Mapping the Evolution of Digital Marketing Research Using Natural Language Processing

Abstract

Digital marketing has become a game-changer by combining cutting-edge technologies, insights into how customers behave, and applicability across industries to change how businesses plan and how they interact with customers. Digital marketing is a key part of being competitive, sustainable, and innovative in a world where more and more people are using the internet and social media. Even though this subject is important, the study of it is still scattered, which shows that there is a need to systematically map out its intellectual structure. This research utilizes a bibliometric and topic modeling methodology, analyzing 4722 publications sourced from the Scopus database, including the string “Digital Marketing”. The authors employed Latent Dirichlet Allocation (LDA), a method from Natural Language Processing, to discern latent study themes and Vosviewer 1.6.20 for bibliometric analysis. The results explore ten main thematic clusters, such as digital marketing and blockchain, applications in the health and food industries, higher education and skill enhancement, machine learning and analytics, small and medium-sized enterprises (SMEs) and sustainability, emerging trends and ethics, sales transformation, tourism and hospitality, digital media and audience perception, and consumer satisfaction through service quality. These clusters show that digital marketing is becoming more interdisciplinary and is becoming more connected to ethical and technological issues. The report finds that digital marketing research is changing quickly because of artificial intelligence (AI), blockchain, immersive technology, and reflect it with a digital business environment. Future directions encompass the expansion of analyses to new economies, the implementation of advanced semantic models, and the navigation of ethical difficulties, thereby guaranteeing that digital marketing fosters both business progress and public welfare.

1. Introduction

The rapid advancement of information and communication technologies (ICTs) has significantly transformed the social, cultural, and economic landscapes of the twenty-first century. For billions globally, the internet, social media, mobile applications, and other digital communication tools have transitioned from mere conveniences to indispensable components of daily existence [1]. Digital technologies have enabled individuals to engage, share, shop, work, and express themselves on global virtual platforms. As of January 2020, around 4.54 billion individuals, including nearly 59% of the global population, were using the internet. Social media platforms have emerged as the predominant venues for engagement, boasting 2.95 billion active users in 2019 and an anticipated 3.43 billion by 2023 [2]. These facts illustrate the rapid transformation of digital connectivity on human behavior, communication, and commerce. Digital technologies are increasingly prevalent, significantly impacting marketing. Digital marketing strategies are becoming prevalent and, in certain instances, are supplanting traditional marketing methods constrained by distance, time, and expense [3]. Digital marketing encompasses the utilization of digital technologies, mostly the internet, to promote products and services, engage customers, and enhance brand visibility. This sort of marketing employs electronic devices and digital platforms, such as search engines, websites, email, and social media networks, to facilitate more targeted communication between businesses and consumers. Digital marketing differs from traditional marketing by enabling organizations to reach a broader and more specific audience, monitor performance metrics in real time, and adjust strategies promptly to optimize outcomes [4]. The emergence of digital marketing can be attributed to the early 1990s, when personal computers and internet accessibility became prevalent. This marks the inception of “online marketing” or “web marketing” [5]. Since then, digital marketing has evolved into a more intricate and expansive field due to advancements such as Web 2.0, mobile internet, cloud computing, and artificial intelligence. Currently, businesses employ various marketing instruments, including search engine optimization (SEO), search engine marketing (SEM), content marketing, social media marketing (SMM), email marketing, influencer marketing, affiliate marketing, pay-per-click (PPC) advertising, and marketing automation tools [6]. These approaches assist organizations in effectively promoting their products and services while also fostering engaging and personalized relationships with their clientele. Digital marketing is crucial as it facilitates bidirectional connection, enabling customers to provide feedback, share experiences, and influence perceptions of a brand in real time. This contrasts with conventional advertising, which operates unidirectionally. Digital marketing is rapidly expanding as an increasing number of individuals globally are utilizing the internet. In 2005, about 1.1 billion individuals (16.6% of the global population) had access to the internet. By 2020, the figure had increased to 4.8 billion, representing over 62% of the global population [7]. Countries such as India and China, characterized by substantial populations and rapidly expanding digital economies, have become significant markets for internet firms. Conversely, developed economies in North America and Europe remain leaders in digital innovation and technological infrastructure. This global trend illustrates the opportunities and challenges marketers have as they adapt to more diverse, interconnected, and competitive marketplaces. A multitude of distinct advantages elucidate the increasing inclination of individuals towards digital marketing. These encompass its affordability, capacity to target specific client segments, potential to level the competitive landscape between small and large enterprises, and capability to assess marketing effectiveness in real time [6]. Digital platforms enable businesses to engage with customers throughout the whole decision-making process, from product awareness to purchase and post-purchase interactions. Digital marketing has evolved into a data-centric domain due to the implementation of advanced technologies such as big data analytics, machine learning, artificial intelligence (AI), and natural language processing (NLP). These technologies enable the personalization of marketing, enhance customer targeting precision, and provide insights into client preferences. These technological advancements not only enhance client experiences but also transform organizational approaches to marketing strategies. Digital marketing is rapidly expanding and has numerous distinct advantages, yet it also presents certain challenges that require further investigation [8]. Concerns over data privacy, cybersecurity, digital fatigue, information saturation, and the ethical ramifications of personalized advertising remain significant apprehensions for corporations, regulators, and consumers. Moreover, while research has extensively analyzed the effectiveness of digital marketing strategies in developed nations, there has been inadequate attention paid to emerging economies, where infrastructural shortcomings and variations in digital literacy present unique challenges and prospects [9].

This study seeks to provide a comprehensive overview of digital marketing, focusing on its evolution, key strategies, global use, and emerging trends. The study aims to demonstrate how digital marketing has emerged as a crucial element in business competition and customer involvement within the digital economy. It aims to address the challenges and ethical dilemmas associated with digital marketing, thereby enhancing understanding of its implications for the future of global commerce.

