서비스연구 (Journal of Service Research and Studies)

  • 제13권3호
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  • Pages.1-19
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  • 2023
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  • 2234-2850(pISSN)
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  • 2466-1813(eISSN)
서비스사이언스학회 (The Society of service Science)
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유튜브 여행 동영상의 긍정적 감정과 부정적 감정이 사용자 참여에 미치는 영향

The Differential Impacts of Positive and Negative Emotions on Travel-Related YouTube Video Engagement

  • 김희진 (가천대학교 경영학부 ) ;
  • 송하연 (성균관대학교 인간AI인터랙션융합전공) ;
  • 유진영 (가천대학교 경영학부 ) ;
  • 최성철 (부경대학교 시스템경영안전공학부)
  • Heejin Kim (College of Business, Gachon University) ;
  • Hayeon Song (Department of Human-Artificial Intelligence Interaction, Sungkyunkwan University) ;
  • Jinyoung Yoo (College of Business, Gachon University) ;
  • Sungchul Choi (Department of System Management Engineering, Pukyong National University)
  • 투고 : 2023.08.03
  • 심사 : 2023.09.11
  • 발행 : 2023.09.30
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⟨ 이전 논문 다음 논문 ⟩

초록

여행 마케팅 분야에서 브이로그와 같은 동영상 기반 소셜미디어 컨텐츠의 중요성이 높아지고 있다. 그럼에도 불구하고 시청자 반응 및 참여 행동을 향상시키는 콘텐츠 특징에 대한 연구는 제한적이다. 본 연구는 유튜브 여행 콘텐츠의 나타난 감정이 시청자 참여 행동, 특히 "좋아요"와 "댓글" 작성에 미치는 영향을 연구하였다. 본 논문에서는 방문자 수가 높은 세계 8개 관광도시에 관한 여행 관련 유튜브 동영상 4,619개의 나래이션을 머신러닝으로 추출하여 텍스트화 한 후 음이항 회귀분석을 통해 분석하였다. 그 결과 긍정 감정 및 부정의 감정 모두 "좋아요" 수에 유의한 영향을 미쳤다. 즉, 동영상에서 나타난 긍정적인 감정과 부정적인 감정이 각각 높을수록 더 많은 시청자들이 "좋아요"를 클릭하는 것으로 나타났다. 댓글 수에 측면에서는 부정적인 감정만 유의한 영향을 보인 반면 긍정적인 감정은 유의한 영향을 미치지 않는 것으로 나타났다. 본 연구는 경험재인 여행 상품의 고유한 특성을 고려할 때 유튜브에서 시청자 참여를 높이고자 하는 마케터들에게 어떠한 동영상 특징이 "좋아요"와 댓글등의 참여 행동을 유도할 수 있는지를 이해하고 전략 수립에 도움을 준다는 면에서 시사하는 바가 크다. 또한 소셜 미디어, 특히 유튜브의 맥락에서 시청자 참여도에 미치는 감정의 영향력을 검증하였다. 향후에는 감정에 대한 긍정-부정의 분류를 넘어 특정 감정이 참여도에 미치는 영향에 대한 고찰을 통해 소셜 미디어 동영상에 나타난 감정의 역할에 대한 이해를 깊이 할 수 있을 것이다.

Despite the growing importance of video-based social media content, such as vlogs, as a marketing tool in the travel industry, there is limited research on the characteristics that enhance engagement among potential travelers. This study explores the influence of emotional valence in YouTube travel content on viewer engagement, specifically likes and comments. We analyzed 4,619 travel-related YouTube videos from eight popular tourist cities. Using negative binomial regression analysis, we found that both positive and negative emotions significantly influence the number of likes received. Videos with higher positive emotions as well as negative emotions receive more likes. However, when it comes to the number of comments, only negative emotions showed a significant positive influence, while positive emotions had no significant impact. These findings offer valuable insights for marketers seeking to optimize engagement strategies on YouTube, considering the unique nature of travel products. Further research into the effects of specific emotions on engagement is warranted to improve marketing strategies. This study highlights the powerful impact of emotions on viewer engagement in the context of social media, particularly on YouTube.

