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Modeling and Analysis of Chinese Culture and Communication

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Published:12 November 2022Publication History
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EXPRESSION OF CONCERN: ACM is issuing a formal Expression of Concern for all papers published in the TALLIP Special Issue on Self-Learning Systems and Pattern Recognition and Exploitation for Multimedia Asian Information Processing while a thorough investigation takes place with regards to the integrity of the peer review process. ACM strongly suggests that papers in this special issue not be cited in the literature until ACM's investigation has concluded and final decisions have been made regarding the integrity of the peer review process.

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Abstract

Along with many other Asian countries, China's communication differs from, and at times, conflicts with, the United States, which is considered more collectivist and low-contact than that of the United States. The topic of this article is mental, physical, and behavioral health. This ancient society is one of the world's oldest, with a history spanning many thousands of years. These aspects of Chinese culture have significant weight in the Chinese community and society. Chinese participants care deeply about the cultural context, whether social scientists, humanists, or clinical psychiatrists. Based on several studies, Chinese culture influences various aspects of health, including physical and mental well-being, parent-child interactions and social connections, goals for individuals and groups, and health care delivery models. According to research on the subject, traditional Confucian cultural norms have influenced Chinese communication features. To maintain harmonious ties, the Chinese rely heavily on indirect communication. For them, the way you stand, your attitude, and even the tone of your voice all communicate a lot more than just words. They use imprecise language and may understate the significance of what they say. For the modeling analysis of Chinese culture and communication (MA-CCC) model, a brand-new approach has been presented. As long as this Confucian-influenced Chinese communication style persists, it will significantly impact Chinese society and communication between Chinese professionals and their Western counterparts. However, the frequency of attachment terms was lower in Chinese literature; the findings showed a rising tendency for AC (affectionate communication) in recent decades. In addition, the frequency of love terms in Chinese novels was linked positively to individuality. As a result of societal shifts, affection sharing becomes more common in individualistic metropolitan settings, as these findings show a performance enhancement of 94.2%.