With digital marketing, marketers can see precise outcomes instantly. Finding out how many people actually read an ad in a newspaper is not always easy, as we have no idea how many sales were generated by that particular ad. Digital marketing can help one to choose a product or service’s reach, interact with prospective customers, promote globally, and promote in a tailored manner. However, digital marketing is not without its flaws [10]. Marketers struggle to make their commercials stand out and encourage customers to start talking about a company’s brand image or products, despite the fact that the internet is essential in digital marketing (as some areas may not have access to the internet, or users may have slow connections due to excessive clutter). There are a lot of competing products and services that employ the same digital marketing strategies, which can be a problem [11]. Due to the abundance of potentially fraudulent advertisements on websites and social media, customers may develop a negative impression of certain businesses. Public perception of a famous brand might be damaged by the actions of an individual or even a small group. The majority of digital marketing’s target audience lacks the power to buy or even make a purchase decision. This has led many to doubt the efficacy of digital marketing in driving revenue [12].

Existing reviews of digital marketing research have predominantly adopted narrative or scoping approaches that provide conceptual insights but offer limited empirical synthesis. Earlier studies that applied topic modeling techniques in the marketing discipline have generally examined extended historical periods before 2020, which means that the recent restructuring of the field, driven by technological and methodological advancements, has not been adequately captured. In contrast, the present study focuses on the contemporary evolution of digital marketing research from 2020 to 2025 and integrates Latent Dirichlet Allocation with bibliometric network analyses such as keyword co-occurrence, author collaboration, and international linkages, complemented by a temporal overlay to trace the emergence and transformation of research themes. Methodologically, this study follows a triangulated validation process that includes topic coherence evaluation, manual inspection of representative documents, and alignment with bibliometric clusters to ensure transparency and reproducibility. Substantively, the study produces a ten-theme conceptual map of the domain that illustrates yearwise thematic progression and collaboration structures reflecting the post-2020 reconfiguration of digital marketing scholarship. This combined temporal, bibliometric, and textual approach differentiates the present work from previous reviews and topic-modeling studies and represents its principal contribution to the literature.

2. Literature Review

An expanding corpus of studies highlights the revolutionary impact of how digital marketing influences consumer behavior, informs corporate strategy, and reshapes the broader business environment. Researchers have emphasized that the rapid increase in internet access has established e-commerce as a vital catalyst for growth for both large enterprises and SMEs, with online commerce in India anticipated to grow substantially in revenue and geographic reach [10]. Simultaneously, limited researchers have examined the dual aspects of social media marketing, recognizing it as an innovative instrument for audience engagement while also acknowledging its intrinsic limitations, thus emphasizing the necessity for organizations to perpetually enhance strategies to tackle challenges such as information overload and swiftly evolving consumer preferences [13]. Researchers have shown that small and medium-sized enterprises (SMEs) can only maintain a competitive edge through program-based marketing strategies; they have also argued that the 80/20 rule is useful for developing CRM plans to increase productivity and revenue [14]. Two additional studies reached the same conclusion that digital marketing is becoming more and more important as a whole strategy rather than just a promotional tool because of its ability to increase sales, strengthen brand loyalty, decrease operational costs, and boost inbound traffic [15]. Complementing this, one more study pointed out that generational differences in consumer behavior necessitate a hybrid approach, with younger consumers preferring digital channels and mature customer segments continuing to rely on traditional media, thereby making integrated strategies that combine both approaches optimal for maximizing market coverage [16]. While digital marketing has policy implications, this study confines its focus to academic research themes and disciplinary development [17]. The concepts have been clarified by numerous researchers who have proposed comprehensive frameworks that incorporate digital technologies into marketing processes. They underscore the significance of stakeholders’ collaboration and the integration of marketing communication as fundamental components of strategy development [18,19]. The Delphi technique has been employed to reinforce the predictive reliability of these findings and underscore the necessity of data-driven procedures in business planning. Contemporary studies have extended this by predicting that the trajectory of digital marketing will be significantly influenced by artificial intelligence, voice-based search, and mobile-driven ecosystems [20,21]. Research undertaken further elucidates the influence of digital media on consumer psychology in India. Social networking platforms serve as efficient marketplaces and as avenues for immediate feedback, enabling companies to enhance their plans with more agility [22]. Supporting these viewpoints, another researcher emphasized that digital marketing is one of the most economical promotional tools, improving engagement, optimizing campaigns, and reducing transaction barriers, while fostering a future characterized by data-driven, AI-enabled, and consumer-centric methodologies [23]. Digital marketing serves as a cost-efficient promotional medium that allows targeted and data-driven engagement with consumers. There are several tools available for conducting bibliometric analysis, such as VOSviewer, Gephi, Biblioshiny (R Studio), CiteSpace, and SciMAT. These tools help visualize and analyze relationships between authors, keywords, institutions, and countries within a body of academic literature [24]. Future research is advocated to enhance this understanding through longitudinal studies, field trials, and cross-sectoral analyses that examine the dynamic relationship between technological advancements and consumer behavior.

3. Methodology

In this study, the authors adopted a structured methodology comprising multiple phases. The process began with the collection of relevant data, followed by preprocessing to ensure accuracy and consistency. Once the data was cleaned and prepared, it was fed into the Latent Dirichlet Allocation (LDA) model for topic modeling. Additionally, bibliometric analysis was conducted using VOSviewer to visualize and interpret research patterns. The overall research methodology applied in this study is systematically represented in Figure 1.

3.1. Data Collection

The dataset for this study was collected from the SCOPUS database, which provides comprehensive coverage of peer-reviewed journals and conference proceedings [25]. The search string “Digital Marketing” was applied to titles, abstracts, and keywords to ensure relevance to the field and received 6279 articles and string passed on 18 August 2025. The search retrieved a wide spectrum of publications, capturing both foundational and contemporary contributions. As per the PRISMA guidelines, the authors applied inclusion/exclusion criteria in which, in the first step, only English-written articles were considered, and the article count was filtered to 6003 [26]. The final dataset excluded all articles with missing information, like authors, year, abstract, etc., and comprised 4722 records from 2020 to August 2025. Each record contained metadata such as the title, abstract, keywords, and year of publication. The process of article selection is represented in Figure 2.

3.2. Data Pre-Processing

Abstracts were selected as the primary unit of analysis, given their ability to summarize the research problem, methodology, and findings. The textual data underwent standard natural language processing (NLP), including:

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Lowercasing all text for consistency.

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Tokenization to split text into words and tokens.

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Stop-word removal to eliminate common non-informative terms.

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Lemmatization to reduce words to their root forms.

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Noise filtering to remove punctuation, numbers, and special characters.

