User-generated Research Articles

Exploring tourist perceptions of calligraphic landscapes: Insights from social media text analysis

Calligraphic landscapes, as distinctive cultural symbols and landscapes with Chinese characteristics, are widely used in urban design, placemaking, and tourism promotion. In cultural heritage tourism, tourists’ perceptions of the symbolic meanings of landscapes significantly influence their travel experiences. This study primarily utilizes social media text analysis to explore the perceptual characteristics and symbolic meanings of calligraphic landscapes in different touristic contexts. Using Python tools, user-generated content was extracted from the Xiaohongshu app and analyzed with ROST CM6, VOSviewer, and NVivo 20 to conduct systematic quantitative and qualitative analyses, including content analysis, semantic network analysis, and co-occurrence clustering. The findings indicate that cultural exchanges on social media significantly enhance public perception of the symbolic meanings of touristic spaces. As online check-in behavior becomes increasingly popular, calligraphic landscapes have gained new esthetic-symbolic meanings among young tourists, becoming part of fashion culture and reflecting the digitalization of a sense of place. In addition, user-generated content reveals that tourists’ perceptions of calligraphic landscapes are intricately linked to place recognition, cultural symbolism, calligraphic appreciation, heritage value, and esthetic experiences. As a significant cultural symbol, calligraphic landscapes are frequently encountered during travel, with their symbolic meanings varying according to the surrounding environment, thereby influencing tourists’ preferences in diverse settings. Furthermore, this study proposes several innovative strategies for designing calligraphic landscapes. This research not only validates the feasibility of web text analysis for exploring the symbolic meanings of cultural landscapes but also enhances theoretical perspectives on how symbolic landscapes shape tourists’ psychological and behavioral responses.

Influence of Social Media Marketing on Destination Choice among European Travelers

Purpose: The aim of the study was to analyze the influence of social media marketing on destination choice among European travelers. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: Social media marketing has a significant influence on destination choice among European travelers, as it shapes their perceptions and decision-making processes. Studies show that platforms like Instagram, Facebook, and YouTube serve as key sources of inspiration and information, with user-generated content and influencer recommendations often playing a pivotal role in shaping travel preferences. Travelers are particularly drawn to visually appealing content, which showcases destinations' attractions, culture, and experiences in an engaging manner. Unique Contribution to Theory, Practice and Policy: Uses and gratifications theory (UGT), social proof theory & elaboration likelihood Model (ELM) may be used to anchor future studies on the influence of social media marketing on destination choice among European travelers. Travel businesses should invest in creating visually compelling content that showcases their offerings. Destination marketing organizations (DMOs) should adopt policies that prioritize high-quality visual content in their marketing strategies.

"I'm in the Bluesky Tonight": Insights from a year worth of social data.

Pollution of online social spaces caused by rampaging d/misinformation is a growing societal concern. However, recent decisions to reduce access to social media APIs are causing a shortage of publicly available, recent, social media data, thus hindering the advancement of computational social science as a whole. We present a large, high-coverage dataset of social interactions and user-generated content from Bluesky Social to address this pressing issue. The dataset contains the complete post history of over 4M users (81% of all registered accounts), totalling 235M posts. We also make available social data covering follow, comment, repost, and quote interactions. Since Bluesky allows users to create and like feed generators (i.e., content recommendation algorithms), we also release the full output of several popular algorithms available on the platform, along with their timestamped "like" interactions. This dataset allows novel analysis of online behavior and human-machine engagement patterns. Notably, it provides ground-truth data for studying the effects of content exposure and self-selection and performing content virality and diffusion analysis.

Liability regulation on short video platforms: balancing freedom of expression and copyright protection

Abstract The rise of short video platforms has fundamentally altered the balance between freedom of expression and copyright protection, challenging traditional legal frameworks like the Safe Harbor Principle. This paper critically examines the evolving legal landscape, with particular focus on the implications of Article 17 of the EU’s Copyright Directive in the Digital Single Market (DSM Directive), especially for small platforms, creators, and users. Through comparative analysis of international legal frameworks and case studies, the study delves into the challenges faced by stakeholders in navigating platform liability, algorithmic content moderation, and user rights. The research highlights how the existing legal environment, while aiming to protect copyright holders, often disproportionately favors large platforms, undermining the expressive freedoms and fair use rights of smaller creators and users. Furthermore, the paper addresses the role of remix culture on short video platforms, discussing how transformative works and user-generated content foster cultural diversity and innovation. It advocates for reforms that balance copyright enforcement with freedom of expression, promoting cooperative licensing models, nuanced content moderation, and expanded fair use exemptions to support a more equitable digital ecosystem where creativity, access, and protection coexist effectively.

