Exploring direct and indirect cultural experiences: a study of global consumers’ Hanbok experience and engagement mediated via YouTube

Abstract

With the rapid development of technology and media, people’s experiences of other cultures have shifted from direct only to a combination of direct and virtual experiences. This study investigated how global consumers directly and indirectly experience other cultures, mediated by YouTube. It focused on the consumer experience of the Korean traditional costume, the Hanbok. YouTube content focusing on Hanbok experiences was collected to understand the direct Hanbok experiences, while viewers’ reactions to YouTube content (i.e., views, likes, and comments) were collected to understand indirect Hanbok experiences. The analysis involved two steps. First, the latent Dirichlet allocation topic modeling algorithm in Python was used to extract topics from direct and indirect Hanbok experiences. Second, simple regression analysis was conducted using numerical data derived from textual data through linguistic inquiry and word count to examine the relationship between direct Hanbok experiences via YouTube and viewer engagement as an indicator of indirect Hanbok experiences. The results showed that YouTubers’ Hanbok experiences were categorized into seven topics, namely novelty, sensory, daily, cultural, trial, pleasing, and intellectual experiences. Indirect Hanbok experiences were identified based on dimensions of consumer engagement, such as social, cognitive, learning, behavioral, and affective engagement. The regression analysis results revealed that cultural and affective Hanbok experiences significantly impacted consumer engagement. This study expanded the scope of research by exploring indirect cultural experiences mediated by a media platform.

Introduction

In recent years, K-pop groups BLACKPINK and BTS have captured the attention of global audiences with their “modified Hanbok,” the traditional Korean costume. The deliberate inclusion of the Hanbok in their music videos, stage performances, and public appearances has sparked a wave of fascination and interest among fans worldwide across diverse media platforms. Although global fans lack experience of wearing a Hanbok, they have eagerly embraced this fusion of traditional Korean attire with contemporary styles (Kwak, 2020), demonstrating their enthusiasm through social media, fan art, and personal attempts to incorporate Hanbok elements into their own fashion choices. This phenomenon highlights the media’s important role in broadening access to varied cultural experiences.

The rapid advancement of technology and media in recent years has significantly transformed the cultural landscape. Historically, gaining insights into other cultures predominantly involved direct experiences such as traveling abroad and engaging in person with individuals from diverse cultures (Ozer et al., 2021). Indeed, research on globalization has often focused on direct experiences such as travel (Bandara et al., 2014) and face-to-face interactions (Haugen & Kunst, 2017; Ozer et al., 2021), while tending to overlook indirect experiences. However, individuals can now immerse themselves in different cultures through accessible means such as watching foreign films and following influencers’ vlogs on YouTube (Ferguson & Bornstein, 2012; Kim & Choo, 2023; Ozer et al., 2021). Despite this shift, there is a notable gap in understanding how people experience other cultures indirectly via media and the internet (Ozer et al., 2021). For example, although Ozer et al. (2021) examined both direct and indirect intercultural contacts in the context of globalization, their study did not fully address the role of the media environment in bridging these experiences, a factor critical to understanding the interconnectedness of direct and indirect cultural interactions.

Based on this gap in the literature, the aims of this study are threefold. First, it explores the direct experiences of global consumers with the Hanbok through the analytics of YouTube video content. This approach improves upon the traditional qualitative methods and self-reporting techniques prevalent in cross-cultural research by using real-time data from YouTube. Second, this study examines consumers’ indirect experiences by analyzing viewers’ reactions to YouTube content, such as views, likes, and comments. Despite the prevalence of indirect experiences in the digital realm, research has yet to clearly define or quantify “indirect experience” as a separate variable within these contexts. Hence, this study employs the concept of consumer engagement as a proxy to articulate these indirect experiences on digital platforms. Lastly, the relationship between direct and indirect experiences is explored by examining how YouTube content produced by creators affects viewers’ responses. To the best of our knowledge, no study has specifically investigated how YouTube, as a platform for cultural exchange, fosters a reciprocal relationship between direct and indirect cultural experiences.

This study is marked by its innovative use of text mining to analyze the cultural experiences depicted in YouTube content. Traditional text mining relies on qualitative analysis to identify several themes, which can raise questions about its reliability and validity (Bleidorn & Hopwood, 2019; Tay et al., 2020). This research addresses these concerns by adopting a quantitative approach, transforming textual data into numerical information using tools such as the Linguistic Inquiry and Word Count program (LIWC hereafter) for the statistical analysis (Parkinson et al., 2017). This methodological advancement contributes to the theoretical growth of text analysis techniques and provides a more holistic understanding of cultural narratives. Moreover, this study contributes to the literature on digital media by investigating YouTube’s role as an interactive platform for cultural exchange. It provides a space for users to both create and consume cultural content, thus facilitating a blend of direct and indirect cultural experiences. The findings of this study can extend beyond entertainment, positioning digital platforms such as YouTube as critical spaces for cultural interaction and understanding and thereby revealing the multifaceted layers of culture that manifest in these digital arenas.

Literature Review

Consumer experience

Direct versus indirect consumer experiences

Consumer experience in a given domain can vary from direct to indirect based on the level of interaction with a domain (Hamilton & Thompson, 2007; Mooy & Robben, 2002). Direct experiences are derived from unmediated interactions between consumers and products or services, encompassing firsthand encounters that engage the senses, including visual, auditory, olfactory, gustatory, and haptic experiences (Suh & Lee, 2005). Indirect experiences are the consumption of information or content related to a domain without direct physical interaction (Hamilton & Thompson, 2007). Li et al. (2001) suggested that consumers can have direct, indirect, and virtual experiences when they consume products. For example, consumers can experience clothing with physical trials (i.e., direct), by watching a video (i.e., indirect), or through virtual fittings in virtual reality settings as a simulated or computer-generated experience (i.e., virtual). Indirect and virtual experiences are mediated, as they involve the use of media to connect consumers with a particular domain.