키워드

과제정보

This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2020046986)

참고문헌

  1. Amatulli, C., De Angelis, M., and Stoppani, A. (2019). Analyzing online reviews in hospitality: data-driven opportunities for predicting the sharing of negative emotional content. Current Issues in Tourism, 22(15), pp. 1904-1917.  https://doi.org/10.1080/13683500.2019.1594723
  2. Babin, B. J., Darden, W. R., and Babin, L. A. (1998). Negative emotions in marketing research: affect or artifact?. Journal of Business Research, 42(3), pp. 271-285.  https://doi.org/10.1016/S0148-2963(97)00124-0
  3. Baumeister, R. F., Bratslavsky, E., Finkenauer, C., and Vohs, K. D. (2001). Bad is stronger than good. Review of General Psychology, 5(4), pp. 323-370.  https://doi.org/10.1037/1089-2680.5.4.323
  4. Beerli, A., and Martin, J. D. (2004). Factors influencing destination image. Annals of Tourism Research, 31(3), pp. 657-681.  https://doi.org/10.1016/j.annals.2004.01.010
  5. Brodie, R. J., Ilic, A., Juric, B., and Hollebeek, L. (2013). Consumer engagement in a virtual brand community: An exploratory analysis. Journal of Business Research, 66(1), pp. 105-114.  https://doi.org/10.1016/j.jbusres.2011.07.029
  6. Ciarrochi, J., Parker, P., Kashdan, T. B., Heaven, P. C., and Barkus, E. (2015). Hope and emotional well-being: A six-year study to distinguish antecedents, correlates, and consequences. The Journal of Positive Psychology, 10(6), pp. 520-532.  https://doi.org/10.1080/17439760.2015.1015154
  7. Chen, M. J., and Farn, C. K. (2020). Examining the influence of emotional expressions in online consumer reviews on perceived helpfulness. Information Processing & Management, 57(6), p. 102266. 
  8. Cheong, H. J., and Morrison, M. A. (2008). Consumers' reliance on product information and recommendations found in UGC. Journal of Interactive Advertising, 8(2), pp. 38-49.  https://doi.org/10.1080/15252019.2008.10722141
  9. Cui, G., Lui, H. K., and Guo, X. (2012). The effect of online consumer reviews on new product sales. International Journal of Electronic Commerce, 17(1), pp. 39-58.  https://doi.org/10.2753/JEC1086-4415170102
  10. De Vries, L., Gensler, S., and Leeflang, P. S. (2012). Popularity of brand posts on brand fan pages: An investigation of the effects of social media marketing. Journal of Interactive Marketing, 26(2), pp. 83-91.  https://doi.org/10.1016/j.intmar.2012.01.003
  11. Dolan, R., Conduit, J., Fahy, J., and Goodman, S. (2016). Social media engagement behaviour: a uses and gratifications perspective. Journal of Strategic Marketing, 24(3-4), pp. 261-277.  https://doi.org/10.1080/0965254X.2015.1095222
  12. Fonberg, E. (1986). Amygdala, emotions, motivation, and depressive states. In Biological Foundations of Emotion (pp. 301-331). Academic Press. 
  13. Forgas, J. P. (2013). The affect infusion model (AIM): An integrative theory of mood effects on cognition and judgments. In Theories of mood and cognition (pp. 99-134). Psychology Press. 
  14. Griskevicius, V., Shiota, M. N., and Nowlis, S. M. (2010). The many shades of rose-colored glasses: An evolutionary approach to the influence of different positive emotions. Journal of Consumer Research, 37(2), pp. 238-250.  https://doi.org/10.1086/651442
  15. Hasan, M. (2019). What Makes Youtube Videos Go Viral? Emotional Triggers and Shopper's Engagement in Viral Advertising. Emotional Triggers and Shopper's Engagement in Viral Advertising (December 29, 2019). 
