Social networks in logistics system decision-making
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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.
Ključne reči:
social networks / information retrieval / logistics system decisions / digilabIzvor:
2nd Logistics International Conference, Belgrade, Serbia, 21 - 23 May 2015, 2015, 166-171Izdavač:
- Belgrade: University of Belgrade, Faculty of Transport and Traffic Engineering
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Institucija/grupa
IFDTTY - 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 .