Research has compared the informational value of direct and indirect experiences (Hamilton & Thompson, 2007; Hoch & Deighton, 1989; Verhoef et al., 2009). Direct experiences, occurring when consumers personally use or interact with products, offer a unique opportunity for hypothesis testing and active learning (Hamilton & Thompson, 2007). This active involvement enables consumers to explore and understand how a product functions in real-world scenarios (Hoch & Deighton, 1989). Such hands-on interaction can lead to a deeper comprehension of the product’s features, performance, and suitability for their needs (Smith & Swinyard, 1982; Verhoef et al., 2009). By contrast, indirect experiences such as reading reviews and watching product demonstrations involve a more passive form of learning. While valuable, such experiences typically lack the depth and personal relevance that direct encounters provide. Consequently, the information gained through direct experiences is often perceived as more credible and reliable by consumers (Hamilton & Thompson, 2007). This credibility stems from the firsthand nature of the learning process, where the consumer is not only receiving information but also actively engaging with and testing the product. Furthermore, direct experiences allow consumers to assess subjective aspects such as comfort, ease of use, and personal satisfaction, which are difficult to gauge through indirect means. The firsthand use of a product can dispel doubts and lead to more confident decision-making, reinforcing the notion that direct experiences often result in more trustworthy and influential information for consumers. Most studies have focused on either direct experiences or the superiority of direct over indirect experiences. This emphasis allows for hands-on engagement, active learning, and firsthand evaluation. However, it is equally important to recognize the significance of indirect experiences such as exposure to advertisements, product descriptions, reviews, and testimonials (Hirschman & Holbrook, 1982; Hwang & Yoon, 2023; Verhoef et al., 2009). These experiences serve as mediators between consumers and the product or service, providing information, creating expectations, and influencing consumer behavior. Indirect experiences can influence consumer decision-making before they have a direct encounter with the product.

While no research explicitly addresses the relationship between direct and indirect experiences through media, several studies have investigated how content on social media platforms such as Facebook (Banerjee & Chua, 2019; Hughes et al., 2019; Sabate et al., 2014) and X, formerly Twitter (Francalanci & Hussain, 2017), influence consumers’ reactions. For example, Banerjee and Chua (2019) demonstrated that content presentation on Facebook Fan Pages significantly impacts post popularity, as measured by the volume of likes, comments, and shares. Hughes et al. (2019) found that online engagement with sponsored blogs, including such actions as commenting and liking a brand, varies based on blogger characteristics and blog content. Similarly, Murano et al. (2021) examined the impact of various language styles in YouTube content on viewer engagement, discovering that factors such as video duration, posting time, language style, and emotional tone significantly affect viewers’ interactions. These studies suggest a relationship between the types or features of content and consumers’ reactions; however, they primarily focus on the content attributes rather than the experiential aspect. This study aims to bridge this gap by specifically exploring how the nature of direct experiences shared on platforms such as YouTube influences the indirect experiences of viewers.

Indirect experiences in the media

With the development of technology and media, the importance of indirect experiences has increased (Verhoef et al., 2009). Technological advancements and the widespread availability of digital platforms have expanded the avenues through which consumers can engage with brands, products, and services. For instance, the rise of social media, online reviews, and influencer marketing has provided consumers with an abundance of indirect experiences, where they can gather information, seek recommendations, and observe others’ experiences (De Veirman et al., 2017; de Vries et al., 2012). Indirect experiences through digital media platforms offer convenience, allowing consumers to explore products and services without geographical limitations and time constraints (De Veirman et al., 2017; Hwang & Yoon, 2023) or direct physical interaction (Phelps et al., 2004). Consumers can access and consume content at their own pace, engaging in virtual experiences that simulate or replicate aspects of the real product experience (Dellarocas et al., 2007).

However, research on the effects of indirect experiences is still relatively narrow in both scope and extent. The concept of indirect experiences has predominantly been applied within traditional media research to denote consumers’ responses to products and services depicted in advertisements. Consequently, studies on consumers’ indirect experiences have largely focused on controlled scenarios involving the observation of advertisements (Daugherty et al., 2008; Keng et al., 2012). However, digital platforms, propelled by technological advancements, offer interactive environments in which consumers can articulate their experiences with a company or brand’s messages via comments, likes, dislikes, and other forms of reaction. This interactivity increases the visibility of indirect experiences for consumers who have not interacted with the product or service directly themselves.

