Annotated Bibliography
The following blog entry presents an annotated bibliography that will inform the development of our digital media blog exploring all things related to new and emerging social media, marketing, communications, culture, and advancing artificial intelligence (AI) technology.
Research: Technology, Media, and Culture Analysis
Gottfried, J., & Park, E. (2025, November 20). Americans’ social media use 2025. Pew Research Center. https://www.pewresearch.org/internet/2025/11/20/americans-social-media-use-2025/
The above Pew research report provides a detailed overview of social media usage patterns across major platforms, including TikTok, YouTube, Instagram, and Facebook. The scope includes demographic analysis, content discovery behaviors, political communication practices, and cultural participation trends. Pew’s nonpartisan methodology and reputation for accurate polling provide industry wide recognition of credibility to annual reports. The intended audience includes academics, marketers, policymakers, and media researchers seeking unbiased cultural reporting. Compared with Euromonitor’s commercially focused research, Pew offers a sociological lens to cultural analysis of online consumer behavior. This report enhances our blog’s framework by framing technology-driven communication trends within broader cultural shifts, specifically generational nuances in content preferences and trust. Pew Research Center additionally forms a foundational cultural lens that pairs cohesively with Statista’s numerical benchmarks.
El Jaourih, A., & Dixon, S. J. (2024). The social media landscape [Report]. Statista. https://www.statista.com/study/165265/the-social-media-landscape/
The Statista Social Media Landscape report provides a comprehensive analysis of global social media usage, platform evolution, demographic trends, and emerging market shifts. Covering platform classifications, user behavior, generational preferences, algorithm-driven engagement, safety concerns, and the evolving usage of artificial intelligence (AI), the report combines quantitative indicators with cultural insights to illustrate how social media networks inform global communications. Authored by Asmaa El Jaourih, a market-modeling analyst, and Stacy Jo Dixon, a researcher specializing in culture and online behavior, the report provides methodological credibility supported by Statista’s industry-standard analytics. For a marketing blog focused on technology, media, and culture, Statista is a critical resource in the contextualization of consumer behavior, generational platform migration, and industry trajectories of the rising influence of Gen Z and Gen Alpha. Compared with Pew Research Center’s (2024) survey-focused studies, Statista offers broader global forecasting and platform-specific metrics, making this database a foundational resource for interpreting contemporary digital media, technology, and communication trends.
Milasevic, M. (2025, March 27). Digital disruptors: The global landscape of social media [Briefing]. Euromonitor International. https://www.portal.euromonitor.com/?OOkVPVP8%2f%2bfLhu3ovZZ4LWK%2bwwJ7Fbv8cMH3yaLZo3%2f9lwnc92mVbQ%3d%3d
The following Euromonitor briefing analyzes how technological advances, artificial intelligence (AI) integration, and evolving consumer expectations are reshaping global social media use. The report covers several major developments, including the move toward niche digital communities, the growing influence of micro-creators, the expanding creator economy, and the increasing use of social commerce as a primary shopping channel. These trends highlight how social platforms have evolved into multifunctional channels where discovery, engagement, and purchasing occur simultaneously. The author, Marija Milasevic, is an industry analyst specializing in digital transformation and global consumer trends, bringing a strong background in market data analysis. Euromonitor International, one of the most respected global intelligence firms, adds credible authority to the findings. Compared with broader cultural sources such as Pew Research (Gottfried & Park, 2025), this briefing report focuses specifically on market behavior and emerging commercial opportunities. These insights strengthen the annotated bibliography by revealing how cultural shifts and new technologies, such as AI, influence brand strategy in the current digital media landscape.
Widener, C., Arbanas, J., Van Dyke, D., Arkenberg, C., Matheson, B., & Auxier, B. (2025). 2025 digital media trends: Social platforms are becoming a dominant force in media and entertainment. Deloitte Insights. https://www.deloitte.com/us/en/insights/industry/technology/digital-media-trends-consumption-habits-survey/2025.html
This Deloitte Insights report examines how evolving digital habits, such as the rise of social platforms as “entertainment hubs” are changing media consumption and cultural engagement. The authors explore a diverse set of behaviors, including how consumers discover content, interact with creators, and navigate between traditional media and algorithm-driven platforms. The scope of the analysis reflects broader cultural changes, such as the synergy of social networking and entertainment and the increasing influence of “personalized digital ecosystems” on daily life. The report is authored by a team of senior Deloitte leaders and researchers, each of whom specializes in technology, media, or telecommunications strategy. Their combined expertise and access to large-scale industry data lend the report significant authority, ensuring the research reflects both analytical rigor and real-world industry insight; making this resource valuable for examining technology’s cultural impact.
