Conflict-Driven User-Generated Content in the Viral Majapahit Laundry Conflict on TikTok

Authors

DOI:

https://doi.org/10.30822/aksioma.v5i2.5656
Crossmark

Keywords:

Conflict-Driven User-Generated Content, Netnografi, TikTok, User-Generated Content, Viral Marketing

Abstract

This study aims to analyze the formation of Conflict-Driven User-Generated Content (CD-UGC) in viral Laundry Majapahit content on TikTok and explain how digital conflict shapes user engagement, sense-making processes, and consumer responses toward a brand. A qualitative approach using netnography was employed to examine user comments posted on four viral TikTok videos of Laundry Majapahit. Data were collected through non-participant observation of comments that had undergone a data-cleaning process and were analyzed using thematic analysis supported by NVivo 12 Plus through stages of open coding, axial coding, and selective coding. The findings identified five major themes underlying the formation of CD-UGC: Emotional Engagement, Marketing Attribution, Sense-Making Process, Community Interaction, and Consumer Response. Emotional Engagement emerged as the most dominant theme, characterized by humor, sarcasm, empathy, and users' tendency to engage with online conflict. Furthermore, the conflict generated perceptions of gimmicks, sponsorship, and staged content; stimulated curiosity about the dispute; fostered interactions among users; shaped brand perceptions; and increased users' intentions to try the service and imitate Laundry Majapahit's communication strategy. These findings demonstrate that digital conflict generates not only online conversations but also Conflict-Driven User-Generated Content, which expands organic reach, strengthens audience engagement, and have the potential to enhance brand virality while creating organic marketing value for businesses. This study contributes to the digital marketing literature by introducing Conflict-Driven User-Generated Content as a conceptual mechanism explaining how online conflict evolves into organic virality within social media ecosystems.

Author Biographies

  • Siti Alfia Ayu Rohmayanti, Universitas Islam Negeri Sunan Ampel Surabaya

    Manajemen, Fakultas Ekonomi dan Bisnis Islam

  • Tri Utami, Universitas Negeri Surabaya

    Ekonomi Islam

References

Braun, V., & Clarke, V. (2021). Can I use TA? Should I use TA? Should I not use TA? Comparing reflexive thematic analysis and other pattern-based qualitative analytic approaches. Counselling and Psychotherapy Research, 21(1), 37–47. https://doi.org/10.1002/capr.12360

Cai, M., Yang, W., Du, Y., Tan, Y., & Lu, X. (2025). Automatic requirements elicitation from user-generated content: A review of data, methods, and representations. In Engineering Applications of Artificial Intelligence (Vol. 156). Elsevier Ltd. https://doi.org/10.1016/j.engappai.2025.111110

Ciolan, L., & Manasia, L. (2017). Reframing photovoice to boost its potential for learning research. International Journal of Qualitative Methods, 16(1). https://doi.org/10.1177/1609406917700647

Fu, X., Liu, X., & Li, Z. (2024). Catching eyes of social media wanderers: How pictorial and textual cues in visitor-generated content shape users’ cognitive-affective psychology. Tourism Management, 100. https://doi.org/10.1016/j.tourman.2023.104815

Hanell, F., & Severson, P. J. (2022). Netnography: Two Methodological Issues and the Consequences for Teaching and Practice. https://platform2.newseye.eu/

Kozinets, R. V. (2012). Marketing Netnography: Prom/ot(Ulgat)ing a New Research Method. Methodological Innovations Online, 7(1), 37–45. https://doi.org/10.4256/mio.2012.004

Kozinets, R. V., & Gretzel, U. (2024). Netnography evolved: New contexts, scope, procedures and sensibilities. Annals of Tourism Research, 104. https://doi.org/10.1016/j.annals.2023.103693

Lacárcel, F. J. S., Huete, R., & Zerva, K. (2024). Decoding digital nomad destination decisions through user-generated content. Technological Forecasting and Social Change, 200. https://doi.org/10.1016/j.techfore.2023.123098

León, C. J., Suárez-Rojas, C., Cazorla-Artiles, J. M., & González Hernández, M. M. (2025). Satisfaction and sustainability concerns in whale-watching tourism: A user-generated content model. Tourism Management, 106. https://doi.org/10.1016/j.tourman.2024.105019