REFERENCES

  1. [1] Jia Z., Leiter R. E., Yeh I. M., Tulsky J. A., and Sanders J. J.. 2020. Toward culturally tailored advance care planning for the Chinese diaspora: An integrative systematic review. Journal of Palliative Medicine 23, 12 (2020), 16621677.Google ScholarGoogle ScholarCross RefCross Ref
  2. [2] Nguyen T. G., Phan T. V., Hoang D. T., Nguyen T. N., and So-In C.. 2020. Efficient SDN-based traffic monitoring in IoT networks with double deep Q-network. In International Conference on Computational Data and Social Networks. Springer, Cham. 2638.Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. [3] Qiu H. and Huang S.. 2020. Mobile dating, relational communication, and motivations for AIDS risk reduction among Chinese MSM college students. Health Communication 35, 3 (2020), 289296.Google ScholarGoogle ScholarCross RefCross Ref
  4. [4] Nguyen T. N., Liu B. H., Nguyen N. P., and Chou J. T.. 2020. Cyber security of smart grid: Attacks and defences. In ICC 2020-2020 IEEE International Conference on Communications (ICC’20). IEEE. 16.Google ScholarGoogle Scholar
  5. [5] Dhingra L., Cheung W., Breuer B., Huang P., Lam K., Chen J., and Portenoy R.. 2020. Attitudes and beliefs toward advance care planning among underserved Chinese-American immigrants. Journal of Pain and Symptom Management 60, 3 (2020), 588594.Google ScholarGoogle ScholarCross RefCross Ref
  6. [6] Loey M., Manogaran G., Taha M. H. N., and Khalifa N. E. M.. 2021. A hybrid deep transfer learning model with machine learning methods for face mask detection in the era of the COVID-19 pandemic. Measurement 167, 108288.Google ScholarGoogle ScholarCross RefCross Ref
  7. [7] Silva M. D., Tsai S., Sobota R. M., Abel B. T., Reid M. C., and Adelman R. D.. 2020. Missed opportunities when communicating with limited English-proficient patients during end-of-life conversations: Insights from Spanish-speaking and Chinese-speaking medical interpreters. Journal of Pain and Symptom Management 59, 3, 694701.Google ScholarGoogle ScholarCross RefCross Ref
  8. [8] Kumar P. M., Gandhi U., Varatharajan R., Manogaran G., Jidhesh R., and Vadivel T.. 2019. Intelligent face recognition and navigation system using neural learning for smart security in Internet of Things. Cluster Computing 22, 4 (2019), 77337744.Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. [9] Ao S. H. and Huang Q. S.. 2020. A systematic review on the application of dialogue in public relations to information communication technology-based platforms: Comparing English and Chinese contexts. Public Relations Review 46, 1 (2020), 101814.Google ScholarGoogle ScholarCross RefCross Ref
  10. [10] Gheisari M., Najafabadi H. E., Alzubi J. A., Gao J., Wang G., Abbasi A. A., and Castiglione A.. 2021. OBPP: An ontology-based framework for privacy-preserving in IoT-based smart city. Future Generation Computer Systems 123 (2021), 113.Google ScholarGoogle ScholarCross RefCross Ref
  11. [11] Zhao D., Zhang Q., and Ma F.. 2020. Communication that changes lives: Exploratory research on a Chinese online hypertension community. Library Hi-Tech 38, 4.Google ScholarGoogle ScholarCross RefCross Ref
  12. [12] Gao J., Wang H., and Shen H.. 2020. Machine learning-based workload prediction in cloud computing. In 29th International Conference on Computer Communications and Networks (ICCCN’20). IEEE, 19.Google ScholarGoogle Scholar
  13. [13] Zhai J., Weller-Newton J. M., Shimoinaba K., Chen H., and Copnell B.. 2020. Emerging from the “Ku:” fluctuating in adjusting with breast cancer—A post-traumatic growth theory situated within Chinese culture. Qualitative Health Research 30, 11 (2020), 16741683.Google ScholarGoogle ScholarCross RefCross Ref
  14. [14] Ramprasad L. and Amudha G.. 2014. Spammer detection and tagging based user-generated video search system—A survey. In International Conference on Information Communication and Embedded Systems (ICICES’14). IEEE. 15.Google ScholarGoogle Scholar
  15. [15] Li H.. 2020. From disenchantment to reenchantment: Rural microcelebrities, short video, and the spectacle-ization of the rural lifescape on Chinese social media. International Journal of Communication 14 (2020), 19.Google ScholarGoogle Scholar
  16. [16] Amudha G.. 2021. Dilated transaction access and retrieval: Improving the information retrieval of blockchain-assimilated Internet of Things transactions. Wireless Personal Communications, 121.Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. [17] Scrimgeour A. and Ganassin S.. 2020. Language, culture and identity in two Chinese community schools. More than one way of being Chinese? Multilingual matters: Languages for intercultural communication and education. Babel 55, 1–2 (2020), 4246.Google ScholarGoogle Scholar
  18. [18] Pillai A. S., Singh K., Saravanan V., Anpalagan A., Woungang I., and Barolli L.. 2018. A genetic algorithm-based method for optimizing multiprocessor systems’ energy consumption and performance. Soft Computing 22, 10 (2018), 32713285.Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. [19] Liu N. and Zhang Y. B.. 2020. Warranting theory, stereotypes, and intercultural communication: US Americans’ perceptions of a target Chinese on Facebook. International Journal of Intercultural Relations 77 (2020), 8394.Google ScholarGoogle ScholarCross RefCross Ref
  20. [20] Wang F., Yang N., Shakeel P. M., and Saravanan V.. 2021. Machine learning for mobile network payment security evaluation system. Transactions on Emerging Telecommunications Technologies, e4226.Google ScholarGoogle Scholar
  21. [21] Younas F., Nadir J., Usman M., Khan M. A., Khan S. A., Kadry S., and Nam Y.. 2021. An artificial intelligence approach for word semantic similarity measure of Hindi language. KSII Transactions on Internet & Information Systems 15, 6 (2021).Google ScholarGoogle Scholar
  22. [22] Hammad M., Alkinani M. H., Gupta B. B., and Abd El-Latif A. A.. 2021. Myocardial infarction detection based on the deep neural network on imbalanced data. Multimedia Systems, 113.Google ScholarGoogle Scholar