This produced a clean and structured corpus suitable for computational analysis [27].

3.3. Topic Modeling

Latent Dirichlet Allocation (LDA) was employed to uncover latent topics within the dataset. LDA, a probabilistic generative model, assumes that documents are mixtures of latent topics, and each topic is defined by a distribution of words. The model was implemented in Python using the gensim library. Multiple values of the number of topics (k) were tested, and the final choice of ten topics was guided by topic coherence metrics and interpretability of results. Each topic was characterized by a set of high-probability terms, which were later used for thematic labeling [28]. During the implementation of Latent Dirichlet Allocation, the authors executed 1000 iterations to ensure model stability and topic coherence. The preprocessing steps involved using the standard NLTK library to remove stopwords and Spacy for lemmatization, which refined the textual data for better topic extraction. The experiment was conducted on Google Colab, leveraging its computational resources for efficient processing. The LdaMallet model was employed with an alpha parameter of 0.2 and iterations = 1000. To ensure reproducibility, a fixed random seed of 42 was used for all stochastic modeling processes. The analyses were performed in Python 3.10 using gensim 4.3.1, NLTK 3.9, and spaCy 3.7 libraries within the Google Colab (2024.08 release) environment. To determine the optimal number of topics (K), the coherence score was used as the primary evaluation metric, ensuring the selection of the most meaningful topic distribution. Although NLP-based methods such as LDA were used in this study to uncover latent themes in digital marketing literature, these techniques were employed strictly as exploratory tools for mapping patterns rather than as inferential or predictive mechanisms. Topic modeling provides a quantitative approximation of semantic structures in a large text corpus, and the quality of the results depends on preprocessing, parameter tuning, and interpretive validation. To mitigate these limitations, multiple steps were taken to ensure reliability, like manual inspection of top terms and representative documents for each topic, coherence score optimization to select the most interpretable topic number, and triangulation of topic-modeling results with traditional bibliometric indicators. Therefore, the NLP component supports rather than substitutes qualitative reasoning and bibliometric evidence in mapping the intellectual structure of digital marketing research. The methodological design follows the PRISMA and reproducibility standards for bibliometric and topic-modeling research, ensuring both transparency and replicability of results.

3.4. Visualization and Interpretation

The results of the topic modeling were visualized using the pyLDAvis library. Two key outputs were generated:

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Intertopic Distance Map, showing how topics overlap or diverge within the semantic space.

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Term Saliency Distribution, which identified the most informative and distinctive terms across the dataset.

This visualization aided in understanding relationships between topics and supported the assignment of meaningful thematic labels.

3.5. Quantitative and Qualitative Validation

The robustness of the identified topics was examined through a two-stage validation process:

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Quantitative Validation: Topic prevalence was assessed by calculating the number and percentage of documents assigned to each dominant topic. This allowed identification of both dominant and niche research themes.

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Qualitative Validation: Representative documents with the highest contribution percentages were reviewed to verify the semantic coherence of topics. Abstracts and associated keywords were cross-checked against model-derived terms to ensure interpretive accuracy.

4. Temporal Evolution of Digital Marketing Research Through Bibliometric Analysis

To illustrate the recent evolution of digital marketing research, the researchers analyzed annual publication counts and keyword trends from 2020 to 2025. The number of publications grew steadily from 416 in 2020 to 1339 in 2024, reflecting heightened academic attention coinciding with the accelerated digitalization during and after the COVID-19 pandemic. Keyword overlay analysis indicates a thematic shift during this period. Early-period studies (2020–2021) emphasize “social media marketing,” “e-commerce,” and “consumer behavior,” while later publications (2023–2025) increasingly reference “artificial intelligence,” “machine learning,” “data privacy,” “influencer marketing,” and “sustainability.” These transitions demonstrate that digital marketing research is evolving from platform- and adoption-focused investigations toward data-driven, ethical, and technology-enabled marketing paradigms.

This five-year window captures a transformative stage in the field, characterized by rapid conceptual diversification and methodological innovation driven by the rise of generative AI, analytics, and immersive media technologies.

4.1. Year-Wise Publication Analysis

The bibliometric analysis of publication trends from 2020 to 2026 reveals a consistent rise in research output during the initial years, followed by a noticeable decline, which is represented in Figure 3. Starting with 416 publications in 2020, the count increased steadily to 568 in 2021 and 651 in 2022, reflecting gradual growth in scholarly contributions. A significant surge was observed in 2023 with 965 publications, which further peaked in 2024 at 1339 publications, marking the most productive year in the dataset.

However, 2025 witnessed a sharp decline to 782 publications, indicating either reduced research activity or possible delays in indexing processes. The data for 2026 currently shows only a single publication, which is likely incomplete given the ongoing year. Overall, the trend highlights a strong upward trajectory in research productivity between 2020 and 2024, followed by a downturn in 2025, suggesting the need for cautious interpretation of the most recent counts.

4.2. Top 10 Publication Avenues

The analysis of the top publication avenues highlights the most influential sources contributing to the research domain under study, shown in Figure 4. Lecture Notes in Networks and Systems emerges as the leading outlet with 133 publications, followed by the Springer Proceedings in Business and Economics with 109 publications, both of which serve as prominent platforms for disseminating interdisciplinary research. Sustainability (Switzerland) (86) and Smart Innovation, Systems and Technologies (75) also feature prominently, reflecting the growing emphasis on sustainable development and innovation-driven studies. Other significant outlets include Cogent Business and Management (70), ACM International Conference Proceedings Series (57), and AIP Conference Proceedings (52), which provide strong international exposure through both journals and conferences. Additionally, Studies in Systems, Decision and Control (51), International Journal of Data and Network Science (44), and the Journal of Digital and Social Media Marketing (43) demonstrate the multidisciplinary nature of contributions, spanning areas of systems research, data science, and marketing.

Together, these outlets capture the breadth and diversity of research dissemination across conferences, indexed proceedings, and peer-reviewed journals, underscoring the field’s wide-ranging impact.

