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Kürsü: Oylaşma Süreçleri için Sosyal Medya Etkili Yönetişim Modeli

Yıl 2022, Cilt: 15 Sayı: 2, 125 - 139, 15.12.2022
https://doi.org/10.54525/tbbmd.1147066

Öz

Güncel yönetişim paradigmaları oylaşmacı süreçler ve temsili kurumlar arasındaki entegrasyonu geliştirmeye odaklanmaktadır. Bu tartışmalar çoğunlukla, açık ve saydam iletişim mekanizmalarının yanı sıra doğrudan katılımı sağlayan süreçlerin geliştirilmesine ve güven mekanizmalarının artırılmasına yönelik gereksinimler etrafında şekillenmektedir. Benzer gereksinimlerden yola çıkarak çalışmamızda, katılımcı ve oylaşmacı süreçlerin takibi ve korunmasını güvence altına alan, sosyal medya etkili yeni bir yönetişim modeli önerilmiştir. Model, etiket yapısı üzerine inşa edilmiş ve iletişimin temel mekanizmaları olan bağlam, değişmezlik, güvenilirlik ve tutarlılık gibi unsurlar etrafında şekillendirilmiştir. Bu modelin geliştirilmesinde, güncel ve değişmezliğin kontrolünü sağlayan bir teknoloji olması nedeniyle öbek zincirinin özetleme mekanizmasından yararlanılmıştır. Ancak öbek zinciri değişebilir veri, bağlam, güvenilirlik ve tutarlılık gibi mekanizmaların modellenmesi için uygun değildir. Bu nedenle, öbek zincirinin veri yapısında söz konusu mekanizmaların desteklenmesi için bazı değişiklikler yapılmış ve sonucunda da geliştirdiğimiz model ile öbek zinciri teknolojisi, zaman ve alan karmaşıklığı açısından karşılaştırılmıştır. Karşılaştırma sonucunda, geliştirdiğimiz modelin temelini oluşturan etiket yapısının, öbek zincirinin veri yapısına göre daha yüksek başarım ortaya koyduğu tespit edilmiştir. Önerimizin, topluluk yönetimlerinde güvenilir bir sosyal medya ortamı oluşturarak oylaşma süreçlerinin geliştirilmesine katkı sunması beklenmektedir.

Destekleyen Kurum

Destekleyen kurum bulunmamaktadır.