Research: Current Resources
Du, R., Li, M., Ai, S., MacSwiney Brugha, C., Reisach, U., & Wang, P. (2024). Artificial intelligence: an opportunity or a threat to good decision-making? Using systems thinking to examine values in an intercultural framework. Journal of Decision Systems, 1–21. https://doi.org/10.1080/12460125.2024.2428175
Du et al. (2024) propose the global adoption of artificial intelligence (AI) depends on building trust across cultures, highlighting the need for a shared value framework. By comparing perspectives from international experts and AI systems, the authors show that users place the greatest importance on understanding AI’s value in supporting human decision-making. As a current resource, this work offers meaningful insight for communication scholars and practitioners by examining the cultural, ethical, and value-driven considerations that shape how AI is understood and trusted, contrasting with Grewal et al. (2024), who focus on operational AI use in retail settings. The research conducted by Du et al. (2024) strengthens the blog’s exploration of technology, media, and culture by demonstrating how evolving cultural values and trust dynamics influence the way societies communicate about the adoption of emerging AI technologies.
Grewal, D., Benoit, S., Noble, S. M., Guha, A., Ahlbom, C.-P., & Nordfält, J. (2024). Leveraging in-store technology and AI: Increasing customer and employee efficiency and enhancing their experiences. Journal of Retailing, 100(1), 1–18. https://doi.org/10.1016/j.jretai.2023.10.002
Grewal et al. (2024) explore how retailers are integrating artificial intelligence (AI) into store technologies to streamline workflow and create impactful customer experiences. Rather than focusing solely on tools, the authors, recognized experts in retail media and service design, explain how AI technology influences employee roles, customer expectations, and the overall customer journey within the retail sector. The intended audience includes academic and industry professionals seeking evidence-based guidance on how digital tools can evolve retail at store level. In contrast to Statista’s (2025) broad, data-heavy reporting on digital consumer behavior, Grewal et al. (2024) focus on the physical retail setting and the day-to-day operations AI technology supports. AI-focused consumer behavior research is further expanded by illustrating how AI systems function in real world retail settings. This resource provides practical insight into how AI technology influences communication within the customer journey and supports cultural shifts toward more interactive, tech-enabled retail experiences.
Maphosa, V. (2024). The rise of artificial intelligence and emerging ethical and social concerns. AI, Computer Science and Robotics Technology Journal, Article 485. https://doi.org/10.5772/acrt.20240020
Maphosa (2024), reviews how the rapid expansion of artificial intelligence (AI) creates ethical and legal challenges across global and culturally diverse industries, including issues tied to privacy, autonomy, accountability, and biased decision-making. The author highlights as AI becomes embedded in core systems, gaps in regulation and oversight become more apparent, emphasizing the need for clear ethical and legal standards. The intended audience includes researchers, policymakers, and industry leaders who require a deeper understanding of AI’s societal implications. These ethical concerns differ from the operational focus of Grewal et al. (2024), who emphasize AI’s role in improving operational workflow and customer experience in retail settings. This review further complements Shi’s (2025) findings by showing that workforce upskilling must include strong ethical and governance competencies, as well as aligns with Du et al. (2024) by reinforcing the need for cultural and value-based frameworks to guide responsible AI adoption. The review also supports findings by Shanmugasundaram and Tamilarasu (2023), demonstrating that AI and digital technologies influence cognitive functioning and overall human well-being requiring ethical and legal oversight collectively across diverse industries.
Shanmugasundaram, M., & Tamilarasu, A. (2023). The impact of digital technology, social media, and artificial intelligence on cognitive functions: a review. Frontiers in Cognition, 1–11. https://doi.org/10.3389/fcogn.2023.1203077
This comprehensive review article by Shanmugasundaram & Tamilarasu (2023) highlights how digital technologies, such as social media and algorithmic content systems, can negatively affect mental health by increasing exposure to stress, comparison pressures, and toxic digital overload. The review further outlines evidence-based strategies to reduce these impacts, including digital literacy education, intentional screen-time management, and platform-level safety design that prioritizes user mental health and well-being. The review is intended for mental health professionals, communication researchers, educators, and policymakers seeking to understand how technology influences psychological and cognitive health and what interventions can help mitigate adverse effects. This work complements Shi’s (2025) focus on upskilling the workforce by showing that developing AI competence must also include preparing individuals to navigate the emotional and cognitive demands of technologically saturated environments. At the same time, it contrasts with Du et al. (2024) by shifting from global cultural value frameworks to more personal and health-oriented consequences of technology use, while together they show that both human well-being and cultural trust are essential components of responsible AI integration.
Shi, L. (2025). Global Perspectives on AI Competence Development: Analyzing National AI Strategies in Education and Workforce Policies. Human Resource Development Review, 24(4), 447–476. https://doi.org/10.1177/15344843251332360
Shi (2025) reviewed the national artificial intelligence (AI) strategies of 50 countries and found that only 13 advanced European economies outlined strategic, actionable plans for preparing an AI-ready workforce. Across these strategies, six central training priorities emerged, including AI literacy, technical skill development, reskilling programs, talent cultivation, interdisciplinary education, and workplace-aligned applied training. The intended audience includes educators, policymakers, human resource development (HRD) professionals, and researchers seeking practical guidance on how nations are structuring AI workforce development. Compared to the research of Du et al. (2024), which emphasizes cultural trust and shared values as the foundation for global AI adoption, this study focuses on the structural and educational requirements that enable culturally diverse societies to build AI competence and upskilling. Together, these studies complement one another by showing that both cultural trust and practical workforce upskilling must advance in tandem for AI technologies to be effectively integrated across diverse global industries.
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