NON-COMMERCIAL CROSS-CULTURAL SOCIAL MEDIA INFLUENCERS TELLING CHINA’S STORY A CASE STUDY OF A CHINESE INFLUENCER IN PERSIAN CULTURE

Yıl 2024, Cilt: 8 Sayı: 2, 325 - 354, 27.05.2024

Qurban Hussain Pamirzad

Öz

This study used the perspective of social media communication strategies to explore the non-commercial social media influencers in the context of cross-cultural communication. Social media influencers, having enormous followers and high marketing potential, have been the center of studies in recent years. Given that the literature in this field only concentrated on commercial social media influencers, this study took a different approach to explore the non-commercial cross-culture social media influencers’ roles beyond their native cultures. Employing the quantitative content analysis method, this study examined the @anahitachin Facebook page run by a Chinese journalist and social media influencer in Persian culture. This article explains the content pattern and utilization of social media communication strategies, clarifying cross-cultural social media influencers' pathways. Similarly, the practical contributions of this study for the cross-culture social media influencers and its theoretical implications are discussed.

Anahtar Kelimeler

China’s story, cross-culture social media influencers, non-commercial social media influencers, public engagement, social media communication strategies, social media influencers

Kaynakça

• Anahita. (2023, September 8). [Q & A with Anahita Video].گفت و گو با آناهیتا. Youtube. Accessed ( Dec 2023) https://www.youtube.com/watch?v=NC3eHlnqZsk.
• Chan, K. K., & Misra, S. (1990). Characteristics of the opinion leader: A new dimension. Journal of Marketing Research, 27(3), 285-294.
• Chee, R. M., Capper, T. S., & Muurlink, O. T. (2023). The impact of social media influencers on pregnancy, birth, and early parenting experiences: systematic review. Midwifery, 120, 103623.
• Dessart, L. (2017). Social media engagement: a model of antecedents and relational outcomes. Journal of Marketing Management, 33(5-6), pp. 375–399.
• Di Yuna, Xiaokun L., Jianing L. Han (2022). Cross-Cultural Communication on Social Media: Review From the Perspective of Cultural Psychology and Neuroscience. Frontiers in Psychology: Cultural Psychology, Vol 13.
• Dolan, R., Conduit, J., Fahy, J., & Goodman, S. (2015). Social media engagement behavior: A uses and gratifications perspective. Journal of Strategic Marketing.
• Dolan, R., Conduit, J., Frethey-Bentham, C., Fahy, J. and Goodman, S. (2019), “Social media engagement behavior: A framework for engaging customers through social media content,” European Journal of Marketing, 53, 2213–2243.
• Duffy, B. E. (2020). Social Media Influencers. International Encyclopedia of Gender, Media, and Communication.
• Farivar, S. Wang, F. (2022). Effective influencer marketing: A social identity perspective. Journal of Retailing and Consumer Services, Vol 67.
• Floreddu, P.B. Cabiddu, F. (2016). Social media communication strategies. Journal of Services Marketing, 30 (5).
• Geertz, C. (1973). The interpretation of cultures: Selected essays. New York: Basic Books. Accessed (Dec 2023) https://hci.stanford.edu/courses/cs376/private/readings/geertz_thick_description.pdf.
• Geyser, W. (2023, November 15th). What is an Influencer? – Social Media Influencers Defined [Updated 2024]. Influencer Marketing Hub. Accessed (Dec 2023) https://influencermarketinghub.com/what-is-an-influencer/.
• Grover, P., Kar, A. K., & Dwivedi, Y. (2022). The evolution of social media influence - A literature review and research agenda. International. Journal of Information Management Data Insights, Vol 2. 100116.
• Hagemann, L., & Abramova, O. (2023). Sentiment, we-talk, and engagement on social media: insights from Twitter data mining on the US presidential elections 2020. Internet Research, 33(6), 1581-1602.
• Hitlin, S. Kwon, H.W Firat, R. (2021). In- and out-groups across cultures: Identities and perceived group values. Social Science Research, Vol 97.
• Hogg, M. (2018). Chapter 5 Social Identity Theory. In M. Hogg, Contemporary Social Psychological Theories: Second Edition (Ed.), (pp. 112–138). Redwood City: Stanford University Press.
• Huang, Z. Zhao, T. Lai, R. Tian, Y. Yang, F. (2023). A comprehensive implementation of the log, Box-Cox, and log-sinh transformations for skewed and censored precipitation data. Journal of Hydrology, Vol 620.
• Hughes, C. S. (2019). Driving Brand Engagement Through Online Social Influencers: An Empirical Investigation of Sponsored Blogging Campaigns. Journal of Marketing, 83(5), 78–964.
• Humanes, M. L. (2019). Selective Exposure in a Changing Political and Media Environment. Media and Communication, 7(3).
• Husiast, B. (2019, February 7). Sentiment Analysis – The Lexicon Based Approach. Alphabold. Accessed (Dec 2023) https://www.alphabold.com/sentiment-analysis-the-lexicon-based-approach/
• Kim, J., & Lee, J. (2022). Fact-checking and audience engagement: A study of content analysis and audience behavioral data of fact-checking coverage from news media. Digital Journalism.
• Kelm, O. (2020). Why do politicians use Facebook and Twitter the way they do? The influence of perceived audience expectations. Studies in Communication and Media, pp. 8–34.
• Kim, D. (2020). Learning Language, Learning Culture: Teaching Language to the Whole Student. ECNU Review of Education, 3(3), 519–541.
• Knuth, K. (2020). The Rise of Social Media Influencers: How effective are they? University of Wisconsin-Whitewater, Accessed (Dec 2023) https://blogs.uww.edu/kaylaknuth/files/2020/04/Final-Influencer-Research-Paper.pdf.
• Kruikemeier, S. v. (2014). Unraveling the effects of active and passive forms of political Internet use: Does it affect citizens’ political involvement? New Media & Society, 16(6), 903-920.
• Kuckartz, U. R. (2019). Coding Text and PDF Files. In: Analyzing Qualitative Data with MAXQDA. Springer, Cham.
• Lee, E.-J., & Shin, S.-Y. (2012). Are they talking to me? Cognitive and affective effects of interactivity in politicians’ Twitter communication. Cyberpsychology, Behavior, and Social Networking, 15(10), 515-520.
• Lee, J. E., & Watkins, B. (2016). YouTube vloggers’ influence on consumer luxury brand perceptions and intentions. Journal of Business Research, 69(12), 5753–5760.
• Li, Y. Xie, Y (2020). Is a Picture Worth a Thousand Words? An Empirical Study of Image Content and Social Media Engagement. Journal of Marketing Research, 57(1), 1–19.
• Taboada, M., Brooke, J., Tofiloski, M., Voll, K., & Stede, M. (2011). Lexicon-Based Methods for Sentiment Analysis. Computational Linguistics, 37(2), 267-307. https://doi.org/10.1162/COLI_a_00049
• McHugh, M. L. (2012). Interrater reliability: the kappa statistic. Biochem Med (Zagreb), 22(3):276-82. Accessed (Dec 2023) https://pubmed.ncbi.nlm.nih.gov/23092060/.
• Mikolajczyk, K. (2023, December 1). Average Engagement Rates for 13 Industries. Hootsuite. Accessed (Dec 2023) https://blog.hootsuite.com/average-engagement-rate/.
• Oberlo. (2023). Average Facebook engagement rate. Oberlo. Accessed (Dec 2023) https://www.oberlo.com/statistics/average-facebook-engagement-rate.