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SYSTEMATIC REVIEW OF THE SOCIAL NETWORK FATIGUE LITERATURE USING A BIBLIOGRAPHIC APPROACH

Yıl 2026, Cilt: 16 Sayı: 2 , 729 - 749 , 01.04.2026
https://doi.org/10.7456/tojdac.1857161
https://izlik.org/JA25DJ76EL

Öz

This study examines the social network fatigue literature using bibliometric analysis from 1983–2025, framed by antecedent approaches such as information overload, media fatigue, and technostress. Data on 832 documents, 3,967 authors, and 590 sources from the Web of Science (WoS) database were analyzed using R Studio. Findings reveal an average annual growth rate of 12.03%, with a marked intensification in academic production post-2010, further accelerated by the COVID-19 pandemic. Results indicate that research has evolved from a descriptive focus on individual psychological symptoms to a multidimensional, interdisciplinary structure utilizing theoretical frameworks like FoMO and the Stress-Strain-Outcome (SSO) model. Thematic analyses position mental health, quality of life, depression, and anxiety at the literature's center. Unlike previous studies, this research addresses social network fatigue through a holistic analysis considering the transformation of theoretical orientations, not just keyword and citation networks. Thus, the study highlights the field's intellectual development, offering a systematic reference framework for future theoretical and applied research

Teşekkür

Doç. Dr. Servet Say'a teşekkür ederim.