  23. [23] Somayaji S. R. K., Alazab M., Manoj M. K., Bucchiarone A., Chowdhary C. L., and Gadekallu T. R.. 2020. A framework for predicting and storing battery life in IoT devices using DNN and blockchain. In IEEE Globecom Workshops (GC Wkshps'20). IEEE. 16.Google ScholarGoogle Scholar
  24. [24] Manickam A., Haldar R., Saqlain S. M., Sellam V., and Soundrapandiyan R.. 2019. Fingerprint image classification using local diagonal and directional extrema patterns. Journal of Electronic Imaging 28, 3 (2019), 033027.Google ScholarGoogle Scholar
  25. [25] Kumar P. M., Pandey H. M., and Srivastava G.. 2021. Special issue on workplace violence prevention using security robots. Work 68, 3 (2021), 821823. ISSN 1875–9270. Work, 68 (3), 821–823.Google ScholarGoogle ScholarCross RefCross Ref
  26. [26] Srivastava A. K., Grotjahn R., Ullrich P. A., and Sadegh M.. 2021. Pooling data improves multimodel IDF estimates over median-based IDF estimates: Analysis over Susquehanna and Florida. Journal of Hydrometeorology 22 (2021), 971995.Google ScholarGoogle ScholarCross RefCross Ref
  27. [27] Liao H., Zhou Z., Zhao X., Zhang L., Mumtaz S., Jolfaei A., and Bashir A. K. 2019. Learning-based context-aware resource allocation for edge-computing-empowered industrial IoT. IEEE Internet of Things Journal, 7, 5 (2019), 42604277.Google ScholarGoogle Scholar
  28. [28] Chen-Bouck L. and Patterson M. M.. 2020. Relations of Chinese mothers’ cultural values and parental control to early adolescents’ self-construals. The Journal of Early Adolescence, 41, 4 (2020), 0272431620931202.Google ScholarGoogle Scholar
  29. [29] Bedford O. and Yeh K. H.. 2019. The history and the future of the psychology of filial piety: Chinese norms to contextualized personality construct. Frontiers in Psychology 10 (2019), 100.Google ScholarGoogle ScholarCross RefCross Ref
  30. [30] Muthukrishna M., Bell A. V., Henrich J., Curtin C. M., Gedranovich A., McInerney J., and Thue B.. 2020. Beyond Western, educated, industrial, rich, and democratic (WEIRD) psychology: Measuring and mapping cultural and psychological distance scales. Psychological Science 31, 6 (2020), 678701.Google ScholarGoogle ScholarCross RefCross Ref
  31. [31] Guang X. and Charoensukmongkol P.. 2020. The effects of cultural intelligence on leadership performance among Chinese expatriates working in Thailand. Asian Business & Management 21 (2020), 123.Google ScholarGoogle Scholar
  32. [32] Li J., Krishnamurthy S., Roders A. P., and van Wesemael P.. 2020. Community participation in cultural heritage management: A systematic literature review comparing Chinese and international practices. Cities 96 (2020), 102476.Google ScholarGoogle ScholarCross RefCross Ref
  33. [33] Sundararajan L.. 2020. A history of the concepts of harmony in Chinese culture. In Oxford Research Encyclopedia of Psychology.Google ScholarGoogle ScholarCross RefCross Ref
  34. [34] Liu J. L., Harkness S., and Super C. M.. 2020. Chinese mothers’ cultural models of children's shyness: Ethnotheories and socialization strategies in social change. New Directions for Child and Adolescent Development 2020, 170 (2020), 6992.Google ScholarGoogle ScholarCross RefCross Ref
  35. [35] Celhay F., Cheng P., Masson J., and Li W.. 2020. Package graphic design and communication across cultures: An investigation of Chinese consumers’ interpretation of imported wine labels. International Journal of Research in Marketing 37, 1 (2020), 108128.Google ScholarGoogle ScholarCross RefCross Ref
  36. [36] Li Q., de Jong M. D., and Karreman J.. 2020. Cultural differences between Chinese and Western user instructions: A content analysis of user manuals for household appliances. IEEE Transactions on Professional Communication 63, 1 (2020), 320.Google ScholarGoogle ScholarCross RefCross Ref
  37. [37] Martin F.. 2020. Iphones and “African gangs”: Everyday racism and ethno-transnational media in Melbourne's Chinese student world. Ethnic and Racial Studies 43, 5 (2020), 892910.Google ScholarGoogle ScholarCross RefCross Ref
  38. [38] Spijkman M. and de Jong M. D.. 2020. Beyond simplifications: Making sense of paradoxical Chinese values in Chinese-Western business negotiations. International Journal of Business Communication, 2329488420907138.Google ScholarGoogle ScholarCross RefCross Ref
  39. [39] Liu T. and Lai Z.. 2020. From non-player characters to othered participants: Chinese women's gaming experience in the ‘free’ digital market. Information, Communication & Society, 119.Google ScholarGoogle Scholar
  40. [40] Shakeel P. M., Baskar S., Fouad H., Manogaran G., Saravanan V., and Montenegro-Marin C. E.. 2021. Internet of things forensic data analysis using machine learning to identify roots of data scavenging. Future Generation Computer Systems 115 (2021), 756768.Google ScholarGoogle ScholarCross RefCross Ref
  41. [41] Saravanan V., Radhakrishnan M., Basavesh A. S., and Kothari D. P.. 2012. A comparative study on performance benefits of multi-core CPUs using OpenMP. International Journal of Computer Science Issues (IJCSI) 9, 1 (2012), 272.Google ScholarGoogle Scholar

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          cover image ACM Transactions on Asian and Low-Resource Language Information Processing
          ACM Transactions on Asian and Low-Resource Language Information Processing  Volume 21, Issue 6
          November 2022
          372 pages
          ISSN:2375-4699
          EISSN:2375-4702
          DOI:10.1145/3568970
          Issue’s Table of Contents

          Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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          Publication History

          • Published: 12 November 2022
          • Online AM: 23 March 2022
          • Accepted: 27 January 2022
          • Revised: 13 January 2022
          • Received: 27 November 2021
          Published in tallip Volume 21, Issue 6

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