“Airbnb Be Like…”: Examining the Impact of Memetic Doppelgängers on Meme Virality and Brand Image

This article examines how internet memes, a distinctive type of user-generated content, have served as a vehicle for the co-destruction of the Airbnb brand. For this purpose, we discuss the relevance of internet memes alongside the doppelgänger brand image concept, which explains the logic behind disparaging brand imagery that circulates within internet culture. A comprehensive research model is developed that links several meme- and user-related characteristics with both meme virality and the brand image of Airbnb. The proposed multilevel model is tested using a split-sample approach on a dataset that includes 121 Airbnb-related memes evaluated by 3,664 participants. The results reveal that the virality of disparaging memes is mainly driven by humor, unambiguity, pictorial format, inoffensive content, and “active” user status. The perceived brand image is, however, mainly affected by the valence (negativity) of the memes, while the meme content and user status are also important.

Natural Language Processing and Machine Learning-Based Solution of Cold Start Problem Using Collaborative Filtering Approach

In today’s digital era, the abundance of online services presents users with a daunting array of choices, spanning from streaming platforms to e-commerce websites, leading to decision fatigue. Recommendation algorithms play a pivotal role in aiding users in navigating this plethora of options, among which collaborative filtering (CF) stands out as a prevalent technique. However, CF encounters several challenges, including scalability issues, privacy implications, and the well-known cold start problem. This study endeavors to mitigate the cold start problem by harnessing the capabilities of natural language processing (NLP) applied to user-generated reviews. A unique methodology is introduced, integrating both supervised and unsupervised NLP approaches facilitated by sci-kit learn, utilizing benchmark datasets across diverse domains. This study offers scientific contributions through its novel approach, ensuring rigor, precision, scalability, and real-world relevance. It tackles the cold start problem in recommendation systems by combining natural language processing (NLP) with machine learning and collaborative filtering techniques, addressing data sparsity effectively. This study emphasizes reproducibility and accuracy while proposing an advanced solution that improves personalization in recommendation models. The proposed NLP-based strategy enhances the quality of user-generated content, consequently refining the accuracy of Collaborative Filtering-Based Recommender Systems (CFBRSs). The authors conducted experiments to test the performance of the proposed approach on benchmark datasets like MovieLens, Jester, Book-Crossing, Last.fm, Amazon Product Reviews, Yelp, Netflix Prize, Goodreads, IMDb (Internet movie Database) Data, CiteULike, Epinions, and Etsy to measure global accuracy, global loss, F-1 Score, and AUC (area under curve) values. Assessment through various techniques such as random forest, Naïve Bayes, and Logistic Regression on heterogeneous benchmark datasets indicates that random forest is the most effective method, achieving an accuracy rate exceeding 90%. Further, the proposed approach received a global accuracy above 95%, a global loss of 1.50%, an F-1 Score of 0.78, and an AUC value of 92%. Furthermore, the experiments conducted on distributed and global differential privacy (GDP) further optimize the system’s efficacy.

Beyond Text: Multimodal Credibility Assessment Approaches for Online User-Generated Content

User-generated content (UGC) is increasingly becoming prevalent on various digital platforms. The content generated on social media, review forums, and question–answer platforms impacts a larger audience and influences their political, social, and other cognitive abilities. Traditional credibility assessment mechanisms involve assessing the credibility of the source and the text. However, with the increase in how user content can be generated and shared (audio, video, and images), multimodal representation of UGC has become increasingly popular. This article reviews the credibility assessment of UGC in various domains, particularly identifying fake news, suspicious profiles, and fake reviews and testimonials, focusing on both textual content and the source of the content creator. Next, the concept of multimodal credibility assessment is presented, which also includes audio, video, and images in addition to text. After that, the article presents a systematic review and comprehensive analysis of work done in the credibility assessment of UGC considering multimodal features. Additionally, the article provides extensive details on the publicly available multimodal datasets for the credibility assessment of UGC. In the end, the research gaps, challenges, and future directions in assessing the credibility of multimodal UGC are presented.