Kaynakça

  • Ayyagari, R., Grover, V., & Purvis, R. (2011). Technostress: Technological antecedents and implications. MIS Quarterly, 35(4), 831–858.
  • Azizan, A. (2024). Exploring the role of social media in mental health research: A bibliometric and content analysis. Journal of Scientometric Research, 13(1), 1–8.
  • Bailenson, J. N. (2021). Nonverbal overload: A theoretical argument for the causes of Zoom fatigue. Technology, Mind, and Behavior, 2(1). 10.1037/tmb0000030
  • Bright, L. F., Kleiser, S. B., & Grau, S. L. (2015). Too much Facebook? An exploratory examination of social media fatigue. Computers in Human Behavior, 44, 148–155. 10.1016/j.chb.2014.11.048
  • Brod, C. (1984). Technostress: The human cost of the computer revolution. Addison-Wesley.
  • Burr, C., Taddeo, M., & Floridi, L. (2020). The ethics of digital well-being: A thematic review. Science and Engineering Ethics, 26(4), 2313–2343
  • Chen, B., Sun, X., Zhang, Q., & Yao, L. (2024). Are fatigued users fleeing social media? A three-level meta-analysis on the association between social media fatigue and social media use. Psychology of Popular Media, 13(3), 457–471. 10.1037/ppm0000495
  • Cho, J., Ramgolam, D. I., Schaefer, K. M., & Sandlin, J. K. (2011). The rate and delay in overload: An investigation of communication overload and channel synchronicity on identification and job satisfaction. Journal of Applied Communication Research, 39(1), 38–54.
  • Chung, T. L. D., Kim, K., & Lee, A. (2025). Social network analysis in fashion research: A systematic literature review. Clothing and Textiles Research Journal. 10.1177/0887302X251325144
  • Cramer, E. M., Song, H., & Drent, A. M. (2016). Social comparison on Facebook: Motivation, affective consequences, self-esteem, and Facebook fatigue. Computers in Human Behavior, 64, 739-746.
  • Dallmann, A., Teutonico, D., Schaller, S., Burghaus, R., & Frechen, S. (2024). In-depth analysis of the selection of PBPK modeling tools: Bibliometric and social network analysis of the Open Systems Pharmacology Community. The Journal of Clinical Pharmacology, 64(9), 1055–1067.
  • Dhir, A., Yossatorn, Y., Kaur, P., & Chen, S. (2018). Online social media fatigue and psychological wellbeing: A study of compulsive use, fear of missing out, fatigue, anxiety and depression. International Journal of Information Management, 40, 141–152. 10.1016/j.ijinfomgt.2018.01.012
  • Donkers, T., & Ziegler, J. (2025, June). Understanding online polarization through human-agent interaction in a synthetic LLM-based social network. Proceedings of the International AAAI Conference on Web and Social Media (Vol. 19, pp. 457–478).
  • dos Santos, B. Z., Reginaldo, L., da Silva, P. R., Vales, S. D. S., Morselli, N. V., & Júnior, J. R. A. (2024). Improving metadata quality in social network classification systems. Revista de Gestão Social e Ambiental, 18(12), 1–12.
  • Ellison, N. B., Steinfield, C., & Lampe, C. (2007). The benefits of Facebook “friends:” Social capital and college students’ use of online social network sites. Journal of Computer-Mediated Communication, 12(4), 1143–1168. 10.1111/j.1083-6101.2007.00367.x
  • Fox, J., & Moreland, J. J. (2015). The dark side of social networking sites: An exploration of the relational and psychological stressors associated with Facebook use and affordances. Computers in Human Behavior, 45, 168–176.
  • Gandasari, D., Tjahjana, D., Dwidienawati, D., & Sugiarto, M. (2024). Bibliometric and visualized analysis of social network analysis research on Scopus databases and VOSviewer. Cogent Business & Management, 11(1), 2376899.
  • Jana, D., & Heuser, C. (2025). Making sense of mental health in later life: Social network dynamics and service access. International Journal of Qualitative Studies on Health and Well-Being, 20(1), 2581516.
  • Kurşunmaden, F. İ. (2025). Bibliometric Analysis of Studies on the Concept of Vuca. Fiscaoeconomia, 9(2), 927-938. https://doi.org/10.25295/fsecon.1586089
  • Lee, A. R., Son, S. M., & Kim, K. K. (2016). Information and communication technology overload and social networking service fatigue: A stress perspective. Computers in Human Behavior, 55, 51–61. 10.1016/j.chb.2015.08.011
  • Li, Z. (2025). Maximum likelihood estimation for Erdős–Rényi graphs in social network analysis. Proceedings of the 3rd International Conference on Mathematical Physics and Computational Simulation (pp. 225–231). 10.54254/2753-8818/100/2025.22144
  • Liu, Y., Diehl, S., & Terlutter, R. (2023). The negative side of social media: A systematic review of social media fatigue. International Journal of Human–Computer Interaction, 39(1), 1-22. https://doi.org/10.1080/10447318.2022.2045564
  • Liu, Y., Mohamad, E. M. W., & Azlan, A. A. (2025). Social media fatigue and discontinuous usage: A meta-analytic structural equation modeling based on the stimulus-organism-response model. Review of Communication Research, 13(Special), 173-195. 10.52152/RCR.V13.S8