Despite the growing ubiquity of indirect experiences in digital spaces, no studies have explicitly identified or measured the term “indirect experiences” as a distinct variable in digital contexts. Instead, many studies have relied on alternative concepts such as “consumer engagement” and “consumer interactions.” These terms are used in research focusing on mediated environments to investigate consumer engagement, thereby shedding light on how consumers indirectly experience products and services through digital media without hands-on experience. This approach is evident in the various studies that have explored the indirect ways consumers interact with products and services through media (e.g., Brodie et al., 2011; Hollebeek et al., 2014; Hwang & Yoon, 2023; Kim & Choo, 2023; Kozinets, 2002; Kujur & Singh, 2018; Munaro et al., 2021). However, these studies seldom explicitly address or operationalize the concept of “indirect experience.” For instance, Kozinets (2002) found that consumers actively engage with brands and products through online communities and virtual spaces. These engagements involve consumers’ indirect experiences such as sharing opinions and recommendations, which contribute to shaping consumers’ perceptions of and attitudes toward a particular brand or product. Brodie et al. (2011) suggested that although consumers do not directly interact with a product or brand, their engagement with media content can still profoundly impact their overall consumption experience and subsequent behaviors. Hollebeek et al. (2014) highlighted that consumer engagement that manifests in the form of active interactions, sharing content, and participating in brand-related activities positively influences brand relationship quality, satisfaction, and loyalty. To assess consumer engagement, studies have gathered data on various metrics, including total views and the number of likes, dislikes, comments, and shares, which can be considered as indirect experiences of YouTube viewers (Kujur & Singh, 2018; Munaro et al., 2021). Studies have also explored the relationship between consumer engagement and various aspects of media-mediated experiences (i.e., indirect experiences). However, in the present study, we explore indirect experiences mediated through media platforms by leveraging consumer engagement.

Consumer engagement

Consumer engagement is the active and meaningful involvement of consumers in various brand-related activities and interactions. Scholars have explored the concept of engagement across various contexts, including social media (Hollebeek et al., 2014), retail (Vivek et al., 2014), and services (Jaakkola & Alexander, 2014). While some studies have focused on a single dimension of engagement such as behavior, there is a growing trend in conceptual and qualitative research to consider multiple dimensions and acknowledge the behavioral, affective, and cognitive aspects of engagement (Dessart et al., 2016; Hollebeek et al., 2014; Van Doorn et al., 2010). Behavioral engagement involves consumers’ observable actions and behaviors such as active participation, advocacy, brand-related content sharing, and purchase behavior (Hollebeek et al., 2014; Van Doorn et al., 2010). Affective engagement focuses on consumers’ affective and emotional responses, including their positive feelings, identification with the brand, and emotional attachment (Dessart et al., 2016; Hollebeek et al., 2014). Cognitive engagement pertains to consumers’ mental processes and activities such as their attention, information processing, and cognitive involvement with the brand (Hollebeek, 2011; Mollen & Wilson, 2010). However, while research has examined the motivational, social, and interactive dimensions of consumer engagement (Brodie et al., 2011; Chandler & Lusch, 2015), the optimal representation of engagement lacks consensus and no shared understanding of the dimensions involved exists (Dessart et al., 2016).

Gavilanes et al. (2018) suggested digital consumer engagement, which refers to consumers’ interactions with a domain (e.g., product, brand, and service) through the media, leading to measurable responses such as clicks, likes, comments, and shares (see also Munaro et al., 2021). They also suggested stages of digital consumer engagement based on the level of consumer investment required to elicit reactions. At a low level of engagement, consumers engage with content by clicking on posts to consume the information provided. This requires minimal investment from consumers, as their involvement is limited to consuming content without participating or contributing actively. At the moderate level, consumers click the “like” button. This reflects a more active and engaged response from them, as they express their appreciation or approval of the content through this interactive feature (Banerjee & Chua, 2019; Gavilanes et al., 2018). At a high level of digital consumer engagement, consumers write comments, which demands more time and cognitive effort (Gavilanes et al., 2018; Labrecque et al., 2020; Yoon et al., 2018), as it requires them to invest their mental resources in formulating a position and contributing their thoughts or opinions. Hence, when users take the time to write a comment, it signifies a higher level of engagement, as it involves a deeper level of personal investment (Sabate et al., 2014). These actions, driven by the indirect experiences of YouTube content, can be considered to be consumer engagement (Munaro et al., 2021).

Cultural experience in the media

Over the past few decades, advancements in transportation and information and communication technologies have revolutionized the way people connect, interact, and conduct business across borders. Media platforms have facilitated cultural exchange by showcasing diverse forms of entertainment, films, music, and literature from different parts of the world. Thus, it is possible to have indirect experiences of foreign cultures through various media platforms without physically visiting these places. In addition, media platforms are a medium through which individuals share their firsthand cultural encounters, allowing others to access and partake in these experiences indirectly.

Specifically, this study focuses on the consumption of traditional costumes by global consumers to explore direct and indirect cultural interactions. Clothing consumption—as a cultural experience—is examined for two reasons. First, traditional costumes, which embody cultural heritage and customs, vary in terms of their silhouettes, colors, textiles, details, and dressing styles across countries and populations (Al-Shehri & Al Dabbagh, 2021). Therefore, exploring global consumers’ consumption of traditional clothing provides valuable insights into how foreign cultures are transferred to and by a global audience (Jo & Ha, 2018). Second, global consumers have limited opportunities to encounter or experience traditional costumes from other countries, as such costumes are not typically worn in daily life. Consequently, the indirect experiences of traditional costumes have gained popularity among young global consumers, primarily through social media (Choi et al., 2017).

