Branko Arsić, Ljubiša Bojić, I. Milentijevic, P. Spalevic, D. Rancic
{"title":"SYMBOLS: SOFTWARE FOR SOCIAL NETWORK ANALYSIS","authors":"Branko Arsić, Ljubiša Bojić, I. Milentijevic, P. Spalevic, D. Rancic","doi":"10.22190/FUACR1803205A","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":93645,"journal":{"name":"Facta universitatis. Series, Mechanics, automatic control and robotics","volume":"27 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Facta universitatis. Series, Mechanics, automatic control and robotics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.22190/FUACR1803205A","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
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.