Kaynakça

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  • García, M.J.G. Smart regulation law-making and participatory democracy: consultation in the European Union. Revista catalana de dret públic, 2019, 59. pp. 85-96.
  • Gonzalez-Zapata F, Heeks R. The multiple meanings of open government data: Understanding different stakeholders and their perspectives. Gov Inf Q. 2015;32: 441–452.
  • Issacharoff S. Democracy’s Deficits. Univ Chic Law Rev. 2018;85: 485–520.
  • Turnhout E, Metze T, Wyborn C, Klenk N, Louder E. The politics of co-production: participation, power, and transformation. Current Opinion in Environmental Sustainability. 2020;42: 15–21.
  • Dwyer T, Martin F. Sharing news online: Social media news analytics and their implications for media pluralism policies. Digital journalism. 2017. Available: https://www.tandfonline.com/doi/abs/10.1080/21670811.2017.1338527
  • Kodila-Tedika O. Natural resource governance: Does social media matter? Mineral Economics. 2021;34: 127–140.
  • Asongu SA, Odhiambo NM. Governance and social media in African countries: An empirical investigation. Telecomm Policy. 2019. Available: https://www.sciencedirect.com/science/article/pii/S0308596118302635.
  • Ballou DP, Pazer HL. Modeling completeness versus consistency tradeoffs in information decision contexts. IEEE Trans Knowledge Data Eng. 2003;15: 240–243.
  • Mojzisch A, Grouneva L, Schulz-Hardt S. Biased evaluation of information during discussion: Disentangling the effects of preference consistency, social validation, and ownership of information. Europe Journal Social Psychology. 2010;40: 946–956.
  • Liu W, Zhang H, Liang H, Li C-C, Dong Y. Managing Consistency and Consensus Issues in Group Decision-Making with Self-Confident Additive Preference Relations and Without Feedback: A Nonlinear Optimization Method. Group Decision and Negotiation. 2022;31: 213–240.
  • Höglund K, Svensson I. “Sticking one’s neck out”: Reducing mistrust in Sri lanka’s peace negotiations. Negot J. 2006;22: 367–387.
  • Yao J, Storme M. Trust Building via Negotiation: Immediate versus Lingering Effects of General Trust and Negotiator Satisfaction. Group Decision and Negotiation. 2021;30: 507–528.
  • Wang P, Meng J, Chen J, Liu T, Zhan Y, Tsai W-T, et al. Smart Contract-Based Negotiation for Adaptive QoS-Aware Service Composition. IEEE Trans Parallel Distrib Syst. 2019;30: 1403–1420.
  • Politou E, Casino F, Alepis E, Patsakis C. Blockchain Mutability: Challenges and Proposed Solutions. IEEE Transactions on Emerging Topics in Computing. 2021;9: 1972–1986.
  • Reif JAM, Kunz FA, Kugler KG. Negotiation contexts: How and why they shape women’s and men's decision to negotiate. Negotiation and. 2019. Available: https://onlinelibrary.wiley.com/doi/abs/10.1111/ncmr.12153
  • Crump L. Analyzing complex negotiations. Negotiation Journal. 2015. Available: https://onlinelibrary.wiley.com/doi/abs/10.1111/nejo.12086
  • Chen H, Miguel BN, Zhou L, Guo CP. Expanding the concept of requirements traceability: The role of electronic records management in gathering evidence of crucial communications and negotiations. Aslib Proc. 2011;63: 168–187.
  • Mohan K, Ramesh B. Traceability-based knowledge integration in group decision and negotiation activities. Decis Support Syst. 2007. Available: https://www.sciencedirect.com/science/article/pii/S0167923605000916.
  • Omar A, Weerakkody V, Daowd A. Studying Transformational Government: A review of the existing methodological approaches and future outlook. Gov Inf Q. 2020;37. doi:10.1016/j.giq.2020.101458.
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  • Sivarajah U, Weerakkody V, Waller P, Lee H, Irani Z, Choi Y, et al. The role of e-participation and open data in evidence-based policy decision making in local government. Journal of Organizational Computing and Electronic Commerce. 2016;26: 64–79.
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  • Anttiroiko A-V, Valkama P, Bailey SJ. Smart cities in the new service economy: building platforms for smart services. AI Soc. 2014;29: 323–334.
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  • Nesti G. Defining and assessing the transformational nature of smart city governance: Insights from four European cases. International Review of Administrative Sciences. 2020;86: 20–37.
  • Odendaal N. Information and communication technology and local governance: understanding the difference between cities in developed and emerging economies. Comput Environ Urban Syst. 2003;27: 585–607.
  • Alawadhi S, Aldama-Nalda A, Chourabi H, Gil-Garcia JR, Leung S, Mellouli S, et al. Building Understanding of Smart City Initiatives. Electronic Government. Springer Berlin Heidelberg; 2012. pp. 40–53.
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  • Enikolopov R, Petrova M, Sonin K. Social media and corruption. J Appl Econ. 2018. Available: https://www.aeaweb.org/articles?id=10.1257/app.20160089
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  • Hassija V, Chamola V, Krishna DNG, Kumar N, Guizani M. A Blockchain and Edge-Computing-Based Secure Framework for Government Tender Allocation. IEEE Internet of Things Journal. 2021. pp. 2409–2418. doi:10.1109/jiot.2020.3027070.
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Lectern: Social Media Oriented Governance Model for Negotiation Processes

Yıl 2022, Cilt: 15 Sayı: 2, 125 - 139, 15.12.2022
https://doi.org/10.54525/tbbmd.1147066

Öz

Current governance paradigms focus on improving integration between deliberative processes and representative institutions. These discussions are mainly shaped around the need to develop open and transparent communication mechanisms and processes that ensure direct participation and increase trust mechanisms. Based on similar needs, a new social media effective governance model has been proposed in our study, which ensures the monitoring and protection of participatory and deliberative processes. The model is built on the tag structure and shaped around elements such as context, immutability, reliability, and consistency, which are the basic mechanisms of communication. In the development of this model, the hashing mechanism of the blockchain was used, as it is a technology that provides up-to-date and immutability control. However, blockchain is unsuitable for modeling mechanisms such as mutable data, context, reliability, and consistency. For this reason, some changes were made in the data structure of the blockchain to support these mechanisms, and as a result, the model we developed was compared with the blockchain technology in terms of time and space complexity. As a result of the comparison, it has been determined that the tag structure, which forms the basis of the model we developed, has higher performance than the data structure of the blockchain. Our proposal is expected to contribute to the development of negotiation processes by creating a reliable social media environment in community administrations.

