AĞ TOPLUMU YAKLAŞIMI İLE AKADEMİK BİR SOSYAL AĞ MODELİ İÇİN GRAF VERİ TABANI ÖNERİSİ

Year 2021, , 68 - 88, 01.06.2021

Alper Değerli

https://doi.org/10.14514/BYK.m.26515393.2021.9/1.68-88

Abstract

Son yirmi beş yılda enformasyon ve iletişim teknolojilerinde yaşanan dramatik gelişim ile toplumsal ilişki biçimlerinin bilinen yapısal formları dönüşüme uğramıştır. Castells’in Ağ Toplumu olarak ifade ettiği ve akışlar iktidarı olarak betimlediği toplumsal yapının günümüzün dijital dünyasındaki izdüşümleri olarak yorumlanabilecek online sosyal ağlar sosyalleşmenin yeni formları olarak karşımıza çıkmaktadır. Sosyal ağlar yoluyla bilgi akışının hiç olmadığı kadar hızlı ve yoğun gerçekleştiği günümüzde, motivasyonunu bilginin üretimi ve yayımından alan akademik dünyayı da bu kapsam dışında düşünmek mümkün olmayacaktır. Bu amaçla online sosyal ağlarda bilginin sınırsız dolaşımı yoluyla bilginin demokratikleşmesi ve bilgiye açık erişim felsefesi ile örtüşen bir akademik yayın ve referans veri tabanı oluşturulmaya çalışılmıştır. Bu kapsamda geleneksel veri tabanlarının sahip olduğu kısıtların aksine sosyal ağlar gibi ağ formunda şekillenen toplulukları kolaylıkla modelleyebilmesi nedeniyle, bir graf veri tabanı platformu olan Neo4j kullanılarak bir alternatif akademik sosyal ağ modeli için veri tabanı önerisi sunulmuştur.

Keywords

Ağ Toplumu, Online Sosyal Ağlar, Graf Veri Tabanı

GRAPH DATABASE PROPOSAL FOR AN ACADEMIC SOCIAL NETWORK MODEL WITH NETWORK SOCIETY APPROACH

Abstract

With the dramatic development in information and communication technologies in the last twenty-five years, known structural forms of social relations have transformed. Online social networks, which can be interpreted as the projections of the social structure that Castells describes as the Network Society and the power of flows in today's digital world, emerge as new forms of socialization. In today's world where the flow of information through social networks takes place faster and intensive than ever before, it will not be possible to think of the academic world, which is motivated by the production and dissemination of information, outside of this scope. For this purpose, through unlimited circulation of information in online social networks, an academic publication and reference database was created in line with the democratization of information and open access to information philosophy. In this context, a database proposal for an alternative academic social network model was presented by using Neo4j, a graph database platform, since it can easily model communities shaped in the form of networks such as social networks contrary to the constraints of traditional databases.