4.3. Author’s Wise Analysis

The co-authorship network given in Figure 5 demonstrates a clustered structure with clear research communities. Central actors include Alshurideh, Muhammad Turki, Alghizzawi, Mahmoud, and Nuseir, Mohammed T., who exhibit high connectivity and function as intellectual bridges across clusters. The red cluster is dominated by Alshurideh and Mohammad, Anber Abraheem Shlash, while the green cluster centers on Alghizzawi in collaboration with Ezmigna and Alhanatleh. In contrast, the purple cluster highlights Nuseir and Refae, whereas smaller clusters reflect relatively isolated collaborations.

Figure 5 illustrates the co-authorship network among researchers publishing on digital marketing. The network reveals several moderately connected clusters, indicating collaborative communities rather than a single dominant research core. The largest clusters correspond to studies in areas such as social media marketing, tourism and hospitality, SME adoption, and data analytics. Prominent authors (high-degree nodes) act as connectors across clusters, bridging disciplinary boundaries. This structure highlights the interdisciplinary nature of digital marketing research, integrating marketing, information systems, and management perspectives. Overall, the network demonstrates steady collaboration growth but also shows scope for deeper integration among research groups. Author-level metrics corroborate these patterns. Sakas, Damianos P. (34 documents, 358 citations, TLS = 70) and Giannakopoulos, Nikolaos T. (21 documents, 163 citations, TLS = 52) emerge as highly productive and structurally central. Citation impact is particularly notable for Dwivedi, Yogesh K. (1569 citations), Krishen, Anjala S. (1508 citations), and Karjaluoto, Heikki (1292 citations), underscoring their intellectual influence despite comparatively lower publication counts. The results indicate a collaborative yet uneven landscape, where a small number of authors significantly shape the knowledge domain through both publication output and citation impact.

4.4. Country-Wise Analysis

The country-level co-authorship network highlights a globally interconnected research landscape with distinct regional clusters. India emerges as the most productive nation (872 publications, 7097 citations, TLS = 296), while the United States demonstrates the highest impact with 9052 citations, and the United Kingdom leads in collaboration strength (TLS = 306). Strong regional hubs are evident, with Asia (India, Indonesia, China, Jordan, Saudi Arabia) and Europe (Portugal, Spain, Germany, Greece, Ukraine) forming dense clusters, while the Middle East, particularly the UAE and Saudi Arabia, plays a bridging role. North America and Australia maintain global integration through extensive collaborations with both Europe and Asia. Peripheral contributors such as Ethiopia, Armenia, and Israel reflect emerging participation. Overall, the analysis indicates a multi-polar structure where a few central nations drive productivity, impact, and collaboration, thereby shaping the international knowledge network.

Figure 6 shows that India leads in volume, the United States leads in impact, and the United Kingdom leads in collaboration strength, with regional clusters indicating strong Asia–Europe–Middle East linkages. Figure 6 depicts international collaboration patterns based on co-authorship by country. The network demonstrates a multi-polar structure, with the United States, India, the United Kingdom, and China emerging as major hubs of collaboration. Strong regional linkages can be observed between Asian and European institutions, reflecting the global relevance of digital marketing as both a research domain and a business practice. The growing participation of developing countries signals increasing global interest and knowledge diffusion in this field. Overall, international collaboration is expanding, suggesting that digital marketing research benefits from diverse cultural and economic contexts.

4.5. Keyword Analysis

The keyword co-occurrence analysis (Figure 7) illustrates the intellectual structure of the field, with “digital marketing” (2049 occurrences, TLS = 4807) emerging as the dominant theme. Closely associated concepts include advertising (75 occurrences), customer engagement (71), social media marketing (160), consumer behavior (103), and digital transformation (138), reflecting both theoretical and applied orientations of research. Emerging technological enablers such as artificial intelligence (242), machine learning (144), deep learning (51), and augmented reality (34) indicate the increasing integration of advanced analytics and immersive technologies into marketing scholarship. Social and behavioral perspectives are emphasized through clusters around sustainability (53), brand loyalty (29), purchase intention (80), and influencer marketing (89), signifying evolving consumer-centric paradigms. The clustering further highlights the interdisciplinary nature of the field, bridging technology-driven innovation with behavioral science, sustainability, and managerial strategies. The network underscores digital marketing as the central research hub, around which specialized and emerging themes coalesce.

Figure 7 shows the keyword co-occurrence network, which identifies the core research themes and their interrelationships. The most frequently co-occurring keywords include digital marketing, social media, consumer behavior, machine learning, and e-commerce, confirming their centrality in current scholarship. Cluster analysis reveals distinct thematic groups such as Analytics and Artificial Intelligence in marketing, Consumer behavior and engagement, Sustainability and SMEs, and Tourism and digital experiences. These clusters align closely with the ten topics identified through LDA modeling, reinforcing the robustness of the thematic structure. The overlay visualization also indicates a recent shift (post-2020) toward emerging topics such as AI-driven personalization, privacy, and influencer marketing.

5. Results and Discussions

5.1. Topic Distribution

The Latent Dirichlet Allocation (LDA) analysis identified ten dominant topics within the dataset. The distribution of documents across these topics was not uniform, indicating the existence of both highly prevalent and more specialized thematic clusters. Topic 1 emerged as the most dominant, encompassing 542 documents (11.48%), followed by Topic 4 with 483 documents (10.23%), and Topic 10 with 422 documents (8.93%). Conversely, smaller clusters such as Topic 0 (4.81%) and Topic 1 (3.94%) represented more niche areas of discourse. This distribution suggests a heterogeneous corpus where certain themes, particularly those related to education, technology, and consumer behavior, are more prominently represented. A topic-wise document count is represented in

Table 1. Topic-wise document count.

Dominant Topic	Document Count	Total Document Percentage
Digital Marketing and Blockchain	227	4.81
Digital Marketing in the Health and Food Industry	186	3.94
Digital Marketing in Higher Education and Skill Enhancement	196	4.15
Machine Learning and Analytics in Digital Marketing	542	11.48
Adoption of Digital Marketing for SMEs and Sustainable Business	483	10.23
Digital Marketing Trends and Ethics	740	15.67
Sales and Digital Transformation	1102	23.34
Digital Marketing in Tourism and Hospitality	399	8.45
Digital Media and Audience Perception	355	7.52
Digital Marketing and Consumer Satisfaction using Service Quality	492	10.42

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5.2. Topic Characterization

Table 2. Topic labeling based on keywords.