Kaynakça

  • Pateman C. Participatory Democracy Revisited. Perspectives on Politics. 2012;10: 7–19.
  • García, M.J.G. Smart regulation law-making and participatory democracy: consultation in the European Union. Revista catalana de dret públic, 2019, 59. pp. 85-96.
  • Gonzalez-Zapata F, Heeks R. The multiple meanings of open government data: Understanding different stakeholders and their perspectives. Gov Inf Q. 2015;32: 441–452.
  • Issacharoff S. Democracy’s Deficits. Univ Chic Law Rev. 2018;85: 485–520.
  • Turnhout E, Metze T, Wyborn C, Klenk N, Louder E. The politics of co-production: participation, power, and transformation. Current Opinion in Environmental Sustainability. 2020;42: 15–21.
  • Dwyer T, Martin F. Sharing news online: Social media news analytics and their implications for media pluralism policies. Digital journalism. 2017. Available: https://www.tandfonline.com/doi/abs/10.1080/21670811.2017.1338527
  • Kodila-Tedika O. Natural resource governance: Does social media matter? Mineral Economics. 2021;34: 127–140.
  • Asongu SA, Odhiambo NM. Governance and social media in African countries: An empirical investigation. Telecomm Policy. 2019. Available: https://www.sciencedirect.com/science/article/pii/S0308596118302635.
  • Ballou DP, Pazer HL. Modeling completeness versus consistency tradeoffs in information decision contexts. IEEE Trans Knowledge Data Eng. 2003;15: 240–243.
  • Mojzisch A, Grouneva L, Schulz-Hardt S. Biased evaluation of information during discussion: Disentangling the effects of preference consistency, social validation, and ownership of information. Europe Journal Social Psychology. 2010;40: 946–956.
  • Liu W, Zhang H, Liang H, Li C-C, Dong Y. Managing Consistency and Consensus Issues in Group Decision-Making with Self-Confident Additive Preference Relations and Without Feedback: A Nonlinear Optimization Method. Group Decision and Negotiation. 2022;31: 213–240.
  • Höglund K, Svensson I. “Sticking one’s neck out”: Reducing mistrust in Sri lanka’s peace negotiations. Negot J. 2006;22: 367–387.
  • Yao J, Storme M. Trust Building via Negotiation: Immediate versus Lingering Effects of General Trust and Negotiator Satisfaction. Group Decision and Negotiation. 2021;30: 507–528.
  • Wang P, Meng J, Chen J, Liu T, Zhan Y, Tsai W-T, et al. Smart Contract-Based Negotiation for Adaptive QoS-Aware Service Composition. IEEE Trans Parallel Distrib Syst. 2019;30: 1403–1420.
  • Politou E, Casino F, Alepis E, Patsakis C. Blockchain Mutability: Challenges and Proposed Solutions. IEEE Transactions on Emerging Topics in Computing. 2021;9: 1972–1986.
  • Reif JAM, Kunz FA, Kugler KG. Negotiation contexts: How and why they shape women’s and men's decision to negotiate. Negotiation and. 2019. Available: https://onlinelibrary.wiley.com/doi/abs/10.1111/ncmr.12153
  • Crump L. Analyzing complex negotiations. Negotiation Journal. 2015. Available: https://onlinelibrary.wiley.com/doi/abs/10.1111/nejo.12086
  • Chen H, Miguel BN, Zhou L, Guo CP. Expanding the concept of requirements traceability: The role of electronic records management in gathering evidence of crucial communications and negotiations. Aslib Proc. 2011;63: 168–187.
  • Mohan K, Ramesh B. Traceability-based knowledge integration in group decision and negotiation activities. Decis Support Syst. 2007. Available: https://www.sciencedirect.com/science/article/pii/S0167923605000916.
  • Omar A, Weerakkody V, Daowd A. Studying Transformational Government: A review of the existing methodological approaches and future outlook. Gov Inf Q. 2020;37. doi:10.1016/j.giq.2020.101458.
  • Mahmood M, Weerakkody V, Chen W. The influence of transformed government on citizen trust: insights from Bahrain. Information Technology for Development. 2019;25: 275–303.
  • Sivarajah U, Weerakkody V, Waller P, Lee H, Irani Z, Choi Y, et al. The role of e-participation and open data in evidence-based policy decision making in local government. Journal of Organizational Computing and Electronic Commerce. 2016;26: 64–79.
  • Khan GF, Park HW. The e-government research domain: A triple helix network analysis of collaboration at the regional, country, and institutional levels. Governance Information Q. 2013;30: 182–193.
  • Layne K, Lee J. Developing fully functional E-government: A four stage model. Gov Inf Q. 2001;18: 122–136.
