TY  - JOUR
AU  - Arsić, Branko
AU  - Bojić, Ljubiša
AU  - Milentijević, Ivan
AU  - Spalević, Petar
AU  - Rančić, Dejan
PY  - 2018
UR  - http://rifdt.instifdt.bg.ac.rs/123456789/2348
AB  - The unique possibilities of 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 a local database and involves a module for a 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.
PB  - Niš: Univerzitet u Nišu
T2  - The Facta Universitatis, Series: Automatic Control and Robotics
T1  - Symbols: Software for Social Network Analysis
IS  - 3
VL  - 17
SP  - 205
EP  - 222
DO  - 10.22190/FUACR1803205A
ER  - 

@article{
author = "Arsić, Branko and Bojić, Ljubiša and Milentijević, Ivan and Spalević, Petar and Rančić, Dejan",
year = "2018",
abstract = "The unique possibilities of 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 a local database and involves a module for a 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.",
publisher = "Niš: Univerzitet u Nišu",
journal = "The Facta Universitatis, Series: Automatic Control and Robotics",
title = "Symbols: Software for Social Network Analysis",
number = "3",
volume = "17",
pages = "205-222",
doi = "10.22190/FUACR1803205A"
}

Arsić, B., Bojić, L., Milentijević, I., Spalević, P.,& Rančić, D.. (2018). Symbols: Software for Social Network Analysis. in The Facta Universitatis, Series: Automatic Control and Robotics
Niš: Univerzitet u Nišu., 17(3), 205-222.
https://doi.org/10.22190/FUACR1803205A

Arsić B, Bojić L, Milentijević I, Spalević P, Rančić D. Symbols: Software for Social Network Analysis. in The Facta Universitatis, Series: Automatic Control and Robotics. 2018;17(3):205-222.
doi:10.22190/FUACR1803205A .

Arsić, Branko, Bojić, Ljubiša, Milentijević, Ivan, Spalević, Petar, Rančić, Dejan, "Symbols: Software for Social Network Analysis" in The Facta Universitatis, Series: Automatic Control and Robotics, 17, no. 3 (2018):205-222,
https://doi.org/10.22190/FUACR1803205A . .