Thus, this study explores how consumers can have direct and indirect cultural experiences through YouTube, a typical social media platform in terms of its user-generated content, high level of social interaction, and algorithm-driven recommendation system (Banerjee & Chua, 2019; Gavilanes et al., 2018; Lobato, 2019). YouTube allows individuals, content creators, and businesses to upload and share videos with wide-ranging audiences. Users can like, dislike, comment on, and share videos, all of which allow for engagement and interaction with both content creators and other viewers. The recommendation system on YouTube promotes exploration and serendipitous discovery, contributing to the social and interactive nature of the platform (Lobato, 2019). These features offer users the opportunity to experience the direct and indirect aspects of other cultures. For example, consumers can obtain direct experiences with traditional costumes by attending cultural festivals and events. On such occasions, consumers can actively engage with costumes by trying them on, feeling the fabric, observing the intricate details closely, and immersing themselves in the experience of wearing them. Videos of these experiences can be uploaded and shared on YouTube. Through detailed descriptions, historical backgrounds, and explanations of cultural significance, YouTube viewers indirectly consume the experiences shared in these videos. Although physical interaction is absent, viewers can observe the costumes being worn and listen to YouTubers’ insights and commentaries. These experiences serve as a means for consumers to acquire knowledge, develop appreciation, and find inspiration about traditional costumes.

Methods

Research questions

With the rapid development of technology and media, there are increasing opportunities to indirectly experience other cultures without direct exposure. This study investigates direct and indirect cultural experiences by examining how global consumers engage with Korean traditional costumes, specifically the Hanbok, through the analysis of YouTube content. Direct experiences are explored by investigating videos in which Hanbok-related experiences are depicted. Viewers’ reactions to these videos, including metrics such as the number of views, likes, and comments, serve as indicators of their indirect experiences. These forms of indirect experiences, as showcased on YouTube, have also been widely employed as measures of consumer engagement in prior research (Kujur & Singh, 2018; Munaro et al., 2021).

This study seeks to:

• 1. Investigate how YouTubers portray Hanbok experiences in their video content.

• 2. Investigate the nature of the indirect Hanbok experiences of viewers through their engagement on YouTube.

• 3. Analyze the influence of YouTubers’ Hanbok experiences on the engagement of viewers on YouTube.

Data collection

This study collected user-generated video content on YouTube as a source of direct experiences. The title and description of the video content, as written by the YouTubers themselves, were collected using TEXTOM, an online data crawling platform for text mining. A total of 550 samples were collected with the keyword “Hanbok experience.” This term was selected after careful consideration and preliminary research, which identified it as the most direct and prevalent term used in YouTube content related to our study’s focus. Additionally, a keyword search volume analysis on YouTube was conducted, which revealed that “Hanbok experience” is a highly searched term.

These videos were published between January 1 and December 31, 2022. This timeframe was chosen because the apparel category, including traditional attire such as the Hanbok, is highly seasonal. Analyzing a full year’s data allowed us to observe all seasonal influences. Additionally, we limited our collection to 2022, as we aimed to examine the most recent dataset to provide up-to-date insights.

The captioned transcripts were also crawled using Python. Google’s YouTube API was used to extract all available autogenerated captions from the videos, as the API converts audio into textual data and saves them as Json files. These automated captions from YouTube have been used in previous analyses (Munaro et al., 2021; Turenne, 2023). The title, text information, and transcript data were integrated for the analysis.

Viewers’ reactions to YouTubers’ video content were collected as the indirect Hanbok experiences. Their reactions included numerical and textual forms of data. The numbers of views, likes, and comments on the 550 videos (i.e., numerical data) were gathered as an indicator of consumer engagement (Kujur & Singh, 2018; Liu et al., 2021; Munaro et al., 2021; Van Noort & Willemsen, 2012). Comments were collected as textual data and extracted using Python with Google’s YouTube API. Of the 550 videos, only 249 had comments.

Data preprocessing

The collected textual data were preprocessed by employing natural language processing techniques, using the Natural Language Toolkit (www.nltk.org) in Python. Natural language processing techniques, including tokenization, lemmatization, and tagging, are essential for enhancing the accuracy and relevance of unstructured textual data. Initially, we removed non-English words from the dataset to address the diverse linguistic backgrounds of the commenters, followed by word-level text tokenization. Tokenization segments sentences into individual words and punctuation marks. This was an essential step, as our analysis required isolating words to use the LIWC tool effectively. Consequently, N-gram analysis was not used, as it combines consecutive words into single entities, which does not align with the LIWC framework designed for single-word tokens. Subsequently, all the text was converted into lowercase letters to maintain consistency. Numbers, punctuation, and stopwords, including common words such as “the,” “in,” “to,” “a,” and “an,” were removed using the Natural Language Toolkit’s stopwords dictionary, which was supplemented manually with additional stopwords unique to our dataset. These included onomatopoeic words, typographical errors, and other irrelevant terms frequently encountered in the automated captions.

Following the initial cleanup, we proceeded with further preprocessing steps. Stemming was applied to reduce the words to their base forms (e.g., converting “wearing” to “wear”). Next, lemmatization was conducted, a process that accounts for the morphological analysis of words, thereby transforming them into their lemmas. This step ensures that words such as “went” are accurately converted to “go” considering the word’s part of speech and context. Finally, part-of-speech (POS) tagging was carried out, where each word in the dataset is tagged with its corresponding part of speech (e.g., nouns, verbs, and adjectives). For our analysis, only nouns, adjectives, verbs, and adverbs were considered.

Data analysis

This study applied a two-step process for the data analysis, which included latent Dirichlet allocation (LDA) topic modeling and simple regression analysis, based on the two data types, namely textual and numerical data. The analysis proceeded as shown in Fig. 1.

Fig. 1

The procedure followed in this study

An LDA algorithm was used to extract the topics concerning direct and indirect Hanbok experiences separately using Python. LDA assumes that each document comprises several topics and that each topic is a probability distribution over a set of words. The algorithm uses this assumption to identify the most likely topics for each document based on the words used in it. It then estimates the probability distribution of the words for each topic based on the words that are most likely to appear in documents assigned to that topic. Therefore, LDA can discover hidden topics from a large volume of documents and extract meaningful insights from large collections of user-generated textual data such as social media posts and customer reviews. After identifying the topics, a qualitative investigation was conducted to uncover how each theme was leveraged.