  • Luqman, A., Cao, X., Ali, A., Masood, A., & Yu, L. (2017). Empirical investigation of Facebook discontinuous usage intentions based on SOR paradigm. Computers in Human Behavior, 70, 544–555. 10.1016/j.chb.2017.01.020
  • Maier, C., Laumer, S., Eckhardt, A., & Weitzel, T. (2015). Giving too much social support: Social overload on social networking sites. European Journal of Information Systems, 24(5), 447–464. 10.1057/ejis.2014.3
  • Marx, W., Bornmann, L., Barth, A., & Leydesdorff, L. (2014). Detecting the historical roots of research fields by reference publication year spectroscopy (RPYS). Journal of the Association for Information Science and Technology, 65(4), 751-764. https://doi.org/10.1002/asi.23089
  • Noordin, N. B. (2025). A bibliometric perspective on technology stress in academic settings: Trends, challenges, and solutions. International Journal of Social Science and Business, 9(1), 1–19.
  • Pang, H., Ji, M., & Hu, X. (2023). How differential dimensions of social media overload influence young people’s fatigue and negative coping during the prolonged COVID-19 pandemic? Insights from a technostress perspective. Healthcare, 11(1), 6. 10.3390/healthcare11010006.
  • Ragu-Nathan, T. S., Tarafdar, M., Ragu-Nathan, B., & Tu, Q. (2008). The consequences of technostress for end users in organizations. Information Systems Research, 19(4), 417–433.
  • Ribeiro, H. C. M., Corrêa, R., Pierot, R. M., & do Nascimento Leal, L. G. (2024). 20 years of the Kyoto Protocol: Profile and behavior in Brazilian academia from the perspective of social network analysis. Revista de Gestão Social e Ambiental, 18(11), 1–28.
  • Sari, I. G. A. C. P., & Muna, N. (2024). Connecting virtually: E-service quality, social network, customer trust, and purchase intention. Quantitative Economics and Management Studies, 5(3), 695–703. 10.35877/454RI.qems2677
  • Say, S., Doğan, M., Abdeshov, D., Tekbaş, M., Sezal, L., & Erdoğan, B. (2025). Evolution of financial development research: A bibliometric analysis. Journal of Risk and Financial Management, 18(1), 10. 10.3390/jrfm18010010
  • Soelistyowati, R. D., Subhan, A., & Sigit, R. R. (2024). Virtual public sphere on social media (Habermas’ critical study of the digital hoax phenomenon WhatsApp group alumni ILUNI MENWA UI). International Journal of Educational Research & Social Sciences, 5(2), 284–289.
  • Stamenković, I., & Aleksić, D. (2025). Digital overload: Fatigue and information avoidance on social media. Applied Media Studies Journal, 6(2), 27–41. 10.46630/amsj.2.2025.02
  • Summak, M. E., & Çöllü, E. F. (2025). Algoritmik iletişim ve halkla ilişkiler: Etik, etki ve düzenleme tartışmaları. Eğitim Yayınevi.
  • Tarafdar, M., Maier, C., Laumer, S., & Weitzel, T. (2020). Explaining the link between technostress and technology addiction for social networking sites: A study of distraction as a coping behavior. Information Systems Journal, 30(1), 96–124. 10.1111/isj.12253.
  • Tarafdar, M., Tu, Q., Ragu-Nathan, T., & Ragu-Nathan, B. (2007). The impact of technostress on role stress and productivity. Journal of Management Information Systems, 24(1), 301–328.
  • Tarafdar, M., Tu, Q., Ragu-Nathan, T., & Ragu-Nathan, B. (2011). Crossing to the dark side: Examining creators, outcomes, and inhibitors of technostress. Communications of the ACM, 54(9), 113–120.
  • Tung, L. T., & Hoang, D. V. (2023). Impact of social network usage on employees’ work performance in public organizations: Evidence from Vietnam. In Proceedings of the International Conference on Business Excellence (Vol. 17, No. 1, pp. 1691–1701). Sciendo. 10.2478/picbe-2023-0151
  • Usui, Y., Nakajima, K., Takano, C., & Aida, M. (2023, November). Perturbation Theory of Online User Dynamics with Respect to Change in Social Network Structures. 2023 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech) (pp. 0401-0407). IEEE.
  • Vanden Abeele, M. (2021). Digital well-being as a dynamic construct. Communication Theory, 31(4), 932–955.
  • Xiao, L., Guo, F., Yu, F., & Liu, S. (2019). The effects of online shopping context cues on consumers’ purchase intention for cross-border e-commerce sustainability. Sustainability, 11(10), 2777. 10.3390/su11102777
  • Xu, L., & Zhang, B. (2018). An empirical study on social media users’ fatigue and negative behavior from the perspective of cognitive load theory: Taking WeChat for example. Library Tribune, 38(11), 94–106.
  • Zhang, S., Shen, Y., Xin, T., Sun, H., Wang, Y., Zhang, X., & Ren, S. (2021). The development and validation of a social media fatigue scale: From a cognitive-behavioral-emotional perspective. PloS one, 16(1), e0245464. 10.1371/journal.pone.0245464
  • Zhang, S., Zhao, L., Lu, Y., & Yang, J. (2016). Do you get tired of socializing? An empirical explanation of discontinuous usage behaviour in social network services. Information & Management, 53(7), 904–914. 10.1016/j.im.2016.03.006
  • Zhang, Y., Chen, J., Yuan, S., Cao, Q., Cruce, A., Gu, H., … Chen, W. (2025). Social network as an engagement approach in child maltreatment prevention programs: A scoping review. Research on Social Work Practice. 10.1177/10497315251338478