  • Moon MJ. The evolution of E‐government among municipalities: Rhetoric or reality? Public Adm. Rev. 2002;62: 424–433.
  • Meneklis V, Douligeris C. Bridging theory and practice in e-government: A set of guidelines for architectural design. Gov Inf Q. 2010;27: 70–81.
  • Prakash A. E-Governance and Public Service Delivery at the Grassroots: A Study of ICT Use in Health and Nutrition Programs in India. Information Technology For Development. 2016;22: 306–319.
  • Singh P, Dwivedi YK, Kahlon KS, Sawhney RS, Alalwan AA, Rana NP. Smart Monitoring and Controlling of Government Policies Using Social Media and Cloud Computing. Inf Syst Front. 2020;22: 315–337.
  • Caragliu AA, Del Bo C, Kourtit K, Nijkamp P. Comparative performance assessment of Smart Cities around the North Sea basin. NETWORK INDUSTRIES QUARTERLY. 2011;13: 15–17.
  • Anttiroiko A-V, Valkama P, Bailey SJ. Smart cities in the new service economy: building platforms for smart services. AI Soc. 2014;29: 323–334.
  • Rotta MJR, Sell D, dos Santos Pacheco RC, Yigitcanlar T. Digital Commons and Citizen Coproduction in Smart Cities: Assessment of Brazilian Municipal E-Government Platforms. Energies. 2019;12: 2813.
  • De Filippi F, Coscia C, Boella G, Antonini A, Calafiore A, Cantini A, et al. MiraMap: A We-Government Tool for Smart Peripheries in Smart Cities. IEEE Access. 2016;4: 3824–3843.
  • Denhardt JV, Denhardt RB. The new public service revisited. Public Adm Rev. 2015;75: 664–672.
  • Nesti G. Defining and assessing the transformational nature of smart city governance: Insights from four European cases. International Review of Administrative Sciences. 2020;86: 20–37.
  • Odendaal N. Information and communication technology and local governance: understanding the difference between cities in developed and emerging economies. Comput Environ Urban Syst. 2003;27: 585–607.
  • Alawadhi S, Aldama-Nalda A, Chourabi H, Gil-Garcia JR, Leung S, Mellouli S, et al. Building Understanding of Smart City Initiatives. Electronic Government. Springer Berlin Heidelberg; 2012. pp. 40–53.
  • Armitage D, Mbatha P, Muhl E-K, Rice W, Sowman M. Governance principles for community‐centered conservation in the post‐2020 global biodiversity framework. Conservat Sci and Prac. 2020;2. doi:10.1111/csp2.160.
  • Enikolopov R, Petrova M, Sonin K. Social media and corruption. J Appl Econ. 2018. Available: https://www.aeaweb.org/articles?id=10.1257/app.20160089
  • Qin B, Strömberg D, Wu Y. Why does China allow freer social media? Protests versus surveillance and propaganda. J Econ Perspect. 2017. Available: https://www.aeaweb.org/articles?id=10.1257/jep.31.1.117
  • Goritz A, Schuster J, Jörgens H, Kolleck N. International Public Administrations on Twitter: A Comparison of Digital Authority in Global Climate Policy. J Comp Pol Anal: Res Pract. 2022;24: 271–295.
  • Lin Y. A Comparison of selected Western and Chinese smart governance: The application of ICT in governmental management, participation and collaboration. Telecomm Policy. 2018;42: 800–809.
  • [Zhao M, Lin Y, Derudder B. Demonstration of public participation and communication through social media in the network society within Shanghai. Environment and Planning B: Urban Analytics and City Science. 2018. pp. 529–547. doi:10.1177/2399808317690154
  • Leleux C, Webster CWR. Delivering Smart Governance in a Future City: The Case of Glasgow. Media and Communication. 2018. pp. 163–174. doi:10.17645/mac.v6i4.1639
  • de Kervenoael R, Schwob A, Manson IT, Ratana C. Business-to-business and self-governance practice in the digital knowledge economy: Learning from pharmaceutical e-detailing in Thailand. Asian Business & Management. 2022;21: 598–622.
  • Lin Y, Zhang X, Geertman S. Toward smart governance and social sustainability for Chinese migrant communities. Journal of Cleaner Production. 2015. pp. 389–399. doi:10.1016/j.jclepro.2014.12.074.
  • Sifah EB, Xia H, Cobblah CNA, Xia Q, Gao J, Du X. BEMPAS: A Decentralized Employee Performance Assessment System Based on Blockchain for Smart City Governance. IEEE Access. 2020. pp. 99528–99539. doi:10.1109/access.2020.2997650.
  • Kumar V, Jain V, Sharma B, Chatterjee JM, Shrestha R. Smart City Infrastructure: The Blockchain Perspective. John Wiley & Sons; 2022.
  • Khan Z, Abbasi AG, Pervez Z. Blockchain and edge computing–based architecture for participatory smart city applications. Concurrency and Computation: Practice and Experience. 2020. doi:10.1002/cpe.5566.