Two types of numerical data were analyzed. First, textual data on direct experiences were transformed into numerical data using the fifth version of the LIWC program (LIWC-22), which updates the original application with increasingly expanded dictionaries (Boyd et al., 2022; Pennebaker et al., 2015). LIWC has been used for text analysis in studies on linguistics, psychology, and marketing (Alzate et al., 2022; Munaro et al., 2021; Zhang, 2019). Furthermore, LIWC’s validity and reliability has been supported by many studies across different contexts and languages (Alpers et al., 2005; Bantum & Owen, 2009; Tausczik & Pennebaker, 2010). It uses the word-count strategy and generates indicators by calculating the percentage of words that fit a predefined dictionary (Zhang, 2019). Based on this dictionary of approximately 12,000 words, word stems, phrases, and select emoticons, LIWC calculates the proportion of the text that can fit into particular categories and helps researchers determine the characteristics of the textual data. Thus, previous studies have established that LIWC output measures can be indicative of underlying psychological and behavioral factors (Alzate et al., 2022; Munaro et al., 2021; Zhang, 2019; Park, 2019; Stone & Can, 2020). For instance, Park (2019) analyzed online consumer reviews of accommodations and used LIWC categories to quantify consumer values, indicating that hedonic value was matched with “positive emotions,” user burdens with “negative emotions,” expectation confirmation with “comparisons,” and pragmatic value with “work, leisure, and home” among the LIWC categories. This approach allowed for a better understanding of consumer sentiment and psychological aspects directly from the textual data.

Second, the number of likes, views, and comments for each video was integrated into the variable as a proxy for the overall engagement of viewers (the indicator of indirect experiences). Given that each video had varying numbers of likes, views, and comments and considering the differing levels of importance of these metrics, we used the arithmetic mean method for this integration (Kujur & Singh, 2018). Weightage was calculated and applied to each parameter using the analytic hierarchy process (Kujur & Singh, 2018; Saaty, 1980) to ensure a pairwise comparison of the parameters and determine their relative importance. To construct a pairwise comparison matrix, three experts were asked to rate their responses on Saaty’s fundamental scales, such as how important was “Like (Comment, View)” compared with “Comment (View, Like)” with respect to consumer engagement while watching YouTube (Extremely unimportant = 1/9, Equal importance = 1, Extremely important = 9). The three responses were aggregated using the analytic hierarchy process template. Table 1 presents the matrix. The following formula was used to calculate viewers’ overall engagement:

$${\text{Overall engagement}} = \frac{{0.{557 } \times {\text{ Comments }} + \, 0.{32}0 \, \times {\text{ Likes }} + \, 0.{123 } \times {\text{ Views}}}}{{\text{Total viewers}}}$$

Table 1 The normalized pairwise comparison matrix and weightage results

The numerical data transformed by LIWC and the composite variable of consumer engagement were used in the simple regression analysis conducted using SPSS 26.0 to explore the effect of Hanbok experiences (direct experiences) on viewers’ overall engagement (indirect experiences).

Results

LDA topic modeling results for Hanbok experiences

YouTubers’ intentions could influence the depiction of direct Hanbok experiences in their videos, particularly with regard to promotional or advertising content. Hence, before applying LDA topic modeling, we analyzed the top 100 words using the Term Frequency and Term Frequency-Inverse Document Frequency methods to understand the content’s nature. Our analysis revealed no promotional language, which validated the subsequent use of LDA topic modeling to uncover the primary themes across the collected documents.

To identify the main themes that underlie our large number of documents, the coherence score was extracted from the LDA algorithm to determine the appropriate number of topics. This algorithm measures the degree of semantic similarity among the top-ranked words within each topic. Higher coherence scores indicate that the words within a topic are more semantically related and that the topic is more coherent; therefore, the topics are well-defined and easily interpretable. The most appropriate number of topics was determined as seven groups for a coherence score of 0.343. Therefore, we applied the LDA algorithm based on seven topics and analyzed the related content. We examined the content by lowering the parameter λ ≥ 0.5 to explore more specific and diverse topics tailored to the content of each document (Blei et al., 2003). Using the set of keywords returned by the LDA algorithm, the name of each topic was identified from the logical connection among the most frequently mentioned words pertaining to a topic. For example, in Table 2, the topic name “Sensory experience” is based on words such as “memory,” “visual,” “cozy,” “enchant,” “neighborhood,” “comfort,” “autumn,” “travel,” “northern,” and “snap,” all of which appear at the top of the list. After the topic names were identified, logical connections presented in the original document were checked to verify them.