  16. Hollebeek, L. (2011). Exploring customer brand engagement: definition and themes. Journal of Strategic Marketing, 19(7), pp. 555-573.  https://doi.org/10.1080/0965254X.2011.599493
  17. Holsti, O. R. (1969). Content analysis for the social sciences and humanities. Reading. MA: Addison-Wesley (content analysis). 
  18. Kim, M. J., Chung, N., Lee, C. K., and Preis, M. W. (2016). Dual-route of persuasive communications in mobile tourism shopping. Telematics and Informatics, 33(2), pp. 293-308.  https://doi.org/10.1016/j.tele.2015.08.009
  19. Kim, S. E., Kim, H. L., and Lee, S. (2021). How event information is trusted and shared on social media: a uses and gratification perspective. Journal of Travel & Tourism Marketing, 38(5), pp. 444-460. 
  20. Kujur, F., and Singh, S. (2018). Emotions as predictor for consumer engagement in YouTube advertisement. Journal of Advances in Management Research, 15(2), pp. 184-197.  https://doi.org/10.1108/JAMR-05-2017-0065
  21. Labrecque, L. I., Swani, K., and Stephen, A. T. (2020). The impact of pronoun choices on consumer engagement actions: Exploring top global brands' social media communications. Psychology & Marketing, 37(6), pp. 796-814. 
  22. Lang, A., Park, B., Sanders-Jackson, A. N., Wilson, B. D., and Wang, Z. (2007). Cognition and emotion in TV message processing: How valence, arousing content, structural complexity, and information density affect the availability of cognitive resources. Media Psychology, 10(3), pp. 317-338.  https://doi.org/10.1080/15213260701532880
  23. Larsen, R. J., and Prizmic-Larsen, Z. (2006). Measuring Emotions: Implications of a Multimethod Perspective.
  24. Lee, D., Hosanagar, K., and Nair, H. S. (2018). Advertising content and consumer engagement on social media: Evidence from Facebook. Management Science, 64(11), pp. 5105-5131.  https://doi.org/10.1287/mnsc.2017.2902
  25. MacCann, C., Erbas, Y., Dejonckheere, E., Minbashian, A., Kuppens, P., and Fayn, K. (2020). Emotional intelligence relates to emotions, emotion dynamics, and emotion complexity: A meta-analysis and experience sampling study. European Journal of Psychological Assessment, 36(3), 460. 
  26. Moreno, M. A., Jelenchick, L. A., Egan, K. G., Cox, E., Young, H., Gannon, K. E., and Becker, T. (2011). Feeling bad on Facebook: Depression disclosures by college students on a social networking site. Depression and anxiety, 28(6), pp. 447-455.  https://doi.org/10.1002/da.20805
  27. Munaro, A. C., Hubner Barcelos, R., Francisco Maffezzolli, E. C., Santos Rodrigues, J. P., and Cabrera Paraiso, E. (2021). To engage or not engage? The features of video content on YouTube affecting digital consumer engagement. Journal of Consumer Behaviour, 20(5), pp. 1336-1352.  https://doi.org/10.1002/cb.1939
  28. Park, E., Kang, J., Choi, D., and Han, J. (2020). Understanding customers' hotel revisiting behaviour: a sentiment analysis of online feedback reviews. Current Issues in Tourism, 23(5), pp. 605-611.  https://doi.org/10.1080/13683500.2018.1549025
  29. Petty, Richard E., Derek D. Rucker, George Y. Gizer, and John T. Cacioppo (2004), "The Elaboration Likelihood Model of Persuasion," in Perspectives on Persuasion, Social Influence and Compliance Gaining, John S. Seiter and Robert H. Gass, eds. Boston: Allyn and Bacon. 
  30. Quoidbach, J., Mikolajczak, M., and Gross, J. J. (2015). Positive interventions: An emotion regulation perspective. Psychological bulletin, 141(3), p. 655. 
