Branko Arsić, Ljubiša Bojić, Ivan Milentijević, Petar Spalević, Dejan Rančić

DOI Number
First page
Last page


The unique possibilities of the online social networks such as real-time data access, knowledge of users’ changing preferences and access to their statuses provide the possibility for innovation in the analysis of people’s behavior and opinions, when compared to classical offline methods. Literature review shows lack of studies about the use of public Facebook data in Serbia for the improvement of different product sale, political or promotional campaigns, recommender systems, etc. In this paper, we present the way how data from Facebook can be collected in order to gain insight into the individuals’ preferences and statuses, as well as their connection to a company's fan pages. In particular, we present data collection framework – Symbols – used for collecting individual specific data. The framework stores data into local database and involves a module for graph and content-based analysis of these data. The proposed framework for social network analysis can be used as a decision-making system in users’ preferences implementation thus creating a space for business improvements in various areas.


framework, social network analysis, Facebook

Full Text:



B. Arsić, P. Spalević, Lj. Bojić, A. Crnišanin, "Social networks in logistics system decision-making," in Proceedings of 2nd Logistics International Conference (LOGIC 2015), pp. 166–171, Serbia, May 21–23, 2015 (ISSN: 978–86–7395–339–7).

C.H. Baird, G. Parasnis, "From social media to social customer relationship management," Strategy and Leadership, vol. 39, no. 5, pp. 30–37, 2011. Available:

N. Park, S. Lee, J.H. Kim, "Individuals' personal network characteristics and patterns of Facebook use: a social network approach," Computers in Human Behavior, vol. 28, no. 5, pp. 1700–1707, 2012. Available:

C.M. Cheung, M.K. Lee, "A theoretical model of intentional social action in online social networks," Decision Support Systems, vol. 49, no. 1, pp. 24–30, 2010. Available:

C. Forman, A. Ghose, B. Wiesenfeld, "Examining the relationship between reviews and sales: the role of reviewer identity discloser in electronic markets," Information Systems Research, vol. 19, no. 3, pp. 291–313, 2008. Available:

T. Hennig-Thurau, K. P. Gwinner, G. Walsh, D. D. Gremier, "Electronic word-of-mouth via consumer-opinion platforms: what motivates consumers to articulate themselves on the Internet," Journal of Interactive Marketing, vol. 18, no.1, pp. 38–52, 2004. Available:

D. Zeng, H. Chen, R. Lusch, S. H. Li, "Social media analytics and intelligence," Intelligent Systems, IEEE, vol. 25, no. 6, pp. 13–16, 2010. Available:

S. Wattal, D. Schuff, M. Mandviwalla, C. B. Williams, "Web 2.0 and politics: the 2008 US presidential election and an e-politics research agenda," Mis Quarterly, vol. 34, no.4, pp. 669–688, 2010. Available:

B. Arsić, M. Bašić, P. Spalević, M. Ilić, M. Veinović, "Facebook profiles clustering," in Proceedings of 6th International Conference on Information Society and Technology (ICIST 2016), Serbia, 28 February – 2 March 2016, pp. 154–158 (ISBN: 978–86–85525–16–2).

R. E. Wilson, S. D. Gosling, L. T. Graham, "A review of Facebook research in the social sciences," Perspectives on psychological science, vol. 7, no. 3, pp. 203–220, 2012. Available:

B. Rieder, "Studying Facebook via data extraction: the Netvizz application," In Proceedings of the 5th annual ACM web science conference, Paris, France, May 02–04, pp. 346–355. ACM, 2013.

M. Kovačević, Sintaksička negacija u srpskome jeziku. Izdavačka jedinica Univerziteta u Nišu, 2002.

CC. Aggarwal, "An Introduction to Social Network Data Analytics," In: Aggarwal CC (eds.) Social Network Data Analytics. New York: Springer US, pp. 1–15, 2011. Available:–1–4419–8462–3_1

D. Cvetković, P. Rowlinson, S. Simić, An Introduction to the Theory of Graph Spectra. London Mathematical Society Student Texts. Cambridge University Press, 2010.