BİBLİYOMETRİK YAKLAŞIMLA SOSYAL AĞ YORGUNLUĞU LİTERATÜRÜNÜN SİSTEMATİK İNCELENMESİ

Yıl 2026, Cilt: 16 Sayı: 2 , 729 - 749 , 01.04.2026
https://doi.org/10.7456/tojdac.1857161
https://izlik.org/JA25DJ76EL

Öz

Bu çalışma, sosyal ağ yorgunluğu literatürünü, kavramın temellerini oluşturan bilgi aşırı yüklemesi, medya yorgunluğu ve teknostres gibi öncül yaklaşımlar çerçevesinde, 1983–2025 yılları arasında bibliyometrik analiz yöntemiyle incelemektedir. Web of Science (WoS) veri tabanından 832 doküman, 3967 yazar ve 590 kaynağa ilişkin veriler R Studio ile analiz edilmiştir. Bulgular, literatürün yıllık ortalama %12,03 oranında büyüdüğünü ve özellikle 2010 sonrasında, COVID-19 pandemisinin etkisiyle akademik üretimde belirgin bir yoğunlaşma yaşandığını ortaya koymaktadır. Bulgular, sosyal ağ yorgunluğu araştırmalarının yalnızca bireysel psikolojik belirtilere odaklanan betimleyici bir çizgiden uzaklaşarak, FoMO ve Stres-Zorlanma-Sonuç (SSO) modeli gibi teorik çerçeveler aracılığıyla çok boyutlu ve disiplinlerarası bir yapıya evrildiğini göstermektedir. Tematik analizler, ruh sağlığı, yaşam kalitesi, depresyon ve anksiyete kavramlarının literatürün merkezinde konumlandığını ortaya koymaktadır. Önceki bibliyometrik çalışmalardan farklı olarak bu araştırma, sosyal ağ yorgunluğunu yalnızca anahtar kelime ve atıf ağları üzerinden değil, teorik yönelimlerin dönüşümünü de dikkate alan bütüncül bir analizle ele almaktadır. Bu yönüyle çalışma, alanın entelektüel gelişim çizgisini görünür kılarak gelecekteki kuramsal ve uygulamalı araştırmalar için sistematik bir referans çerçevesi sunmaktadır.