Keywords

Network Society, Online Social Networks, Graph Database

References

• Angles, R. (2012). “A Comparison of Current Graph Database Models”, Data Engineering Workshops (ICDEW), 2012 IEEE 28th International Conference, 1-5 Nisan 2012, Washington, ABD: IEEE Computer Society, 171-177.
• Angles, R., Gutierrez, C. (2008). Survey of Graph Database Models. ACM Comput. Surv. Vol. 40, No. 1, 1-39.
• Batra, S., Tyagi, C. (2012). Comparative Analysis of Relational and Graph Databases. International Journal of Soft Computing and Engineering (IJSCE). Vol. 2, No. 2, 509-512.
• Berg K. L., Seymour, T., Goel, R. (2013). History of Databases. International Journal Of Management & Information Systems. Vol. 17, No. 1, 29-35.
• Bhide, A.M., Heung, Y.J., Kee, C.M. (2007). “Research Library: A New Look of Academic Digital Libraries”, Second International Conference on Internet and Web Applications and Services (ICIW'07), 13-19 Mayıs 2007, Mauritius, 1-5.
• Castells, M. (2005). Enformasyon Çağı: Ekonomi, Toplum ve Kültür – Birinci Cilt: Ağ Toplumunun Yükselişi. (Çev.: Ebru Kılıç). İstanbul: İstanbul Bilgi Üniversitesi Yayınları.
• Castells, M. (2005). Enformasyon Çağı: Ekonomi, Toplum ve Kültür – Üçüncü Cilt: Binyılın Sonu. (Çev.: Ebru Kılıç). İstanbul: İstanbul Bilgi Üniversitesi Yayınları.
• Chairunnanda, P., Forsyth, S., Daudjee, K. (2012). “Graph Data Partition Models for Online Social Networks”, Proceedings of the 23rd ACM Conference on Hypertext and Social Media, 25-28 Haziran 2012, Amerika: ACM, 175-179.
• Costa, F. F. (2013). Social Networks,Web-Based Tools and Diseases: Implications For Biomedical Research. Drug Discovery Today. Vol. 18, No. 5-6, 272–281.
• Dukić, D. (2010). “Online Academic Databases Use in Croatian Higher Education”, Proceedings of the 32nd Int. Conf. on Information Technology Interfaces, 21-24 Haziran 2010, Hırvatistan: IEEE, 349-354.
• Hansen, D. L., Shneiderman, B., Smith, M.A. (2011). Analyzing Social Media Networks with NodeXL: Insights From a Connected World. 1. Basım. Çin: Elsevier Inc.
• Kierkegaard, P., Adrian, A. (2010). Wikitopia: Balancing Intellectual Property Rights Within Open Source Research Databases. Computer Law & Security Review. No.26, 502-519.
• Miller, J.J. (2013). “Graph Database Applications and Concepts with Neo4j”. Proceedings of the Southern Association for Information Systems Conference, 23-24 Mart 2013, ABD, 141-147.
• Neo4j Team, The. (2013). “The Neo4j Manual v2.0.0”. http://doc.we-yun.com:1008/neo4j-doc/2.X/other%20manuals/neo4j-manual-2.0.0.pdf.
• O’Reilly, T. (2006, 10 Aralık), “Web 2.0 Compact Definition: Trying Again”. http://radar.oreilly.com/2006/12/web-20-compact-definition-tryi.html
• Oh, J.S., Jeng, W. (2011). “Groups in Academic Social Networking Services: An Exploration of Their Potential as a Platform for Multi-disciplinary Collaboration”, 2011 IEEE Third International Conference on Social Computing, 9-11 Ekim 2011, Washington, ABD: IEEE, 545 – 548.
• Partner, J., Vukotic, A., Watt, N. (2012). Neo4j in Action. 1. Basım. New York: Manning Publications.
• Rajbhandari, P., Shah, R.C., Agarwal, S. (2012). “Graph Database Model for Querying, Searching and Updating”, 2012 International Conference on Software and Computer Applications (ICSCA 2012), 9-10 Haziran 2012, Singapur, 170-175.
• Redmond, E., Wilson, J.R. (2018). Seven Databases in Seven Weeks: A Guide to Modern Databases and the NoSQL Movement. 2. Basım. Amerika: The Pragmatic Bookshelf.
• Robinson, I., Webber, J., Eifrem, E. (2013). Graph Databases, 1. Basım. California: O’Reilly.
• Soussi, R., Aufaure, M.A., Baazaoui, H. (2010). “Towards Social Network Extraction Using a Graph Database”. 2010 Second International Conference on Advances in Databases, Knowledge, and Data Applications, 11-16 Nisan 2010, Fransa: CPS, 28-34.
• Soussi, R., Aufaure, M.A., Baazaoui, H. (2011). “Graph Database for Collaborative Communities”, Pardede, E. (Ed.). Community-Built Database, Heidelberg: Springer, 205-234.
• van Dijk, J. (2012). The Network Society 3rd Editon. 1. Basım. Londra: SAGE Publications.
• Vicknair, C., Macias, M., Zhao, Z., Nan, X., Chen, Y., Wilkins, D. (2010). “A Comparison of a Graph Database and a Relational Database: A Data Provenance Perspective”. Proceedings of the 48th Annual Southeast Regional Conference, 15-17 Nisan 2010, New York, ABD: ACM, 1-6.
• Warchal, L. (2012). Using Neo4j Graph Database in Social Network Analysis. Studia Informatica. Number 2A(105), 271-279.
• Williams, W.G. (2010). Uses and Limitations of Registry and Academic Databases. Pediatric Cardiac Surgery Annual. Vol. 13, No. 2, 66-70.