Topic	Top Article Contribution %	Topic Terms	Topic	Top Article
1	95.83	search, engine, blockchain, seo, web, mobile, optimization, analytic, internet, security, iot, privacy, traffic, big, smart, page, cost, device, data, firm	Digital Marketing and Blockchain	[29]
2	99.88	food, health, post, child, exposure, beverage, healthcare, participant, advertisement, adolescent, policy, people, young, patient, unhealthy, medical, alcohol, target, country, relate	Digital Marketing in Health and Food Industry	[30]
3	88.52	student, education, case, skill, university, learn, institution, educational, sport, project, level, program, work, job, learning, startup, competency, knowledge, academic, educator	Digital Marketing in Higher Education and Skill Enhancement	[31]
4	99.84	machine, learn, learning, propose, technique, time, campaign, sentiment, algorithm, feature, deep, language, prediction, rate, accuracy, dataset, text, generate, target, analytic	Machine Learning and Analytics in Digital Marketing	[32]
5	99.73	sme, small, capability, sustainable, adoption, sustainability, msme, firm, financial, economic, resource, chain, green, entrepreneur, community, economy, supply, transformation, environmental, sector	Adoption of Digital Marketing for SMEs and Sustainable business	[33]
6	99.73	drive, chapter, marketer, practice, global, landscape, highlight, analytic, future, emerge, potential, book, ethical, dynamic, evolve, framework, opportunity, key, comprehensive, leverage	Digital Marketing Trends and Ethics	[34]
7	99.8	sale, activity, channel, pandemic, internet, covid, license, springer, promotion, article, transformation, main, environment, create, exclusive, time, sector, traditional, world, work	Sales and Digital Transformation	[35]
8	99.33	tourist, destination, literature, hotel, travel, article, luxury, future, fashion, trend, cultural, virtual, reality, bibliometric, area, field, systematic, hospitality, methodology, purpose	Digital Marketing in Tourism and Hospitality	[36]
9	99.71	video, virtual, theory, visual, live, emotional, interaction, generate, audience, message, perceive, attitude, perception, response, investigate, type, follower, positive, image, framework	Digital Media and Audience Perception	[37]
10	99.72	perceive, satisfaction, quality, questionnaire, survey, variable, structural, equation, loyalty, sample, positive, respondent, affect, behaviour, collect, trust, attitude, awareness, test, significantly	Digital Marketing and Consumer Satisfaction using Service Quality	[38]

highlights representative documents that strongly align with distinct digital marketing–related topics derived from the LDA analysis. Doc 487 emphasizes the integration of blockchain, SEO, IoT, and analytics, reflecting the technological backbone of digital marketing. Doc 1089 illustrates applications in the health and food industry, where marketing intersects with consumer exposure and policy. Similarly, Doc 2877 demonstrates the growing role of digital marketing in higher education and skill development. Doc 1000 showcases the incorporation of machine learning and sentiment analytics into campaign strategies, while Doc 3056 illustrates how SMEs adopt digital marketing for sustainable growth and environmental transformation. Emerging practices and ethical frameworks are addressed in Doc 3984, whereas Doc 1189 captures the pandemic-driven digital transformation of sales channels. In the service sector, Doc 3916 exemplifies digital marketing’s impact on tourism and hospitality, including luxury and virtual experiences. Finally, Docs 4703 and 177 highlight audience perception in digital media and consumer satisfaction using service quality models, respectively. Collectively, these documents reveal the multifaceted role of digital marketing across technological, industrial, educational, and behavioral dimensions. Other topics captured distinct domains such as tourism, small and medium enterprises (SMEs), and analytics. Collectively, the term distributions across topics confirm the multidimensional nature of the corpus, spanning academic, business, and socio-technical concerns. The “Contribution %” reported in Table 2 represents the relative proportion of documents assigned to each topic or cluster within the total corpus. It was calculated as

$$Contribution\left(\%\right)=\left({\displaystyle \frac{N_{\mathrm{documents} \mathrm{in} \mathrm{topic} i}}{N_{\mathrm{total} \mathrm{documents}}}}\right)\times 100$$

where $N_{\mathrm{documents} \mathrm{in} \mathrm{topic} i}$ is the number of documents assigned to topic i, i.e., those with the highest topic-probability score for that topic in the LDA model. N_{total documents} is total number of documents analyzed. In this study, this value is 4722.

“Top Article” designations identify representative documents that exhibit the highest posterior probability (topic loading) for a given topic in the LDA model. These articles were selected to illustrate the conceptual focus of each theme rather than to imply citation-based ranking or quality assessment. When multiple papers had similar topic probabilities, the most recent publication was chosen to ensure temporal relevance.

5.2.1. Digital Marketing and Blockchain

Digital marketing and blockchain together represent a rapidly evolving research domain, where current studies emphasize transparency, security, and efficiency, while future directions highlight personalization, tokenization, and Web3 ecosystems. At present, blockchain is being leveraged to enhance consumer trust by providing immutable records of transactions, securing programmatic advertising against fraud, and enabling decentralized ownership of consumer data in line with global privacy regulations [29]. Smart contracts are automating influencer marketing, affiliate agreements, and loyalty programs, while cryptocurrency integration is reshaping cross-border e-commerce and reward systems. Looking ahead, research is expected to focus on the integration of blockchain-secured data with artificial intelligence for hyper-personalized marketing without compromising privacy, the development of tokenized engagement and loyalty models, and interoperability across digital platforms to create unified and secure marketing ecosystems. Additionally, blockchain is likely to play a crucial role in verifying sustainability claims, enabling ethical marketing practices, and powering marketing strategies within the metaverse and Web3 environments through NFTs, decentralized communities, and immersive digital experiences [39]. Together, these trends highlight blockchain as both a technological safeguard and a transformative enabler for the future of digital marketing.