S. Günter, H. Bunke, "Self-organizing map for clustering in the graph domain," Pattern Recognition Letters, vol. 23, no. 4, pp. 405–417, 2002. Available:–8655(01)00173–8

F. Serratosa, R. Alquézar, A. Sanfeliu, "Synthesis of function described graphs and clustering of attributed graphs," International Journal of Pattern Recognition and Artificial Intelligence, vol. 16, no. 6, pp. 621–655, 2002. Available:

X. Jiang, A. Münger, H. Bunke, "An median graphs: properties, algorithms, and applications," Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol. 23, pp. 1144–1151, 2001. Available:

U. von Luxburg, "A tutorial on spectral clustering", Statistics and Computing, vol. 17(4), pp. 395–416, 2007. Available:–9033–z

S. A. Catanese, P. De Meo, E. Ferrara, G. Fiumara, A. Provetti, "Crawling facebook for social network analysis purposes," In Proceedings of the International Conference on Web Intelligence, Mining and Semantics, Sogndal, Norway, May 25–27, pp. 52, ACM, 2011.

J. Ugander, B. Karrer, L. Backstrom, C. Marlow, "The anatomy of the Facebook social graph", arXiv preprint arXiv:1111.4503, 2011.

J. W. van Dam, M. Van De Velden, "Online profiling and clustering of Facebook users," Decision Support Systems, vol. 70, pp. 60–72, 2015. Available:

S. Catanese, P. De Meo, E. Ferrara, G. Fiumara, A. Provetti, "Extraction and analysis of Facebook friendship relations," In Computational Social Networks, A. Abraham (Eds.) Springer London, 2012, pp. 291–324. Available:–1–4471–4054–2_12

M. G. Everett, S. P. Borgatti, "The centrality of groups and classes," The Journal of mathematical sociology, vol. 23, pp. 181–201, 1999. Available:

J. Scott, Social network analysis. Sage, London, 2012.

B. Pang, L. Lee, H. Rd, S. Jose, "Thumbs up? Sentiment Classification using Machine Learning Techniques," In Proceedings of the ACL-02 conference on Empirical methods in Natural Language Processing (EMNLP ’02), Philadelphia, PA, USA, July 6–7, vol. 10, pp. 79–86, 2002.

J. Akaichi, Z. Dhouioui, M. J. L. H. Pérez, "Text mining Facebook status updates for sentiment classification". In Proceedings of the 17th International Conference on System Theory, Control and Computing (ICSTCC), Sinaia, Romania, October 11–13, pp. 640–645, IEEE, 2013.

J. K. Ahkter, S. Soria, Sentiment analysis: Facebook status messages. Master's thesis, Stanford, CA, 2010.

C. Troussas, M. Virvou, K. J. Espinosa, K. Llaguno, J. Caro, "Sentiment analysis of Facebook statuses using Naive Bayes classifier for language learning". In Proceedings of the Fourth International Conference on Information, Intelligence, Systems and Applications (IISA), pp. 1–6. IEEE, 2013.

E. Ugljanin, D. Stojanović, E. Kajan, Z. Maamar, "Re-engineering of smart city's business processes based on social networks and Internet of Things," Facta Universitatis, Series: Automatic Control and Robotics, vol. 16, no. 3, pp. 275–286, 2018. Available:

A. Giachanou, F. Crestani, "Like it or not: A survey of Twitter sentiment analysis methods," ACM Computing Surveys (CSUR), vol. 49(2), no. 28, pp. 1–41, 2016. Available:

A. Ljajić, U. Marovac, "Improving Sentiment Analysis for Twitter Data by Handling Negation Rules in the Serbian Language," Computer Science and Information Systems. Available:, to be published.

S. Branković, "Napredna istraživanja komunikacije na društvenim mrežama: jedan analitički model," Časopis za komunikaciju i medije (communication and media journal), vol. 32, pp. 63–82, 2014.

L. Bojic, J.-L. Marie, S. Brankovic, "Reception and Expression Capabilities of Media Addicts in Serbia," Kultura polisa, vol. 10, no. 22, pp. 353–368, 2013.



  • There are currently no refbacks.

Print ISSN: 1820-6417
Online ISSN: 1820-6425