Amelia, L., & Balqis, N. (2023). Changes in communication patterns in the digital age. ARRUS Journal of Social Sciences and Humanities.  https://doi.org/10.35877/soshum1992

    These authors examine how social media has fundamentally influenced human interaction, showing that new media has established new ways of social interaction and has increased global connectivity. The study also notes resulting challenges, including changing norms and privacy issues. This source looks at cultural shifts in digital media and technology by focusing on changes to everyday social interaction and communication norms. It provides the perspective that social media has disrupted core human communication patterns.

Amoore, L. (2022). Machine learning political orders. Review of International Studies. https://www.cambridge.org/core/journ als/review-of-international- studies/article/machine- learning-politicalorders/E10088513299784A34BB6EA4204E8B07    

Amoore argues that deep network algorithms used in the media have created a new machine learning political order by reconfiguring complex societal and political issues and treating them as purely abstract, quantifiable machine learning problems. He warns that this system will harm communities. The importance here is that algorithmic design as used in social media and elsewhere is not a neutral tool, but is a system that can manipulate societal instability for both profit and power.

Chan, M., & Yi, J. (2024). Social media use and political engagement in polarized times: Political Communication. https://www.tandfonline.com/doi/abs/10.1080/10584609.2024.2325423

Chan examines polarization in democracies caused by new technology applied to social media. In particular his finding that the adoption of Artificial Intelligence (AI) profoundly transforms society. This new technology forces democratic institutions to adopt specific values .This source expands analysis of technology to the organizational and corporate sphere. It demonstrates that technological tools (AI) are not just used by culture but actively act as an independent force that imposes cultural requirements onto human institutions via social media.   

Dinh, T., & Lee, Y.  (2025). Understanding the psychological drivers of online self-presentation: a survey study on social media exposure, social comparison, social network type and FOMO. BMC Psychol. https://pmc.ncbi.nlm.nih.gov/articles/PMC12255000/

This study examines how individuals use self-presentation strategies to construct and manage their online identities. It notes that the composition of the user’s social network is a key factor influencing effective online impression management and identity construction.  It also identifies and discussed key digital concepts like FOMO (fear of missing out) and CFA (confirmatory factor analysis). This source is important for analyzing how social media affects modern culture and identity. It offers a psychological framework to explain shifts in online behavior, self-concept, and the pressure to maintain a positive public image. 

McQuail, D., & Deuze, M. (2020). McQuail's Media & Mass Communication Theory (7th ed.). Sage. http://pure.uva.nl/ws/files/53580792/2020_Deuze_in_CT_media_and_mass_comm.pdf   

McQuaid and Deuze address communications theory for the digital era, specifically dealing with new issues such as big data, algorithmic culture, AI, platform governance, streaming services, and mass self-communication. It introduces the concept of mass self-communication, which describes networked, decentralized communication environments that deviate from traditional centralized media models. This source provides the theoretical vocabulary and historical context for defining the subject matter. It traces the evolution of mass media from a centralized system to a networked one.

Murire, O. T. (2024). Artificial Intelligence and Its Role in Shaping Organizational Work Practices and Culture. Administrative Sciences. https://doi.org/10.3390/admsci14120316

This article investigates the overall impact of the adoption of Artificial Intelligence (AI). It takes the position that AI will transform organizations resulting in cultural shifts. AI will be a driver of innovation across all aspects of business. In this way it is demonstrated that technology can force change on how our society and culture functions. While AI will result in greater and innovation, it also raises serious issues of bias, ethics, and privacy.

Wolfs, W., & Veldhuis, J. J. (2023). Regulating social media through self-regulation: A process-

tracing case study of the European Commission and Facebook. International Communication Gazette, 85(2), 170–190. https://www.tandfonline.com/doi/full/10.1080/2474736X.2023.2182696  

This study investigates the lack of regulation of online political advertising in the media and finds that the model of self-regulation has failed. Lack of monitoring and accountability is blamed . This prevents regulatory bodies from effectively online political advertisements.   This source provides information on the lack of governance and ethics of technology and social media. It demonstrates the policy failures that highlight urgent need to address social media platforms that can influence political outcomes.