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 . .

TY  - CONF
AU  - Arsić, Branko
AU  - Spalević, Petar
AU  - Bojić, Ljubiša
AU  - Crnišanin, Adela
PY  - 2015
UR  - http://rifdt.instifdt.bg.ac.rs/123456789/2354
AB  - Social networks, such as Facebook, Twitter and LinkedIn have been becoming very
popular during the last few years. Facebook is currently the world’s most populous “country” with
more t han 1 .3 b illion “ inhabitants”. A ccording to t he s tatistical d ata, t he u sers share their
impressions daily in the form of statuses about upcoming events and present state of affairs, their
problems, plans, novel experiences about the products, political stances, and alike. Having the
possibility to extract the information of interest from a huge amount of hand-created data about
the users’ personal affinities and their usage within logistics system, it is facilitated to meet the
customers’ needs. In this paper we present a procedure for finding and analyzing valuable
information related to the specific products, and its effect on logistics system decision-making.
Filtering is being done by already developed software for neurolinguistics social network analysis -
“Symbols”. This software offers graphical representation of statistical data for selected brands
based on the social network statuses, its implications, as well as target group demographic and
territorial structure. The results obtained point out possible increasing/decreasing demands
among separate user groups, therefore giving a factual basis for logistics changes.
PB  - Belgrade: University of Belgrade, Faculty of Transport and Traffic Engineering
C3  - 2nd Logistics International Conference, Belgrade, Serbia, 21 - 23 May 2015
T1  - Social networks in logistics system decision-making
SP  - 166
EP  - 171
UR  - https://hdl.handle.net/21.15107/rcub_rifdt_2354
ER  - 

@conference{
author = "Arsić, Branko and Spalević, Petar and Bojić, Ljubiša and Crnišanin, Adela",
year = "2015",
abstract = "Social networks, such as Facebook, Twitter and LinkedIn have been becoming very
popular during the last few years. Facebook is currently the world’s most populous “country” with
more t han 1 .3 b illion “ inhabitants”. A ccording to t he s tatistical d ata, t he u sers share their
impressions daily in the form of statuses about upcoming events and present state of affairs, their
problems, plans, novel experiences about the products, political stances, and alike. Having the
possibility to extract the information of interest from a huge amount of hand-created data about
the users’ personal affinities and their usage within logistics system, it is facilitated to meet the
customers’ needs. In this paper we present a procedure for finding and analyzing valuable
information related to the specific products, and its effect on logistics system decision-making.
Filtering is being done by already developed software for neurolinguistics social network analysis -
“Symbols”. This software offers graphical representation of statistical data for selected brands
based on the social network statuses, its implications, as well as target group demographic and
territorial structure. The results obtained point out possible increasing/decreasing demands
among separate user groups, therefore giving a factual basis for logistics changes.",
publisher = "Belgrade: University of Belgrade, Faculty of Transport and Traffic Engineering",
journal = "2nd Logistics International Conference, Belgrade, Serbia, 21 - 23 May 2015",
title = "Social networks in logistics system decision-making",
pages = "166-171",
url = "https://hdl.handle.net/21.15107/rcub_rifdt_2354"
}

Arsić, B., Spalević, P., Bojić, L.,& Crnišanin, A.. (2015). Social networks in logistics system decision-making. in 2nd Logistics International Conference, Belgrade, Serbia, 21 - 23 May 2015
Belgrade: University of Belgrade, Faculty of Transport and Traffic Engineering., 166-171.
https://hdl.handle.net/21.15107/rcub_rifdt_2354

Arsić B, Spalević P, Bojić L, Crnišanin A. Social networks in logistics system decision-making. in 2nd Logistics International Conference, Belgrade, Serbia, 21 - 23 May 2015. 2015;:166-171.
https://hdl.handle.net/21.15107/rcub_rifdt_2354 .

Arsić, Branko, Spalević, Petar, Bojić, Ljubiša, Crnišanin, Adela, "Social networks in logistics system decision-making" in 2nd Logistics International Conference, Belgrade, Serbia, 21 - 23 May 2015 (2015):166-171,
https://hdl.handle.net/21.15107/rcub_rifdt_2354 .