Li, C., Lin, Y., Chen, R., & Chen, J. (Elaine). (2025). How do users adopt AI-generated content (AIGC)? An exploration of content cues and interactive cues. Technology in Society, 81. https://doi.org/10.1016/j.techsoc.2025.102830

Maher, C., Hadfield, M., Hutchings, M., & de Eyto, A. (2018). Ensuring Rigor in Qualitative Data Analysis: A Design Research Approach to Coding Combining NVivo With Traditional Material Methods. International Journal of Qualitative Methods, 17(1). https://doi.org/10.1177/1609406918786362

Mustak, M., Hallikainen, H., Laukkanen, T., Plé, L., Hollebeek, L. D., & Aleem, M. (2024). Using machine learning to develop customer insights from user-generated content. Journal of Retailing and Consumer Services, 81. https://doi.org/10.1016/j.jretconser.2024.104034

Nasrabadi, M. A., Beauregard, Y., & Ekhlassi, A. (2024). The implication of user-generated content in new product development process: A systematic literature review and future research agenda. Technological Forecasting and Social Change, 206. https://doi.org/10.1016/j.techfore.2024.123551

Rahimi, S., & khatooni, M. (2024). Saturation in qualitative research: An evolutionary concept analysis. International Journal of Nursing Studies Advances, 6. https://doi.org/10.1016/j.ijnsa.2024.100174

Siti Altasya Tangahu, Sirrajudien Bialangi, & Ramly Abudi. (2026). Pengaruh Konten Tren Running Terhadap Gaya Hidup Berlari pada Mahasiswa Pengguna Aktif Tiktok di Universitas Negeri Gorontalo. Jurnal Ilmu Psikologi Dan Kesehatan (SIKONTAN), 5(1), 22–33. https://doi.org/10.47353/sikontan.v5i1.4917

Song, H., & Yao, Z. (2025). Different but equal? The impact of personal incentives and platform incentives on user-generated content in online mental health communities. Information Processing and Management, 62(4). https://doi.org/10.1016/j.ipm.2025.104132

Tang, P., Qu, Z., Duan, C., & Xu, Z. (2025). Assessing urban park services for children’s wellbeing using user-generated content (UGC): A case study of Shanghai, China. Frontiers of Architectural Research. https://doi.org/10.1016/j.foar.2025.08.007

Usman, N. P., Nani, Y. N., Badjuka, A., Abdussamad, J., & Akuba, A. M. (2026). Dari Keteladanan Ke Empati Pelayanan: Model Kepemimpinan Transformasional Dalam Meningkatkan Kualitas Pelayanan Publik di DPM-PTSP Kabupaten Gorontalo. Wathan: Jurnal Ilmu Sosial Dan Humaniora, 3(2), 259–290. https://doi.org/10.71153/wathan.v3i2.556

Wei, D., Liu, M., Grekousis, G., Wang, Y., & Lu, Y. (2023). User-generated content affects urban park use: Analysis of direct and moderating effects. Urban Forestry and Urban Greening, 90. https://doi.org/10.1016/j.ufug.2023.128158

Zhang, Y., Pappa, C. I., & Pittich, D. (2024). Exploring user-generated content motivations: A systematic review of theoretical perspectives and empirical gaps in online learning. Computers and Education Open, 7. https://doi.org/10.1016/j.caeo.2024.100235

Zhang, Z., Li, C., & Zhang, H. (2026). Digital confusion: Comprehending the impact mechanisms of artificial intelligence-generated content and user-generated content on tourism decision making. Tourism Management, 112. https://doi.org/10.1016/j.tourman.2025.105269

Zhao, E., Sun, S., Fu, C., Wu, J., & Wang, S. (2025). How user-generated content influence different types of travelers to select hotels? A perspective with prospect theory. Information Processing and Management, 62(3). https://doi.org/10.1016/j.ipm.2024.104049

Zhuang, W., Zeng, Q., Zhang, Y., Liu, C., & Fan, W. (2023). What makes user-generated content more helpful on social media platforms? Insights from creator interactivity perspective. Information Processing and Management, 60(2). https://doi.org/10.1016/j.ipm.2022.103201

Published

10-08-2026

How to Cite

Ayu Rohmayanti, S. A., & Utami, T. (2026). Conflict-Driven User-Generated Content in the Viral Majapahit Laundry Conflict on TikTok. AKSIOMA : Jurnal Manajemen, 5(2), 145-162. https://doi.org/10.30822/aksioma.v5i2.5656