5.2.2. Digital Marketing in Health and Food Industry

Digital marketing in the health and food industry has emerged as a critical research domain due to its direct influence on consumer behavior, public health outcomes, and regulatory frameworks. Current studies highlight how social media platforms, targeted advertisements, and influencer campaigns are shaping dietary preferences, particularly among children and adolescents, often raising concerns about exposure to unhealthy foods, alcohol, and sugary beverages [40]. At the same time, digital campaigns are increasingly employed by healthcare organizations and food companies to promote healthy lifestyles, nutritional awareness, and preventive care, demonstrating the dual impact of digital strategies on both positive and negative health behaviors. Research also underscores the role of digital platforms in enabling personalized dietary recommendations, health-tracking apps, and patient engagement initiatives that integrate marketing with healthcare delivery. Looking forward, future research is expected to investigate the ethical dimensions of marketing unhealthy products online, the development of policy frameworks to regulate digital food advertising, and the use of artificial intelligence to create tailored health communication strategies [41]. Moreover, the intersection of blockchain and digital marketing may enhance transparency in food supply chains, allowing consumers to verify the authenticity and sustainability of food products. Thus, digital marketing in the health and food sector is evolving as a powerful yet complex force, balancing commercial objectives with pressing public health responsibilities.

5.2.3. Digital Marketing in Higher Education and Skill Enhancement

Digital marketing in higher education and skill enhancement has become a pivotal area of research, reflecting the growing reliance of academic institutions on digital platforms to attract, engage, and retain learners. Current studies emphasize the role of search engine optimization (SEO), social media campaigns, and targeted advertising in shaping institutional visibility and student recruitment, particularly in a highly competitive global education market [42]. At the same time, digital marketing is being integrated into curricula as a vital skill, with universities offering specialized programs and industry-driven training modules to bridge the gap between academic learning and employability requirements. Research also highlights how digital campaigns promote MOOCs, online certifications, and lifelong learning pathways, thereby democratizing access to education and skill development. Looking forward, future research is expected to examine the ethical use of data-driven marketing for student profiling, the application of artificial intelligence and predictive analytics to personalize learning pathways, and the role of immersive technologies such as virtual reality and the metaverse in enhancing academic branding and student engagement [43]. Thus, digital marketing in higher education not only serves as a strategic tool for institutional growth but also as a transformative driver for equipping learners with critical competencies aligned to evolving labor market demands.

5.2.4. Machine Learning and Analytics in Digital Marketing

Machine learning and analytics are revolutionizing digital marketing by enabling data-driven decision-making, predictive modeling, and personalized customer engagement. Current research highlights the use of supervised and unsupervised learning techniques for customer segmentation, sentiment analysis, churn prediction, and campaign optimization, with deep learning models increasingly applied to extract insights from unstructured data such as text, images, and social media interactions [44]. Real-time analytics powered by machine learning allows marketers to dynamically adjust pricing, content, and targeting strategies, thereby improving conversion rates and return on investment. At the same time, sentiment and opinion mining are widely used to understand consumer attitudes toward brands, products, and advertising campaigns. Looking ahead, future research is expected to focus on the integration of machine learning with blockchain and privacy-preserving techniques to ensure ethical use of consumer data, the development of explainable AI models for greater transparency in marketing decisions, and the adoption of reinforcement learning to optimize long-term customer lifetime value [45]. Furthermore, the convergence of machine learning, big data platforms, and immersive technologies such as augmented and virtual reality is likely to transform consumer experiences, enabling hyper-personalized and context-aware digital marketing strategies. Collectively, these advances position machine learning and analytics as central enablers of innovation in the digital marketing ecosystem.

5.2.5. Adoption of Digital Marketing for SMEs and Sustainable Business

The adoption of digital marketing by small and medium enterprises (SMEs) is increasingly recognized as a critical driver of sustainable business growth and competitiveness. Current research highlights how SMEs leverage digital tools such as social media marketing, search engine optimization, and e-commerce platforms to overcome resource limitations and expand their market reach. Digital marketing enables SMEs to engage directly with customers, enhance brand visibility, and optimize operations through data-driven insights, all of which contribute to improved financial resilience [46]. At the same time, the integration of sustainability principles into digital marketing strategies, such as promoting eco-friendly products, communicating green supply chain practices, and building community-oriented campaigns illustrates how SMEs align business growth with environmental and social responsibility. Future research is expected to explore how SMEs can adopt advanced digital technologies, including artificial intelligence, blockchain, and big data analytics, to create transparent, ethical, and resource-efficient marketing ecosystems. Moreover, the rise of sustainability-driven consumer behavior positions digital marketing not only as a tool for competitive advantage but also as a means of fostering long-term transformation toward greener economies [47]. Thus, the intersection of digital marketing, SMEs, and sustainability represents a promising area of study with implications for inclusive growth, responsible entrepreneurship, and global economic resilience.

5.2.6. Digital Marketing Trends and Ethics

Digital marketing trends and ethics have emerged as a critical area of inquiry, reflecting the dynamic evolution of marketing practices alongside rising concerns over consumer rights, privacy, and fairness. Current research emphasizes the rapid adoption of data-driven strategies such as predictive analytics, influencer marketing, and immersive technologies, which are reshaping how brands interact with audiences in real time [48]. At the same time, ethical considerations are increasingly foregrounded, as issues such as data misuse, algorithmic bias, targeted advertising to vulnerable groups, and manipulative persuasive design practices raise questions about accountability and trust. Regulatory frameworks like the GDPR and CCPA have further intensified scholarly and industry attention toward transparent, ethical digital practices. Looking forward, future research is expected to explore the integration of ethical AI in marketing decision-making, the development of global standards for responsible digital communication, and the role of blockchain and Web3 technologies in enabling transparency and consumer empowerment [49]. Moreover, sustainable and inclusive marketing strategies—where campaigns not only maximize profits but also promote social good—are likely to dominate forthcoming research agendas. Collectively, this theme positions ethics not as an adjunct to digital marketing trends but as a central determinant of credibility, long-term engagement, and societal impact.

5.2.7. Sales and Digital Transformation

Sales and digital transformation represent a pivotal intersection where traditional business models are being reshaped by technology-driven marketing and consumer engagement strategies. Current research highlights how digital platforms, e-commerce ecosystems, and omnichannel sales approaches have become indispensable, particularly in the wake of the COVID-19 pandemic, which accelerated the migration from physical to digital marketplaces [50]. Social media, mobile applications, and personalized recommendation systems are enabling firms to reach broader audiences while tailoring offerings to individual customer needs. At the same time, analytics-driven insights are transforming sales forecasting, customer relationship management, and pricing strategies, allowing businesses to adapt in real time to volatile market conditions. Future research is expected to focus on the integration of artificial intelligence, machine learning, and blockchain into sales processes to enhance transparency, efficiency, and consumer trust. Moreover, immersive technologies such as augmented and virtual reality are likely to redefine consumer experiences, offering interactive product demonstrations and virtual showrooms that bridge the gap between online and offline sales [51]. Thus, digital transformation in sales is not only a technological shift but also a strategic reorientation, redefining value creation, consumer engagement, and competitiveness in the global marketplace.