Kiswahili Translation in Digital Media Platforms: Bridging Language Gaps in the AI Age

Purpose: As digital media platforms continue to proliferate globally, the need for multilingual content in these platforms has become increasingly apparent. Translation of online content is a necessity for netizens and other digital platform users who seek knowledge and information around a myriad of user-generated content on diverse issues and topics. Being a widely spoken language that goes beyond the borders of East Africa, Kiswahili’s significance in bridging linguistic barriers and facilitating communication and information access for Kiswahili speakers is clear. The purpose of this exploratory research paper was to examine the state of Kiswahili as a language of translation through different technologies across varied translation apps and social media platforms such as Facebook, You Tube, Tik Tok and Netflix. Methodology: The study adopted a descriptive research design. Data collection was done through online data mining tools including API access for web scrapping and manual extraction of content through random search engine searches. The data for the study included 10 sentences, 10 videos and 25 specific word forms such as proverbs, spiritual/religious words, similes and cultural words for food, beauty and family ties. Content analysis for both text and multimedia content such as written sentences, social media posts and videos was done. The study analyzed translation outputs of 14 Kiswahili translation apps in order to establish the status and accuracy of these translations. Of key consideration was the role of AI technology in the translation apps and the effect it has on the translated texts across different apps. The challenges and emerging issues facing Kiswahili translation through digital technologies were also explored. Findings: The findings of this study showed that the Apps used for Kiswahili translation have demonstrated great translation accuracy in basic semantic forms, with an average score of 60% accuracy upon random searches and between 10-30% accuracy for cultural forms and idiomatic expressions. Unique Contribution to Theory, Practice and Policy: The study was guided by the Skopos theory by Hans Vermeer (1978) which was complemented by the Relevance Theory by Dan Sperber and Deidre Wilson (1986). These Apps seem to have the feature of interoperability in that they seem to produce the same results suggesting that the AI supported feature in the apps may be interconnecting the apps during translation. The study advocates for more AI integration translation apps as this will help standardize Kiswahili translation corpus.

User-Generated Contents and Brand Loyalty of Skinscare Products in Port Harcourt

This paper empirically investigated the relationship between User-Generated Contents and Brand Loyalty of Skincare Products in Port Harcourt. Specifically, the objectives of the study were to determine how user authenticity and user engagement rate relate with customer satisfaction and repeat patronage of skincare products in Port Harcourt. The correlational research design was adopted and the population of the study was infinite. Topman’s formula was used to generate a sample size of 384 customers. However, only 262 respondents provided data for the study through questionnaire that was designed in the Likert 5-point scale of strongly disagree to strongly agree. Spearman Correlation (rho) was used to four hypotheses. From results of the analysis it was revealed that user authenticity and user engagement rate which are the proxies of user-generated contents positively and significantly relate with customer satisfaction and repeat patronage (i.e. measures of brand loyalty) of skincare products in Port Harcourt. Based on these findings, it was concluded that both factors have a very strong and positive impact on customer loyalty, with authenticity playing a particularly crucial role in shaping customer perceptions and trust. The strong relationship between user engagement and repeat patronage further highlights the importance of fostering active and meaningful interactions with customers. Therefore, the study recommended amongst others that skincare brands should encourage genuine customer reviews and testimonials by creating platforms where customers feel comfortable sharing their honest experiences. Authentic content resonates more with potential buyers, fostering trust and leading to higher customer satisfaction and repeat purchases.

The Influence of Social Media Communication Towards Customer-Based Brand Equity on Netflix

This study aims to analyze how social media communication seen from user-generated content, firm-generated content, and distribution intensity affects customer-based brand equity on Netflix. Respondents in the study were 321 Netflix subscribers. This study uses a lower-order construct as a research model. Based on the results of research that has been conducted, show that firm-generated content (FGC), user-generated content (UGC), and distribution intensity (DI) affect customer-based brand equity (CBBE) at different levels. Although UGC has a smaller effect size compared to FGC, it still has significant relevance. Distribution intensity is important for increasing brand awareness and loyalty, although it has no direct impact on perceived quality. This in-depth understanding can guide marketing and brand management decisions to effectively utilize these components.