  31. Reinecke, L., and Trepte, S. (2014). Authenticity and well-being on social network sites: A two-wave longitudinal study on the effects of online authenticity and the positivity bias in SNS communication. Computers in Human Behavior, 30, pp. 95-102.  https://doi.org/10.1016/j.chb.2013.07.030
  32. Rita, P., Ramos, R., Borges-Tiago, M. T., and Rodrigues, D. (2022). Impact of the rating system on sentiment and tone of voice: A Booking. com and TripAdvisor comparison study. International Journal of Hospitality Management, 104, 103245. 
  33. Sabate, F., Berbegal-Mirabent, J., Canabate, A., and Lebherz, P. R. (2014). Factors influencing popularity of branded content in Facebook fan pages. European Management Journal, 32(6), pp. 1001-1011.  https://doi.org/10.1016/j.emj.2014.05.001
  34. Schwarz, N. (2012). Feelings-as-information theory. Handbook of theories of social psychology, 1, pp. 289-308.  https://doi.org/10.4135/9781446249215.n15
  35. Silaban, P. H., Chen, W. K., Nababan, T. S., Eunike, I. J., and Silalahi, A. D. K. (2022). How travel vlogs on YouTube influence consumer behavior: A use and gratification perspective and customer engagement. Human Behavior and Emerging Technologies, 2022, pp. 1-16.  https://doi.org/10.1155/2022/4432977
  36. Statista ( Pex, and Rain News. (June 10, 2019). Average YouTube video length as of December 2018, by category. Retrieved July 31, 2023, from https://www.statista.com/statistics/1026923/youtube-video-category-average-length/) 
  37. Swani, K., and Milne, G. R. (2017). Evaluating Facebook brand content popularity for service versus goods offerings. Journal of Business Research, 79, pp. 123-133.  https://doi.org/10.1016/j.jbusres.2017.06.003
  38. Swani, K., Milne, G. R., Brown, B. P., Assaf, A. G., and Donthu, N. (2017). What messages to post? Evaluating the popularity of social media communications in business versus consumer markets. Industrial Marketing Management, 62, pp. 77-87.  https://doi.org/10.1016/j.indmarman.2016.07.006
  39. Tafesse, W. (2020). YouTube marketing: how marketers' video optimization practices influence video views. Internet Research, 30(6), pp. 1689-1707.  https://doi.org/10.1108/INTR-10-2019-0406
  40. Teixeira, T., Wedel, M., and Pieters, R. (2012). Emotion-induced engagement in internet video advertisements. Journal of Marketing Research, 49(2), pp. 144-159.  https://doi.org/10.1509/jmr.10.0207
  41. Tellis, G. J., MacInnis, D. J., Tirunillai, S., and Zhang, Y. (2019). What drives virality (sharing) of online digital content? The critical role of information, emotion, and brand prominence. Journal of Marketing, 83(4), pp. 1-20.  https://doi.org/10.1177/0022242919841034
  42. Um, E. R. (2008). The effect of positive emotions on cognitive processes in multimedia-based learning. New York University. 
  43. Utz, S. (2012). Social network site use among Dutch students: Effects of time and platform. In Networked sociability and individualism: Technology for personal and professional relationships (pp. 103-125). 
  44. Watson, D., Clark, L. A., and Tellegen, A. (1988). Development and validation of brief measures of positive and negative affect: the PANAS scales. Journal of Personality and Social Psychology, 54(6), 1063. 
  45. Williams, P. (2014). Emotions and consumer behavior. Journal of Consumer Research, 40(5), viii-xi. 
  46. Wimmer, R. D. (1997). and JR Dominick. Mass Media Research: An Introduction. 
  47. Yousaf, S., & Kim, J. M. (2023). Dark personalities and online reviews: A textual content analysis of review generation, consumption and distribution. Tourism Management, 98, 104771.