5.2.8. Digital Marketing in Tourism and Hospitality

Digital marketing in tourism and hospitality has become a transformative force, reshaping how destinations, hotels, and service providers connect with global audiences in an increasingly competitive industry. Current research emphasizes the use of search engine optimization, social media campaigns, influencer marketing, and virtual reality experiences to enhance destination visibility and engage travelers through immersive storytelling [52]. Bibliometric studies indicate a surge in scholarly attention toward online reviews, user-generated content, and electronic word-of-mouth (eWOM), which significantly influence consumer decision-making in tourism. At the same time, luxury travel and hospitality brands are employing personalized digital campaigns to target niche markets and build loyalty through data-driven insights. Future research is expected to explore the integration of blockchain for transparent booking systems, artificial intelligence for predictive customer experience management, and the metaverse for interactive tourism experiences. Moreover, sustainability and cultural authenticity are likely to become central to digital marketing strategies, as travelers increasingly value ethical practices and meaningful connections. Collectively, digital marketing in tourism and hospitality represents not just a promotional tool but a strategic driver of innovation, customer satisfaction, and long-term competitiveness in the global travel economy [53].

5.2.9. Digital Media and Audience Perception

Digital media and audience perception have become a central theme in contemporary marketing research, focusing on how consumers interpret, engage with, and respond to digital content across platforms. Current studies emphasize the role of social media, video marketing, and interactive content in shaping audience attitudes, emotional responses, and brand perceptions [54]. Influencer campaigns, live streaming, and immersive formats such as augmented and virtual reality are shown to generate stronger engagement by creating personalized and relatable experiences. At the same time, sentiment analysis and opinion mining are widely applied to capture consumer reactions, providing marketers with actionable insights for refining strategies. However, concerns about message overload, misinformation, and manipulative content highlight the ethical complexities of influencing perception in digital spaces. Looking forward, research is expected to explore the intersection of digital media with artificial intelligence and neuromarketing to understand subconscious drivers of consumer behavior, while the rise of Web3 and decentralized platforms may transform the dynamics of audience engagement and trust. Overall, digital media is not merely a communication channel but a powerful force that shapes how audiences perceive value, authenticity, and credibility in an increasingly saturated marketing environment.

5.2.10. Digital Marketing and Consumer Satisfaction Using Service Quality

Digital marketing and consumer satisfaction using service quality frameworks represent a significant research stream that bridges technological innovation with customer relationship management. Current studies highlight how digital platforms—ranging from social media and mobile apps to e-commerce portals serve as critical touchpoints for shaping perceptions of service quality, trust, and loyalty [55]. Tools such as online surveys, structural equation modeling, and customer feedback systems are frequently employed to measure constructs like responsiveness, reliability, and assurance in the digital context. Research also emphasizes how personalized communication, seamless user interfaces, and secure transactions enhance consumer satisfaction and long-term engagement. At the same time, digital marketing analytics provide firms with actionable insights into consumer expectations, enabling continuous improvement in service delivery. Looking forward, future research is expected to focus on the integration of artificial intelligence and machine learning for real-time service personalization, the role of blockchain in ensuring transparency and trust, and the adoption of omnichannel service strategies to provide consistent quality across platforms. Moreover, ethical considerations and sustainability-driven practices are likely to become central to consumer satisfaction studies, as customers increasingly seek authentic and responsible brand experiences [56]. Thus, digital marketing not only amplifies service offerings but also fundamentally redefines how consumer satisfaction is achieved and sustained in the digital era.

5.3. Representative Documents

The Latent Dirichlet Allocation (LDA) model, visualized using pyLDAvis, reveals the intertopic structure and salient terms within the corpus represented in Figure 8. The intertopic distance map demonstrates ten distinct yet partially overlapping topics, with varying degrees of separation. Larger circles denote higher prevalence, indicating dominant thematic clusters such as education, student engagement, small and medium enterprises (SMEs), tourism, health, and blockchain-related discussions. The proximity of topics suggests conceptual similarity, whereas isolated clusters indicate unique thematic domains. The saliency analysis highlights the most informative terms across the corpus, including food, student, SME, health, education, blockchain, and university, which collectively shape the semantic space of the dataset. These findings suggest a heterogeneous text collection characterized by intersections of educational discourse, technological innovation, and socio-economic themes.

To ensure interpretability, representative documents with the highest contribution to each topic were examined.

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Within Topic 1, an example abstract highlighted the growing demand for optimized digital marketing strategies, integrating blockchain technologies to enhance consumer trust and transparency. Another document emphasized content marketing trends with a focus on search engine optimization (SEO). Both illustrate how Topic 1 is anchored in the convergence of marketing and emerging technologies.

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For Topic 2, representative abstracts discussed the impact of digital media exposure on children’s dietary habits and broader implications for public health interventions. This validates the interpretation of Topic 2 as centered on nutrition and health behavior.

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Topic 3 was exemplified by documents addressing the skills gap between industry requirements and university curricula, as well as studies on experiential learning approaches. These findings underscore the educational and pedagogical orientation of this cluster.

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In Topic 10, abstracts consistently dealt with service quality measurement and customer satisfaction. For example, one study applied questionnaire-based models to evaluate consumer perceptions, highlighting the robustness of this topic in capturing quality assessment research.