Developing Marketing Strategy for User-Generated Content: Study Case for Company X

This study investigates strategies to enhance user-generated content (UGC) growth for Company X, a part of Company X, to address the declining trend in UGC contributions and increasing operational costs. The study employs a qualitative methodology, including in-depth interviews with Company X users and content creators, to identify user personas, motivations, and preferences. External analyses such as PESTEL, competitive analysis, and internal SWOT analysis are used to frame the problem. The results suggest that enhancing the reward system, aligning incentives with user expectations, and improving platform engagement can increase UGC contributions. The proposed strategies aim to leverage UGC to reduce costs and boost user engagement and retention, supporting Company X’s future growth.

Understanding content dissemination on sensemaking: WHO’s social listening strategy on X during the initial phase of COVID-19

Abstract Purpose Guided by the Crisis and Emergency Risk Communication model (CERC, Reynolds and Seeger 2005. Crisis and emergency risk communication as an integrative model. Journal of Health Communication 10(1). 43–55.), the present study aimed to study how X (formerly Twitter) users sensemaking and efficacy based message. Additionally, the study also aimed to understand how the World Health Organization (WHO) responded to the emerging conversation. Methods Unsupervised machine learning was conducted on 6.1 million tweets between January and March 2020 to understand sensemaking about COVID-19 among X users. Additionally, content analysis was used to examine if the World Health Organization (WHO) responded to popular emerging conversations via content on their own X handle. Findings The majority of dominant topics in COVID-19 tweets from January to March 2020 related to understanding the virus and the crisis it caused. X users tried to make sense of their surroundings and re-create their familiar world by framing events. Content analysis revealed that WHO engaged in effective social listening and responded quickly to dominant X conversations to help people make sense of the situation. Practical Implications The initial stage of COVID-19 pandemic was marked with uncertainty. However, WHO had a robust communication strategy and addressed the dominant conversation during the time frame including debunking misinformation. Originality/Value The present study fills the research gap by situating the themes in the context of the health crisis and extending the CERC model to user-generated content via the lens of sensemaking and efficacy messages during the COVID-19 pandemic. Additionally, the study segmented the timelines into smaller time intervals to understand how sensemaking evolved over time.

Examining the Impact of Social Media Marketing on Consumer Purchase Intentions: Insights from Content, Influencer, and User-Generated Content Strategies

How social media affect the customers behavior plays an essential role for enterprise who aiming to thrive in a competitive market under the rapid digital platforms development and increasing amount of time people spend online. Social media platforms are the main source of information, entertainment and interaction, as well as the significant tool of marketing and customer engagement. The article emphasizes multiple influences of social media to customer determination through analyzing content, influencer and user generated content (UGC) marketing. Content marketing involves generating valuable and pertinent information to engage and sustain a specifically targeted audience, whereas influencer marketing utilizes the influence and credibility of prominent figures to endorse products and brands. UGC, on the other hand, provides authentic, peer-driven content that resonates with potential customers. These strategies comprehensively enhance the brand reputation, emotional resonance and consumer trust to drive purchase decisions and facilitate success. The study reveals that effective social media tactics can improve customer engagement and credibility, further increase the purchase intention, and conversation. These findings underscore the importance of integrating comprehensive social media strategies into marketing plans to positively influence consumer behavior and achieve business objectives.

Douyin—— the leading application in short video in the next decade

In recent years, along with the comprehensive innovation of communication technology, new media has also achieved rapid development and gradually penetrated into various fields. According to the 48th Statistical Report on the Development of the Internet in China released by the China Internet Network Information Center, as of June 2021, the number of Internet users in China has reached 1.011 billion, of which 888 million are short video users, accounting for 87.8% of the total Internet users. According to the survey results of the products most commonly used by short video users from 2020 to 2021, Douyin ranked first with 45.2%. As one of the emerging social media, Douyin short video APP is different from the previous simple graphic social, but the combination of music, special effects and video, so as to closely connect users of different ages, industries and identities. Based on this, this paper will discuss the possibility of Douyin platform to achieve fine operation and further expand market share by optimizing user generated content (UGC) model and analyzing the personality and commonality of audience psychology.