Table 2 Seven topics of Hanbok experiences

As shown in Table 2, the Hanbok experiences depicted in the YouTube videos were categorized into novelty, sensory, daily, cultural, trial, pleasing, and intellectual experiences. Novelty experiences emphasize encountering something new, unique, or unfamiliar that can evoke a sense of novelty and excitement about the Hanbok. Jeong and Park (1997) proposed four dimensions of novelty experiences in tourism: thrill, deviation from routine, alleviation of boredom, and surprise. The keywords such as “Muslim,” “discover,” “search,” and “episode” extracted from the videos suggested that YouTubers engaged in unconventional and unique experiences. Sensory experiences refer to the perception and stimulation of the senses such as sight, hearing, touch, taste, and smell (Kim & Sullivan, 2019) during the consumption of the Hanbok itself. The analysis of the keywords extracted showed that YouTubers had positive and memorable moments while experiencing the aesthetic aspects of the Hanbok (Hwang & Hyun, 2012; Schmitt, 1999). Daily experiences involve wearing the Hanbok in everyday life, indicating its adoption as a standard choice of clothing, rather than as an outfit reserved solely for special occasions and cultural events. This category includes video content depicting foreigners purchasing Hanbok school uniforms and modern Hanbok clothing for regular use. The keywords related to the daily experience indicated that YouTubers showcased their everyday routines and activities while dressed in the Hanbok. Cultural experiences include immersion into and engagement with Korean culture by wearing and appreciating the Hanbok. They encompass the exploration and celebration of the historical, artistic, and symbolic elements associated with the Hanbok as a representation of Korean heritage (Lee & Lee, 2019). Trial experiences refer to the actions, behaviors, and activities associated with wearing the Hanbok for the first time and engaging in related experiences. They encompass the practical aspects of trying on/renting Hanbok clothing and visiting cultural sites while dressed in a Hanbok. For example, YouTubers discussed their Hanbok trying on and renting experiences, particularly in popular tourist destinations such as Gyeongbokgung and Changdeokgung Palace. Pleasing experiences refer to the emotions and affective responses that YouTubers experienced while engaging with the Hanbok, such as joy, admiration, excitement, love, and a sense of aesthetic appreciation (Hwang & Hyun, 2012; Manthiou et al., 2016). Finally, intellectual experiences involve cognitive and intellectual engagement such as studying, discussing, analyzing, and gaining knowledge on the cultural traditions around and historical significance and contemporary interpretations of the Hanbok (Manthiou et al., 2016).

LDA topic modeling results for viewer engagement

LDA topic modeling was conducted on the comments left by viewers on the YouTube videos on the Hanbok to explore engagement as their indirect experiences. Based on the highest coherence score, the number of topics was extracted. The most appropriate number of topics was determined as five groups for a coherence score of 0.349. The themes investigated by LDA topic modeling were interpreted based on the context in which the keywords were used in the original documents. Each topic name was determined given the nature of consumer engagement in the literature (Dessart et al., 2016), namely social, cognitive, learning, behavioral, and affective engagement, as shown in Table 3.

Table 3 Five topics of viewer engagement

Behavioral engagement encompasses the observable behaviors and expressions of viewers (Hollebeek et al., 2014; Van Doorn et al., 2010). The keywords extracted imply viewers’ actions such as expressing admiration, watching videos attentively, visiting related places, trying on outfits, and expressing happiness or excitement. Affective engagement encompasses viewers’ feelings, sentiments, and emotional connections toward Hanbok-related content (Dessart et al., 2016; Hollebeek et al., 2014; Van Doorn et al., 2010). Keywords such as “love,” “princess,” “amaze,” “adorable,” “beautiful,” and “cute” indicated viewers’ emotional reactions such as expressing love and admiration, being amazed by beauty, finding the content cute or adorable, and cherishing memorable experiences. The cognitive engagement of viewers was identified through keywords such as “beautiful,” “look,” “great,” “wonderful,” and “new,” which presented their appreciation for the content and recognition of its quality, aesthetics, and positive attributes. The behavioral, affective, and cognitive aspects are the most frequently discussed forms of engagement in the literature (Dessart et al., 2016). The presence of keywords such as people’s names (e.g., Ollie, Jaehyun, Sana, Josh, and Aco) in viewers’ comments indicated their engagement in social interactions (Vivek et al., 2014). The concept of learning engagement was proposed by Dessart et al. (2016) as a dimension of consumer engagement. In this study, learning engagement was defined as viewers’ active involvement in seeking content, information, experiences, ideas, and other resources from their engagement with YouTube videos. The viewers’ comments demonstrated learning engagement by expressing their interest in topics such as valid information on the Hanbok, dress sizes, and Korean culture, gratitude for the information provided, and excitement and/or surprise at the content presented.

The effects of Hanbok experiences on viewers’ overall engagement

A simple regression analysis was conducted to explore the impact of YouTubers’ Hanbok experiences on viewers’ overall engagement with the video content. Numerical data that were transformed from textual data extracted from YouTubers’ videos were used as the independent variables. A composite variable of consumer engagement was employed as the dependent variable. Textual data were entered into the LIWC program for the sentiment analysis, which compares and classifies each word in an extract of text against and into predefined word categories, respectively, and then calculates the number of words that match each dictionary (Pennebaker et al., 2015). For example, in a dictionary installed in LIWC, the words “good,” “love,” “happy,” and “hope” were grouped under “positive” emotions and the words “bad,” “hate,” “hurt,” and “tired” were grouped under “negative” emotions. The scores of the categories given by LIWC were calculated to explore the types of Hanbok experiences that were depicted through YouTube videos. In previous studies, this methodology has successfully transformed qualitative data into a numerical format, allowing for its further examination using statistical tools (Alzate et al., 2022; Munaro et al., 2021; Zhang, 2019; Park, 2019; Stone & Can, 2020).