5.4. Interpretation and Discussions

The combination of quantitative prevalence and qualitative exemplars demonstrates that the dataset encompasses a broad spectrum of themes, with education, consumer satisfaction, and technological transformation appearing as central axes. The overlap of certain topics, visible in the intertopic distance map, suggests conceptual intersections—for example, between digital marketing (Topic 1) and consumer satisfaction (Topic 10), or between educational discourse (Topic 3) and SME-related themes. The results highlight the richness and interdisciplinarity of the corpus, where academic, technological, and socio-economic discourses co-exist. This provides a strong foundation for subsequent analysis in the Discussion section, particularly in situating these findings within existing literature on digital transformation, higher education, and consumer behavior. The bibliometric network analyses complement the topic modeling results by illustrating how collaboration patterns and thematic clusters shape the evolution of digital marketing research. The time-bounded analysis (2020–2025) highlights the field’s recent evolution, where emerging technologies and post-pandemic digital acceleration have reshaped both academic inquiry and marketing practice. The alignment between co-occurrence clusters and LDA topics confirms the validity of identified themes, while the author and country networks provide insight into the global and interdisciplinary character of the field. Together, these analyses show that digital marketing research is maturing through diverse international contributions, methodological innovation, and the growing convergence of technology and marketing disciplines.

Table 3. Topic Distribution over Time.

Dominant Topic	Document Count	Papers in 2020–2021	Papers in 2022–2023	Papers in 2024–2025	2020–2021 (%)	2022–2023 (%)	2024–2025 (%)
Digital Marketing and Blockchain	227	61	86	80	1.29	1.82	1.69
Digital Marketing in Health and Food Industry	186	50	69	67	1.06	1.46	1.42
Digital Marketing in Higher Education and Skill Enhancement	196	54	74	68	1.14	1.57	1.44
Machine Learning and Analytics in Digital Marketing	542	146	206	190	3.09	4.36	4.02
Adoption of Digital Marketing for SMEs and Sustainable Business	483	129	183	171	2.73	3.88	3.62
Digital Marketing Trends and Ethics	740	199	282	259	4.21	5.97	5.48
Sales and Digital Transformation	1102	295	417	390	6.25	8.83	8.26
Digital Marketing in Tourism and Hospitality	399	107	149	143	2.27	3.16	3.03
Digital Media and Audience Perception	355	95	129	131	2.01	2.73	2.77
Digital Marketing and Consumer Satisfaction using Service Quality	492	133	184	175	2.82	3.90	3.71

presents the topic distribution over the years.

6. Implications of the Research

This study carries significant implications for academia, industry, and policymakers by mapping the evolving landscape of digital marketing through topic modeling.

6.1. Academic Implications

The identification of ten distinct research themes, including blockchain, health and food industry applications, higher education, SMEs, and consumer satisfaction, provides a structured framework for future scholarly inquiry. It highlights the interdisciplinary nature of digital marketing research and directs scholars toward emerging areas such as ethical AI, sustainability-driven marketing, and metaverse applications. The methodology adopted—combining quantitative topic modeling with qualitative validation—also contributes a replicable analytical framework for bibliometric and thematic studies.

6.2. Managerial and Industry Implications

For practitioners, the findings illustrate the breadth of digital marketing’s impact across sectors. Themes such as machine learning in analytics, consumer trust and satisfaction, and digital transformation of sales demonstrate how firms can leverage data-driven tools to improve engagement, personalization, and service quality. The strong emphasis on SMEs and sustainability underscores how small businesses can adopt digital marketing not only as a growth strategy but also as a vehicle for environmental and social responsibility. The results further guide organizations in aligning their marketing strategies with consumer expectations of transparency, ethics, and innovation.

6.3. Policy Implications

The prominence of topics such as health, food marketing, and ethics reveals the need for robust regulatory frameworks to balance commercial objectives with consumer welfare. Policymakers can use these insights to design guidelines around responsible advertising, consumer privacy, and sustainability claims. The integration of blockchain and AI in marketing also raises questions of accountability and governance, requiring forward-looking policies to ensure trust and fairness in digital ecosystems. This research underscores that digital marketing is no longer confined to promotion but is evolving as a strategic, ethical, and interdisciplinary driver of organizational competitiveness, consumer well-being, and sustainable development.

7. Conclusions and Future Scope

This research, while comprehensive, has certain limitations that must be acknowledged. The dataset was restricted to the SCOPUS database using the search string “Digital Marketing”, which may have excluded relevant studies indexed elsewhere or using alternative terminologies such as online marketing or social media advertising. The analysis was conducted primarily on abstracts rather than full texts, potentially overlooking deeper insights embedded in full-length articles. Methodologically, the use of Latent Dirichlet Allocation (LDA) provided robust topic extraction but is constrained by its bag-of-words assumption, limiting the capture of semantic and contextual nuances that advanced transformer-based models could reveal. Furthermore, topic labeling involved qualitative interpretation, introducing a degree of subjectivity despite validation through representative documents. Finally, as digital marketing is a fast-evolving domain shaped by emerging technologies, regulatory frameworks, and shifting consumer behavior, the findings reflect a static snapshot in time and may not fully encompass future developments.

This study provides a comprehensive thematic mapping of digital marketing research using Latent Dirichlet Allocation (LDA) on a dataset extracted from the SCOPUS database with the search string “Digital Marketing.” The analysis identified ten distinct topics, including blockchain, health and food industry applications, higher education, SMEs and sustainability, machine learning and analytics, tourism, consumer satisfaction, and ethical considerations, thereby highlighting the interdisciplinary and rapidly evolving nature of the field. The results demonstrate that digital marketing has expanded beyond its traditional role as a promotional tool to become a strategic driver of technological innovation, consumer engagement, and sustainable business practices. Through quantitative prevalence analysis and qualitative validation of representative documents, this research not only consolidates existing knowledge but also identifies key domains where digital marketing is making transformative impacts.

Looking ahead, the future scope of research in this area is substantial. Emerging technologies such as artificial intelligence, blockchain, augmented reality, virtual reality, and the metaverse will continue to redefine how organizations design and implement marketing strategies. Future studies can build on this work by integrating datasets from multiple sources beyond SCOPUS, applying advanced semantic models such as BERTopic or transformer-based approaches for deeper contextual insights, and analyzing full-text articles to capture richer details. Moreover, longitudinal studies could examine the evolution of digital marketing themes over time, while sector-specific research may investigate how digital strategies influence industries such as education, healthcare, tourism, and SMEs differently. Ethical considerations, sustainability-driven marketing, and consumer-centric innovations will remain central to ensuring that digital marketing not only achieves business objectives but also contributes to social and economic well-being. Thus, this research establishes a foundation for scholars, practitioners, and policymakers to understand current trends and pursue future explorations in the dynamic domain of digital marketing.