  • Hassija V, Chamola V, Krishna DNG, Kumar N, Guizani M. A Blockchain and Edge-Computing-Based Secure Framework for Government Tender Allocation. IEEE Internet of Things Journal. 2021. pp. 2409–2418. doi:10.1109/jiot.2020.3027070.
  • Bai Y, Hu Q, Seo S-H, Kang K, Lee JJ. Public Participation Consortium Blockchain for Smart City Governance. IEEE Internet of Things Journal. 2022. pp. 2094–2108. doi:10.1109/jiot.2021.3091151.
  • Khanna A, Sah A, Bolshev V, Jasinski M, Vinogradov A, Leonowicz Z, et al. Blockchain: Future of e-Governance in Smart Cities. Sustainability. 2021. p. 11840. doi:10.3390/su132111840.
  • Verhulsdonck G, Weible JL, Helser S, Hajduk N. Smart Cities, Playable Cities, and Cybersecurity: A Systematic Review. International Journal of Human–Computer Interaction. 2021. pp. 1–13. doi:10.1080/10447318.2021.2012381.
  • Myeong S, Jung Y. Administrative Reforms in the Fourth Industrial Revolution: The Case of Blockchain Use. Sustainability. 2019. p. 3971. doi:10.3390/su11143971.
  • Alexopoulos C, Charalabidis Y, Loutsaris MA, Lachana Z. How Blockchain Technology Changes Government. International Journal of Public Administration in the Digital Age. 2021. pp. 1–20. doi:10.4018/ijpada.20210101.oa10.
  • Kassen M. Blockchain and e-government innovation: Automation of public information processes. Information Systems. 2022. p. 101862. doi:10.1016/j.is.2021.101862.
  • Carter L, Ubacht J. Blockchain applications in government. Proceedings of the 19th Annual International Conference on Digital Government Research: Governance in the Data Age. 2018. doi:10.1145/3209281.3209329.
  • Faria I. The market, the regulator, and the government: Making a blockchain ecosystem in the Netherlands. Finance and Society. 2021. pp. 40–56. doi:10.2218/finsoc.v7i1.5590.
  • Alketbi A, Nasir Q, Talib MA. Novel blockchain reference model for government services: Dubai government case study. International Journal of System Assurance Engineering and Management. 2020. pp. 1170–1191. doi:10.1007/s13198-020-00971-2.
  • Sujatha R, Navaneethan C, Kaluri R, Prasanna S. Optimized Digital Transformation in Government Services with Blockchain. Blockchain Technology and Applications. 2020. pp. 79–100. doi:10.1201/9781003081487-5.
  • [Nicolae-Bogdan-Cristian T, Luca SA, Pungila C. Towards Efficient Governance In Distributed Ledger Systems Using High-Performance Computational Nodes. 2020 22nd International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC). 2020. doi:10.1109/synasc51798.2020.00054.
  • Xuan J, Shi X, Sun X. Construction and Practice of Public Service Platform Based on Trusted Blockchain. Journal of Physics: Conference Series. 2020. p. 012046. doi:10.1088/1742-6596/1626/1/012046.
  • Grigorescu A, National University of Political Studies and Public Administration – SNSPA, Bucharest, Romania, Ion A-E. The Impact of Blockchain Technologies for the Agriculture Development and Sustainability. New Trends in Sustainable Business and Consumption. 2021. doi:10.24818/basiq/2021/07/033.
  • Jiang Y, Cheng XY, Zhu JW, Xu YT. A consensus mechanism based on multi-round concession negotiation. Comput Stand Interfaces. 2021;74. doi:10.1016/j.csi.2020.103488.
  • Feng JY, Zhao XY, Chen KX, Zhao F, Zhang GH. Towards random-honest miners selection and multi-blocks creation: Proof-of-negotiation consensus mechanism in blockchain networks. Future Generatıon Computer Systems-The Internatıonal Journal Of Escıence. 2020;105: 248–258.
  • Wu Y, Song LT, Liu L, Li JC, Li XF, Zhou LL. Consensus Mechanism of IoT Based on Blockchain Technology. Shock Vibr Dig. 2020;2020. doi:10.1155/2020/8846429.
  • Leng J.W., Sha W.N., Lin Z.S., Jing J.B., Liu Q., Chen X. Blockchained smart contract pyramid-driven multi-agent autonomous process control for resilient individualised manufacturing towards Industry 5.0. Int J Prod Res. doi:10.1080/00207543.2022.2089929.
  • Cormen T.H., Leiserson C.E., Rivest R.L., Stein C. Introduction to Algorithms, fourth edition. MIT Press; 2022.
  • Guner H, Acarturk C. The use and acceptance of ICT by senior citizens: A comparison of technology acceptance model (TAM) for elderly and young adults. Univers access inf soc. 2020;19: 311–330.
Toplam 68 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Mühendislik
Bölüm Makaleler(Araştırma)
Yazarlar