Cultural, sensory, trial, pleasing, and intellectual experiences were measured using LIWC categories such as ethnicity, visual/feeling, lifestyle, positive emotion, and curiosity. These categories were chosen based on the earlier LDA topic modeling results. In the LIWC dictionary, the Ethnicity category includes terms related to national, regional, ethnic, and cultural identities (Boyd et al., 2022), making it relevant to the concept of cultural experiences. Sensory experiences are defined as the detection of objects through sensory organs, encompassing visual, auditory, tactile, and olfactory sensations (Brakus et al., 2009; Hwang & Hyun, 2012), thus corresponding with the Visual and Feeling categories in LIWC, which together represent both tactile sensations and emotional responses. Trial experiences are understood as an individual’s initial interaction with the activities associated with a particular lifestyle (Lee & Kang, 2012). Accordingly, it aligns with the Lifestyle category in LIWC, encompassing behavioral aspects related to domains such as school, home, and leisure activities (Boyd et al., 2022). Pleasing experiences, which involve subjective feelings, sentiments, and emotions (Hwang & Hyun, 2012), were found to be predominantly positive in the LDA topic modeling results, leading to the selection of the Positive Emotion category for the analysis. Finally, intellectual experiences concern an event or place’s capacity to provoke thought or curiosity (Lee & Kang, 2012), which is why the Curiosity category was deemed appropriate. However, novelty and daily experiences, as identified through the LDA topic modeling, did not align with any of the categories in the LIWC dictionary and were excluded from the analysis. Tables 4 and 5 describe the variables, measurements, and descriptive statistics used in this study.

Table 4 Independent variable information and descriptive statistics

Table 5 Dependent variable information and descriptive statistics

The results of the simple regression analysis showed the significant main effects of cultural (β = 0.238, p < 0.01) and affective Hanbok experiences (β = 0.229, p < 0.05) on the engagement of viewers. However, the main effects of sensory (β =  − 0.143, p = 0.086), trial (β =  − 0.010, p = 0.897), and intellectual experiences (β =  − 0.036, p = 0.639) were not significant. These findings suggest that among the dimensions of Hanbok experiences depicted in the YouTube videos, cultural and pleasing experiences play a more influential role in driving viewer engagement. The cultural experience of the Hanbok involves exploring and celebrating its historical, artistic, and symbolic significance as an emblem of Korean heritage. Pleasing experiences, which encompass emotions such as joy, admiration, and excitement, appeared to elicit a positive response and contribute to viewer engagement (Fig. 2).

Fig. 2

Results of the simple regression analysis

Discussion

YouTubers’ Hanbok experiences included novelty, sensory, daily, cultural, trial, pleasing, and intellectual aspects. Their actual experience with the Hanbok, as depicted on YouTube videos, was multifaceted and it encompassed a wide range of experiences and perceptions. This finding aligns with that of Kim et al. (2012), who suggested that a memorable tourism experience comprises seven domains: novelty, refreshment, hedonism, meaningfulness, knowledge, involvement, and local culture. Studies have shown that consumer experiences can be categorized into affective, behavioral, sensory, and intellectual dimensions (Brakus et al., 2009; Manthiou et al., 2016). This study specifically introduced the aspect of daily experiences, emphasizing how global consumers have integrated the Hanbok into their daily routines. This goes beyond the traditional, perhaps ceremonial use of the attire, showcasing the Hanbok in settings such as daily wear, casual outfits for regular activities, or simply as part of an everyday wardrobe. This daily experience reflects a shift from perceiving the Hanbok as exclusively for single events and rare cultural moments to recognizing its role in the routine fabric of life, highlighting its versatility and relevance in modern daily contexts. This perspective offers a richer understanding of the adoption of cultural apparel, suggesting a deeper, more habitual connection with the Hanbok among global consumers.

Viewer engagement with the video content showcasing YouTubers’ Hanbok experiences was examined and classified into social, cognitive, learning, behavioral, and affective aspects. Studies have explored the multifaceted nature of engagement, highlighting its social and interactive (Brodie et al., 2011; Chandler & Lusch, 2015), cognitive (Hollebeek, 2011; Mollen & Wilson, 2010), behavioral (Hollebeek et al., 2014; Van Doorn et al., 2010), and affective aspects (Dessart et al., 2016; Hollebeek et al., 2014). Few studies have focused on learning engagement. However, Dessart et al. (2016) offered insights into the potential for learning engagement by introducing the subdimension of behavioral engagement, which includes activities such as sharing, learning, and endorsing. Building on this, this study revealed that YouTube videos serve as a medium for learning engagement, enabling viewers to gain knowledge about the Hanbok. Through these videos, viewers can learn about its aesthetic aspects (e.g., colors and silhouettes), understand the intricacies of how to wear it, and gain insights into its wear ability and comfort, all without the need for a physical trial. This virtual learning experience broadens viewers’ understanding and appreciation of the Hanbok, highlighting the educational potential of digital content.

Finally, the effect of YouTubers’ Hanbok experiences on the overall engagement of the viewers was investigated. Cultural and pleasing experiences had a significant effect on overall engagement. However, the sensory, trial, and intellectual experiences of YouTubers did not significantly influence viewer engagement. These findings align with those of Dessart et al. (2016), who examined the creation of accommodation experiences in brand hotels. They emphasized the importance of affective and behavioral aspects in influencing the overall experience and noted that intellectual and sensory perspectives played a lesser role. Building on this, the present study discovered that cultural experiences are crucial for broadening the indirect experiences of other consumers. This can be attributed to the intrinsic nature of Hanbok costumes, which embed cultural heritage and significance. The Hanbok, with its rich cultural heritage, provides a unique lens for viewers to explore and appreciate Korean culture. The garment’s aesthetic appeal and historical significance likely enhance the impact of cultural experiences on engagement. Viewers are not just observing the Hanbok’s beauty; they are being immersed in its cultural narrative. This differs from typical tourism experiences, as the Hanbok offers a more aesthetic and personal connection (Al-Shehri & Al Dabbagh, 2021), being worn by individuals rather than simply observed. Such cultural immersion, as presented by YouTubers, may resonate more deeply with viewers, leading to greater engagement than sensory or trial experiences that might lack this cultural depth.