Kaynakça

  • Ayyagari, R., Grover, V., & Purvis, R. (2011). Technostress: Technological antecedents and implications. MIS Quarterly, 35(4), 831–858.
  • Azizan, A. (2024). Exploring the role of social media in mental health research: A bibliometric and content analysis. Journal of Scientometric Research, 13(1), 1–8.
  • Bailenson, J. N. (2021). Nonverbal overload: A theoretical argument for the causes of Zoom fatigue. Technology, Mind, and Behavior, 2(1). 10.1037/tmb0000030
  • Bright, L. F., Kleiser, S. B., & Grau, S. L. (2015). Too much Facebook? An exploratory examination of social media fatigue. Computers in Human Behavior, 44, 148–155. 10.1016/j.chb.2014.11.048
  • Brod, C. (1984). Technostress: The human cost of the computer revolution. Addison-Wesley.
  • Burr, C., Taddeo, M., & Floridi, L. (2020). The ethics of digital well-being: A thematic review. Science and Engineering Ethics, 26(4), 2313–2343
  • Chen, B., Sun, X., Zhang, Q., & Yao, L. (2024). Are fatigued users fleeing social media? A three-level meta-analysis on the association between social media fatigue and social media use. Psychology of Popular Media, 13(3), 457–471. 10.1037/ppm0000495
  • Cho, J., Ramgolam, D. I., Schaefer, K. M., & Sandlin, J. K. (2011). The rate and delay in overload: An investigation of communication overload and channel synchronicity on identification and job satisfaction. Journal of Applied Communication Research, 39(1), 38–54.
  • Chung, T. L. D., Kim, K., & Lee, A. (2025). Social network analysis in fashion research: A systematic literature review. Clothing and Textiles Research Journal. 10.1177/0887302X251325144
  • Cramer, E. M., Song, H., & Drent, A. M. (2016). Social comparison on Facebook: Motivation, affective consequences, self-esteem, and Facebook fatigue. Computers in Human Behavior, 64, 739-746.
  • Dallmann, A., Teutonico, D., Schaller, S., Burghaus, R., & Frechen, S. (2024). In-depth analysis of the selection of PBPK modeling tools: Bibliometric and social network analysis of the Open Systems Pharmacology Community. The Journal of Clinical Pharmacology, 64(9), 1055–1067.
  • Dhir, A., Yossatorn, Y., Kaur, P., & Chen, S. (2018). Online social media fatigue and psychological wellbeing: A study of compulsive use, fear of missing out, fatigue, anxiety and depression. International Journal of Information Management, 40, 141–152. 10.1016/j.ijinfomgt.2018.01.012
  • Donkers, T., & Ziegler, J. (2025, June). Understanding online polarization through human-agent interaction in a synthetic LLM-based social network. Proceedings of the International AAAI Conference on Web and Social Media (Vol. 19, pp. 457–478).
  • dos Santos, B. Z., Reginaldo, L., da Silva, P. R., Vales, S. D. S., Morselli, N. V., & Júnior, J. R. A. (2024). Improving metadata quality in social network classification systems. Revista de Gestão Social e Ambiental, 18(12), 1–12.
  • Ellison, N. B., Steinfield, C., & Lampe, C. (2007). The benefits of Facebook “friends:” Social capital and college students’ use of online social network sites. Journal of Computer-Mediated Communication, 12(4), 1143–1168. 10.1111/j.1083-6101.2007.00367.x
  • Fox, J., & Moreland, J. J. (2015). The dark side of social networking sites: An exploration of the relational and psychological stressors associated with Facebook use and affordances. Computers in Human Behavior, 45, 168–176.
  • Gandasari, D., Tjahjana, D., Dwidienawati, D., & Sugiarto, M. (2024). Bibliometric and visualized analysis of social network analysis research on Scopus databases and VOSviewer. Cogent Business & Management, 11(1), 2376899.
  • Jana, D., & Heuser, C. (2025). Making sense of mental health in later life: Social network dynamics and service access. International Journal of Qualitative Studies on Health and Well-Being, 20(1), 2581516.
  • Kurşunmaden, F. İ. (2025). Bibliometric Analysis of Studies on the Concept of Vuca. Fiscaoeconomia, 9(2), 927-938. https://doi.org/10.25295/fsecon.1586089
  • Lee, A. R., Son, S. M., & Kim, K. K. (2016). Information and communication technology overload and social networking service fatigue: A stress perspective. Computers in Human Behavior, 55, 51–61. 10.1016/j.chb.2015.08.011
  • Li, Z. (2025). Maximum likelihood estimation for Erdős–Rényi graphs in social network analysis. Proceedings of the 3rd International Conference on Mathematical Physics and Computational Simulation (pp. 225–231). 10.54254/2753-8818/100/2025.22144
  • Liu, Y., Diehl, S., & Terlutter, R. (2023). The negative side of social media: A systematic review of social media fatigue. International Journal of Human–Computer Interaction, 39(1), 1-22. https://doi.org/10.1080/10447318.2022.2045564
  • Liu, Y., Mohamad, E. M. W., & Azlan, A. A. (2025). Social media fatigue and discontinuous usage: A meta-analytic structural equation modeling based on the stimulus-organism-response model. Review of Communication Research, 13(Special), 173-195. 10.52152/RCR.V13.S8
  • Luqman, A., Cao, X., Ali, A., Masood, A., & Yu, L. (2017). Empirical investigation of Facebook discontinuous usage intentions based on SOR paradigm. Computers in Human Behavior, 70, 544–555. 10.1016/j.chb.2017.01.020
  • Maier, C., Laumer, S., Eckhardt, A., & Weitzel, T. (2015). Giving too much social support: Social overload on social networking sites. European Journal of Information Systems, 24(5), 447–464. 10.1057/ejis.2014.3