The Impact of Social Media Marketing on the Energy Drink Industry: A Case Study of Red Bull

As Red Bull domains in the market share and is well-known for its special social media marketing strategy, this article intend to explore how Red Bull’s approach to marketing, particularly through social media, has been instrumental in building its brand identity and connecting with consumers. Through an in-depth analysis of Red Bull’s strategies on various social media platforms, this study examines the company’s distinctive approach, particularly its use of Search Engine Optimization (SEO). The analysis highlights the most prominent features and advantages of each platform, revealing how Red Bull has successfully built a strong brand image and expanded its brand influence by leveraging the power of social media. Undeniably, this success stems from Red Bull’s strategic approach of tailoring its brand message to suit each platform, thereby maximizing the utility and impact of its social media presence. The study aslo provides further actionable recommendations for Red Bull to enhance its social media strategy. Key suggestions include increasing the use of User-Generated Content (UGC) to reduce production costs and enhance authenticity, optimizing resource allocation through data-driven analysis to focus on high-impact marketing activities, and forming strategic partnerships to share costs and resources, thereby expanding reach and boosting brand presence. These strategies not only address current challenges but also offer a blueprint for other companies aiming to refine their social media marketing efforts.

Social Media and Events: A Curated Collection of Articles Published in Event Management From 2015 to 2022

The advent of social media has transformed society in terms of the way information is created and disseminated. In professional and private spheres such as events, social media has evolved to be more than a tool for user-generated content but is also now a heavily adopted technological platform to create competitive advantage. This curated collection examines 21 articles published in Event Management from 2015 to 2022 and identifies the trends, concepts, contexts, and outcomes of social media in events to provide a snapshot of literature to date and what future directions of social media and event research would look like.

Single versus double transseptal puncture for pulmonary vein isolation with radiofrequency catheter ablation for atrial fibrillation - insights from "Go for Zero Fluoroscopy" registry

Abstract Background Transseptal puncture is one of the most challenging steps in catheter ablation of atrial fibrillation (AF) because of the potential risk of complication. While single TSP reduces the puncture-related risk, double TSP simplifies the procedure (immediate signal visualization in pulmonary veins, avoidance of multiple changes of catheters through the single sheath). The purpose of this study was to analyze the impact of single versus double TSP during pulmonary vein isolation (PVI) with radiofrequency (RF) catheter ablation for AF on the fluoroscopy usage and procedure time. Methods Data reported from the international, multicenter prospective „Go For Zero Fluoroscopy Registry" performed in years 2018–2019 were analyzed. Overall 25 European electrophysiology centers from 14 countries and up to 5 operators from each center were enrolled. Only isolated PVI procedures were analyzed. Results A total data of 393 PVI RF procedures were collected from 25 centers. The median dose-area-product (DAP), fluoroscopy time and overall procedure time were: 810 (325 – 1839) cGy*cm2, 8 (4 – 14) minutes and 124 (92 – 168) minutes, respectively. Single TSP was associated with significantly higher DAP: 984 (459 – 1939) vs 667 (227 – 1469) cGy*cm2 (p=0.002), longer fluoroscopy time: 11 (6 – 19) vs 6 (3 – 11) minutes (p<0.001) and longer overall procedure time: 133 (103 – 168) vs 110 (90 – 168) minutes (p=0.003) as compared with double TSP. Single and double TSP group did not differ significantly in regards of general anesthesia usage, circular and multipolar mapping catheter use (p>0.05). However, single TSP was performed by operators with longer EP lab experience: 10 (4 – 15) vs 3 (0 – 10) years (p<0,001). Conclusions Double TSP is related with lower fluoroscopy usage and shorter overall procedure time of pulmonary vein isolation with radiofrequency catheter ablation for atrial fibrillation.

Accessibility of digital healthcare in 2023: insights from a Dutch national survey study

