)

  21. Yamamoto, Y., Tezuka, T., Jatowt, A., Tanaka, K.: Supporting judgment of fact trustworthiness considering temporal and sentimental aspects. In: Bailey, J., Maier, D., Schewe, K.-D., Thalheim, B., Wang, X.S. (eds.) WISE 2008. LNCS, vol. 5175, pp. 206–220. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-85481-4_17

    Chapter  Google Scholar 

  22. Zhao, W.X., et al.: A survey of large language models (2023)

    Google Scholar 

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Sumikawa, Y., Jatowt, A. (2023). HistoChatbot: Educating History by Generating Quizzes in Social Network Services. In: Goh, D.H., Chen, SJ., Tuarob, S. (eds) Leveraging Generative Intelligence in Digital Libraries: Towards Human-Machine Collaboration. ICADL 2023. Lecture Notes in Computer Science, vol 14457. Springer, Singapore. https://doi.org/10.1007/978-981-99-8085-7_3

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  • DOI: https://doi.org/10.1007/978-981-99-8085-7_3

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