  • Marx, W., Bornmann, L., Barth, A., & Leydesdorff, L. (2014). Detecting the historical roots of research fields by reference publication year spectroscopy (RPYS). Journal of the Association for Information Science and Technology, 65(4), 751-764. https://doi.org/10.1002/asi.23089
  • Noordin, N. B. (2025). A bibliometric perspective on technology stress in academic settings: Trends, challenges, and solutions. International Journal of Social Science and Business, 9(1), 1–19.
  • Pang, H., Ji, M., & Hu, X. (2023). How differential dimensions of social media overload influence young people’s fatigue and negative coping during the prolonged COVID-19 pandemic? Insights from a technostress perspective. Healthcare, 11(1), 6. 10.3390/healthcare11010006.
  • Ragu-Nathan, T. S., Tarafdar, M., Ragu-Nathan, B., & Tu, Q. (2008). The consequences of technostress for end users in organizations. Information Systems Research, 19(4), 417–433.
  • Ribeiro, H. C. M., Corrêa, R., Pierot, R. M., & do Nascimento Leal, L. G. (2024). 20 years of the Kyoto Protocol: Profile and behavior in Brazilian academia from the perspective of social network analysis. Revista de Gestão Social e Ambiental, 18(11), 1–28.
  • Sari, I. G. A. C. P., & Muna, N. (2024). Connecting virtually: E-service quality, social network, customer trust, and purchase intention. Quantitative Economics and Management Studies, 5(3), 695–703. 10.35877/454RI.qems2677
  • Say, S., Doğan, M., Abdeshov, D., Tekbaş, M., Sezal, L., & Erdoğan, B. (2025). Evolution of financial development research: A bibliometric analysis. Journal of Risk and Financial Management, 18(1), 10. 10.3390/jrfm18010010
  • Soelistyowati, R. D., Subhan, A., & Sigit, R. R. (2024). Virtual public sphere on social media (Habermas’ critical study of the digital hoax phenomenon WhatsApp group alumni ILUNI MENWA UI). International Journal of Educational Research & Social Sciences, 5(2), 284–289.
  • Stamenković, I., & Aleksić, D. (2025). Digital overload: Fatigue and information avoidance on social media. Applied Media Studies Journal, 6(2), 27–41. 10.46630/amsj.2.2025.02
  • Summak, M. E., & Çöllü, E. F. (2025). Algoritmik iletişim ve halkla ilişkiler: Etik, etki ve düzenleme tartışmaları. Eğitim Yayınevi.
  • Tarafdar, M., Maier, C., Laumer, S., & Weitzel, T. (2020). Explaining the link between technostress and technology addiction for social networking sites: A study of distraction as a coping behavior. Information Systems Journal, 30(1), 96–124. 10.1111/isj.12253.
  • Tarafdar, M., Tu, Q., Ragu-Nathan, T., & Ragu-Nathan, B. (2007). The impact of technostress on role stress and productivity. Journal of Management Information Systems, 24(1), 301–328.
  • Tarafdar, M., Tu, Q., Ragu-Nathan, T., & Ragu-Nathan, B. (2011). Crossing to the dark side: Examining creators, outcomes, and inhibitors of technostress. Communications of the ACM, 54(9), 113–120.
  • Tung, L. T., & Hoang, D. V. (2023). Impact of social network usage on employees’ work performance in public organizations: Evidence from Vietnam. In Proceedings of the International Conference on Business Excellence (Vol. 17, No. 1, pp. 1691–1701). Sciendo. 10.2478/picbe-2023-0151
  • Usui, Y., Nakajima, K., Takano, C., & Aida, M. (2023, November). Perturbation Theory of Online User Dynamics with Respect to Change in Social Network Structures. 2023 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech) (pp. 0401-0407). IEEE.
  • Vanden Abeele, M. (2021). Digital well-being as a dynamic construct. Communication Theory, 31(4), 932–955.
  • Xiao, L., Guo, F., Yu, F., & Liu, S. (2019). The effects of online shopping context cues on consumers’ purchase intention for cross-border e-commerce sustainability. Sustainability, 11(10), 2777. 10.3390/su11102777
  • Xu, L., & Zhang, B. (2018). An empirical study on social media users’ fatigue and negative behavior from the perspective of cognitive load theory: Taking WeChat for example. Library Tribune, 38(11), 94–106.
  • Zhang, S., Shen, Y., Xin, T., Sun, H., Wang, Y., Zhang, X., & Ren, S. (2021). The development and validation of a social media fatigue scale: From a cognitive-behavioral-emotional perspective. PloS one, 16(1), e0245464. 10.1371/journal.pone.0245464
  • Zhang, S., Zhao, L., Lu, Y., & Yang, J. (2016). Do you get tired of socializing? An empirical explanation of discontinuous usage behaviour in social network services. Information & Management, 53(7), 904–914. 10.1016/j.im.2016.03.006
  • Zhang, Y., Chen, J., Yuan, S., Cao, Q., Cruce, A., Gu, H., … Chen, W. (2025). Social network as an engagement approach in child maltreatment prevention programs: A scoping review. Research on Social Work Practice. 10.1177/10497315251338478
Toplam 46 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Sosyal Medya Çalışmaları, Ekran ve Medya Kültürü
Bölüm Araştırma Makalesi
Yazarlar

Eyüp Erdal Yörük 0000-0001-6802-9502

Gönderilme Tarihi 6 Ocak 2026
Kabul Tarihi 27 Mart 2026
Yayımlanma Tarihi 1 Nisan 2026
DOI https://doi.org/10.7456/tojdac.1857161
IZ https://izlik.org/JA25DJ76EL
Yayımlandığı Sayı Yıl 2026 Cilt: 16 Sayı: 2

Kaynak Göster

APA Yörük, E. E. (2026). BİBLİYOMETRİK YAKLAŞIMLA SOSYAL AĞ YORGUNLUĞU LİTERATÜRÜNÜN SİSTEMATİK İNCELENMESİ. The Turkish Online Journal of Design Art and Communication, 16(2), 729-749. https://doi.org/10.7456/tojdac.1857161


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