Savaş Takan 0000-0002-7718-9476

Duygu Ergün Takan 0000-0002-5639-8615

Erken Görünüm Tarihi 3 Aralık 2022
Yayımlanma Tarihi 15 Aralık 2022
Yayımlandığı Sayı Yıl 2022 Cilt: 15 Sayı: 2

Kaynak Göster

APA Takan, S., & Ergün Takan, D. (2022). Kürsü: Oylaşma Süreçleri için Sosyal Medya Etkili Yönetişim Modeli. Türkiye Bilişim Vakfı Bilgisayar Bilimleri Ve Mühendisliği Dergisi, 15(2), 125-139. https://doi.org/10.54525/tbbmd.1147066
AMA Takan S, Ergün Takan D. Kürsü: Oylaşma Süreçleri için Sosyal Medya Etkili Yönetişim Modeli. TBV-BBMD. Aralık 2022;15(2):125-139. doi:10.54525/tbbmd.1147066
Chicago Takan, Savaş, ve Duygu Ergün Takan. “Kürsü: Oylaşma Süreçleri için Sosyal Medya Etkili Yönetişim Modeli”. Türkiye Bilişim Vakfı Bilgisayar Bilimleri Ve Mühendisliği Dergisi 15, sy. 2 (Aralık 2022): 125-39. https://doi.org/10.54525/tbbmd.1147066.
EndNote Takan S, Ergün Takan D (01 Aralık 2022) Kürsü: Oylaşma Süreçleri için Sosyal Medya Etkili Yönetişim Modeli. Türkiye Bilişim Vakfı Bilgisayar Bilimleri ve Mühendisliği Dergisi 15 2 125–139.
IEEE S. Takan ve D. Ergün Takan, “Kürsü: Oylaşma Süreçleri için Sosyal Medya Etkili Yönetişim Modeli”, TBV-BBMD, c. 15, sy. 2, ss. 125–139, 2022, doi: 10.54525/tbbmd.1147066.
ISNAD Takan, Savaş - Ergün Takan, Duygu. “Kürsü: Oylaşma Süreçleri için Sosyal Medya Etkili Yönetişim Modeli”. Türkiye Bilişim Vakfı Bilgisayar Bilimleri ve Mühendisliği Dergisi 15/2 (Aralık 2022), 125-139. https://doi.org/10.54525/tbbmd.1147066.
JAMA Takan S, Ergün Takan D. Kürsü: Oylaşma Süreçleri için Sosyal Medya Etkili Yönetişim Modeli. TBV-BBMD. 2022;15:125–139.
MLA Takan, Savaş ve Duygu Ergün Takan. “Kürsü: Oylaşma Süreçleri için Sosyal Medya Etkili Yönetişim Modeli”. Türkiye Bilişim Vakfı Bilgisayar Bilimleri Ve Mühendisliği Dergisi, c. 15, sy. 2, 2022, ss. 125-39, doi:10.54525/tbbmd.1147066.
Vancouver Takan S, Ergün Takan D. Kürsü: Oylaşma Süreçleri için Sosyal Medya Etkili Yönetişim Modeli. TBV-BBMD. 2022;15(2):125-39.

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