Abstract Background Digital technology is reshaping healthcare, offering potential improvements in accessibility, efficiency and quality. However, to realize potential benefits, ensuring equal access for all is crucial. We investigated digital healthcare usage and studied differences in use across age groups and educational backgrounds in the Netherlands. Methods Surveys were conducted among general healthcare users (n = 837, any citizen living in the Netherlands with access to healthcare) and healthcare users with chronic conditions (n = 1437). We studied their digital skills (can you independently use a computer, tablet or smartphone; digital applications; email and apps?) and their use of digital selfcare (did you use websites for health-related information or treatment?). Findings are stratified for educational level (low/medium/high) and age (15 -39, 40-64, over 65 years). Data collection occurred between April and August 2023, focusing on the twelve months preceding the survey. Results The majority of respondents use digital devices independently (range: 78-91%), but these percentages vary between subgroups, from 48-65% for users with lower education vs 86-99% for users with higher education. Similar differences exist across age groups: 98-100% of users aged 15-39 use a computer, tablet or smartphone, in contrast with 59-78% in the over 65 years age group. Similarly, the use of websites for health information is 22-31% among lower educated users to 68-70% among higher educated users; and 36-48% among those ≥65 years to 73-75% among respondents aged 15-39. Conclusions Substantial variation exists in the use of digital tools and digital selfcare across ages and educational levels. These findings underscore the urgency of addressing inequalities in access to digital healthcare, serving as a call to action for policymakers, healthcare providers, and developers to collectively strive for an accessible (digital) healthcare system for all. Key messages • Differences in use of digital tools and digital selfcare among people of different ages and educational levels warrants the need for co-creation and tailored development and implementation. • Differences in use of digital tools and digital selfcare among people of different ages and educational levels warrants the need for co-creation and tailored development and implementation.

Assessment of digital literacy and user experience in patients with cochlear implants

Abstract Introduction The cochlear implant (CI) is the treatment of choice for people affected by deafness or profound hearing loss. Patients with cochlear implants (PwCIs) can enhance their hearing outcomes using digital hearing training programs (dHTPs). Current technological trends leans towards personalized, AI-driven dHTPs, aiming to optimize user experience (UX) and adherence. This study aims to investigate the digital literacy skills and UX of PwCI before and after testing a prototype of a dHTP with an AI-driven design (TraiCI). Methods Two research-specific questionnaires developed by the Hearing Center Düsseldorf (QDL and QUX) were used to assess digital literacy skills and user experience in TraiCI. Additionally, the User Experience Questionnaire (UEQ) was employed to evaluate general user experience. The UEQ assesses software quality across dimensions such as transparency and stimulation using paired opposites. Results 22 outpatient PwCIs the Hearing Center Düsseldorf with unilateral or bilateral CI (mean age 54 years; SD = 15) were included. In QDL, PmCI demonstrated high levels of digital literacy skills. The majority of PmCI (80.6%) reported prior experience with dHTP. Usage of these programs occurred daily to multiple times per week within the first six months after CI treatment, with session durations predominantly ranging from 10 to 30 minutes. QUX data indicated a smooth initiation process (70.8%) and seamless login experience (95.5%). The UEQ addressed various aspects of user experience, with ‘transparency’ receiving the highest scores (MW = 1.9; SD = 0.6), while ‘stimulation’ received the least positive ratings (MW = 0.0; SD = 2.1). Conclusions The results show a high degree of digital literacy among PwCIs. They encountered minimal challenges in operating hardware and software components. Further refinement is necessary to align with PwCI’s expectations and maximize benefits. Early and iterative involvement of PwCIs in future projects could optimize outcomes. Key messages • The study highlights the proficient digital literacy skills of cochlear implant patients (PwCIs). • Further refinement of dHTPs is needed to better align with PwCIs’ expectations and maximize benefits, emphasizing the importance of iterative involvement for optimized outcomes.

The Dominance of TikTok in Shaping Online Purchasing Intention

In recent years, TikTok has emerged as a dominant force in the realm of social media, captivating millions worldwide with its short-form video content. This paper explores the significant influence of TikTok on consumers' online purchase intentions. Through an examination of relevant literature and empirical studies, the paper elucidates the mechanisms through which TikTok impacts consumer behavior and decision-making processes. It delves into the role of user-generated content, influencer marketing, and algorithmic recommendations in shaping consumer preferences and driving purchase intentions on the platform. Additionally, the paper discusses the unique features of TikTok, such as its immersive and engaging format, personalized content delivery, and seamless integration of e-commerce functionalities, which contribute to its efficacy as a persuasive tool for brands and marketers. Furthermore, the paper highlights the implications of TikTok's dominance for businesses seeking to leverage the platform for marketing purposes and outlines strategies for effectively harnessing its potential to enhance online sales and brand engagement. Overall, this paper sheds light on the transformative influence of TikTok in the digital landscape and underscores its pivotal role in shaping contemporary consumer behavior and purchase intentions.