Conclusions

Theoretical and managerial implications

This study suggests several theoretical implications in the domains of cross-cultural and consumer experiences. First, it draws attention to the reciprocal nature of direct and indirect cultural experiences by examining the relationship between YouTube content creators and their viewers. To the best of our knowledge, no study has delved into the relationship between user-generated content and its recipients on social media platforms. While existing research has often separately examined consumers’ direct cultural experiences and their indirect experiences through media, few studies explicitly analyze and validate the interconnection between these experiences. By examining these relationships in the context of Hanbok experiences, we provide insights into how digital platforms enable a simultaneous observation of direct and indirect cultural experiences, a phenomenon less pronounced in traditional media settings. While studies have explored the effect of YouTube content on consumers, this study goes a step further by evaluating data from YouTube through a text-mining approach. It thus provides a foundation for further research and opens up opportunities to explore the dynamics of user-generated content and audience engagement in various cultural contexts.

Second, through text-mining techniques, this study extracts valuable insights from the textual and numerical data found in the YouTube content and viewer reactions. Text mining allows researchers to analyze large volumes of unstructured data such as comments, reviews, and descriptions to uncover patterns, sentiments, and themes. It enables a more comprehensive understanding of the relationship between content creators and their audiences, revealing valuable information on the direct and indirect cultural experiences mediated through social media platforms. However, traditional text mining often uses qualitative approaches to identify themes, a practice that may lead to concerns about its reliability and validity (Bleidorn & Hopwood, 2019; Tay et al., 2020). This study addresses these issues by employing a quantitative methodology, converting textual data into a numerical form through tools such as LIWC for the statistical analysis (Parkinson et al., 2017). This methodological shift bridges a significant gap in the literature, providing a valuable approach for examining the impact and dynamics of user-generated content in the digital landscape.

Third, the results can expand the scope of cross-cultural research that traditionally focuses on direct contact with different cultures. By exploring the indirect cultural experiences mediated through media platforms, this study offers new perspectives and expands the understanding of cross-cultural interactions. Cross-cultural research has studied individuals who have direct physical contact with different cultures such as through traveling, living abroad, and participating in cultural exchange programs. This study adds a valuable dimension to cross-cultural research by highlighting the significance of indirect cultural experiences, which was previously thought impossible.

The managerial implications of this study include the opportunities for leveraging user-generated content. For example, brand managers/marketers can collaborate with content creators or influencers who authentically represent and engage with cultural experiences to reach and connect with global consumers. The findings emphasize the significance of cultural experiences, particularly the affective and cultural dimensions, in driving consumer engagement. Brand marketers should consider incorporating cultural elements into their brand messaging and marketing strategies to resonate with consumers’ interests and enhance engagement. By incorporating culturally relevant references sensitively, brands can establish meaningful connections with global consumers and tap into their curiosity and desire to explore and experience different cultures.

Limitations and directions for future research

This study used a computerized method to extract all available auto-generated captions from the videos for the textual data analysis. While recent studies have also employed automated captions and subtitles for their analyses (Munaro et al., 2021; Turenne, 2023), the inherent limitations of this approach must be acknowledged. These captions, produced by automated speech-to-text processes, may contain inaccuracies due to factors such as background noise, the speaker’s accent, and technical issues (Munaro et al., 2021), leading to potential grammatical and semantic errors. Although a thorough preprocessing phase was conducted to improve the dataset’s quality, residual imperfections might have still affected the analysis. Future research could enhance accuracy by incorporating manual verification into the process or adopting more sophisticated natural language processing technologies.

Second, this study relied on user-generated content and viewers’ reactions on YouTube. For direct experiences depicted in video content, YouTubers may have various motivations for uploading videos to YouTube, including promoting the Hanbok, sharing tourism experiences, and exploring cultural elements. While all experiences shared by YouTubers who have personally engaged with the Hanbok are deemed direct experiences, the nature of these experiences may vary depending on the uploader’s intent. Therefore, future research could explore how the purposes behind YouTubers’ uploads influence their interaction with products and services (i.e., direct experiences) as well as whether these intentions subsequently alter viewers’ reactions (i.e., indirect experiences).

Third, this study did not control for factors such as video duration, the number of subscribers, or the number of shares, consistent with methodologies commonly used in previous research in this field. However, these factors might influence consumers’ indirect experiences with the product or service presented in the videos. Thus, future studies could benefit from including these variables, thereby providing a more comprehensive analysis of the various factors that influence user engagement on platforms such as YouTube.

Finally, the sample of YouTubers and viewers may not be fully representative of the entire population of Hanbok consumers or YouTube users. As a result, the findings might be influenced by the specific characteristics and preferences of the selected sample as well as YouTubers’ purpose and intentions behind their video creation. This limitation may have affected the generalizability of our findings. Additionally, while the text-mining approach provides valuable insights into the content and sentiments expressed, it may not fully capture the subtleties and complexities that could be revealed through direct interviews and surveys. Thus, future research could benefit from adopting a mixed-methods approach that combines big data analysis with direct measurements of consumers’ perceptions. Such an approach would likely yield a more comprehensive understanding of the behaviors associated with cultural experiences.