Ranking the social media platform user pages using Big Data

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dc.citation.epage65
dc.citation.issue1
dc.citation.journalTitleMathematical Modeling and Computing
dc.citation.spage56
dc.citation.volume5
dc.contributor.affiliationНаціональний університет "Львівська політехніка"
dc.contributor.affiliationLviv Polytechnic National University
dc.contributor.authorМастикаш, О.
dc.contributor.authorЛюбінський, Б.
dc.contributor.authorТопилко, П.
dc.contributor.authorПеняк, І.
dc.contributor.authorMastykash, O.
dc.contributor.authorLiubinskyi, B.
dc.contributor.authorTopylko, P.
dc.contributor.authorPenyak, I.
dc.coverage.placenameLviv
dc.date.accessioned2019-05-07T14:02:01Z
dc.date.available2019-05-07T14:02:01Z
dc.date.created2018-01-15
dc.date.issued2018-01-15
dc.description.abstractПроаналiзовано платформи соцiальних середовищ Iнтернету залежно вiд їхнього кон- тенту. Здiйснено класифiкацiю, яка дала змогу виокремити групи за певними озна- ками. Для ранжування сторiнок користувачiв вiртуальних спiльнот запропоновано використовувати модифiкований алгоритм PageRank. Побудовано пiдхiд, який осно- вується на використаннi лексичного аналiзу, алгоритму ранжування та упорядкуван- ня даних з використанням парадигми MapReduce. Реалiзовано програмне забезпечен- ня для ранжування сторiнок користувачiв. Проаналiзовано результати оброблених даних та формування PageRank користувачiв платформи.
dc.description.abstractThe platforms of the social media of the Internet, depending on their content have been analyzed in the paper. The classification that allows selecting groups by specific one’s signs has been made. To rank the pages of users of virtual communities, it is suggested to use a modified PageRank algorithm. An approach based on the use of lexical analysis and algorithm for ranking and organizing data using the MapReduce paradigm is developed. Using the developed approach and the appropriate algorithm, the software for ranking user pages has been implemented. The results of processed data and the formation of users’ PageRank of the platform has been analyzed.
dc.format.extent56-65
dc.format.pages10
dc.identifier.citationRanking the social media platform user pages using Big Data / O. Mastykash, B. Liubinskyi, P. Topylko, I. Penyak // Mathematical Modeling and Computing. — Lviv : Lviv Politechnic Publishing House, 2018. — Vol 5. — No 1. — P. 56–65.
dc.identifier.citationenRanking the social media platform user pages using Big Data / O. Mastykash, B. Liubinskyi, P. Topylko, I. Penyak // Mathematical Modeling and Computing. — Lviv : Lviv Politechnic Publishing House, 2018. — Vol 5. — No 1. — P. 56–65.
dc.identifier.urihttps://ena.lpnu.ua/handle/ntb/44901
dc.language.isoen
dc.publisherLviv Politechnic Publishing House
dc.relation.ispartofMathematical Modeling and Computing, 1 (5), 2018
dc.relation.references[1] ElMorrC., MaretP. Virtual Community Building and the Information Society: Current and Future Directions”, IGI Global (2012).
dc.relation.references[2] TrachO., Fedushko S. Development of Software Complex of Virtual Community Life Cycle Organization. International Journal of Computer Science and Business Informatics. 17 (1), 1–11 (2017).
dc.relation.references[3] TrachO., PeleshchyshynA. Development of directions tasks indicators of virtual community life cycle organization. Proceedings of the 12th International Scientific and Technical Conference on Computer Sciences and Information Technologies, CSIT 2017. 127–130 (2017).
dc.relation.references[4] MastykashO., PeleshchyshynA. Analysis of the Methods of Data Collection on Social Networks. Proceedings of the 12th International Scientific and Technical Conference on Computer Sciences and Information Technologies, CSIT 2017. 175–178 (2017).
dc.relation.references[5] ShakhovskaN., VovkO., HaskoR., KryvenchukY. The Method of Big Data Processing for Distance Educational System. In: ShakhovskaN., StepashkoV. (eds) Advances in Intelligent Systems and Computing II. CSIT 2017. Advances in Intelligent Systems and Computing. 689, 461–473 (2018).
dc.relation.references[6] Howard˙T. Design to Thrive: Creating Social Networks and Online Communities that Last. Elsevier (2015).
dc.relation.references[7] LuoQ., CuiH., ZhangB., ZhangD. Ranking social network objects. US Patent 9,081,823 (2015).
dc.relation.references[8] Papadopoulos S., KompatsiarisY. Social multimedia crawling for mining and search. Computer. 47 (5), 84–87 (2014).
dc.relation.references[9] ZuckerbergM., SittigA. Mapping relationships between members in a social network. US Patent 9,183,599 (2015).
dc.relation.references[10] LuX., Liang F., WangB., Zha L., Xu Z. DataMPI: extending MPI to hadoop-like big data computing. In: Parallel and Distributed Processing Symposium, 2014 IEEE 28th International. IEEE, 829–838 (2014).
dc.relation.referencesen[1] ElMorrC., MaretP. Virtual Community Building and the Information Society: Current and Future Directions", IGI Global (2012).
dc.relation.referencesen[2] TrachO., Fedushko S. Development of Software Complex of Virtual Community Life Cycle Organization. International Journal of Computer Science and Business Informatics. 17 (1), 1–11 (2017).
dc.relation.referencesen[3] TrachO., PeleshchyshynA. Development of directions tasks indicators of virtual community life cycle organization. Proceedings of the 12th International Scientific and Technical Conference on Computer Sciences and Information Technologies, CSIT 2017. 127–130 (2017).
dc.relation.referencesen[4] MastykashO., PeleshchyshynA. Analysis of the Methods of Data Collection on Social Networks. Proceedings of the 12th International Scientific and Technical Conference on Computer Sciences and Information Technologies, CSIT 2017. 175–178 (2017).
dc.relation.referencesen[5] ShakhovskaN., VovkO., HaskoR., KryvenchukY. The Method of Big Data Processing for Distance Educational System. In: ShakhovskaN., StepashkoV. (eds) Advances in Intelligent Systems and Computing II. CSIT 2017. Advances in Intelligent Systems and Computing. 689, 461–473 (2018).
dc.relation.referencesen[6] Howard˙T. Design to Thrive: Creating Social Networks and Online Communities that Last. Elsevier (2015).
dc.relation.referencesen[7] LuoQ., CuiH., ZhangB., ZhangD. Ranking social network objects. US Patent 9,081,823 (2015).
dc.relation.referencesen[8] Papadopoulos S., KompatsiarisY. Social multimedia crawling for mining and search. Computer. 47 (5), 84–87 (2014).
dc.relation.referencesen[9] ZuckerbergM., SittigA. Mapping relationships between members in a social network. US Patent 9,183,599 (2015).
dc.relation.referencesen[10] LuX., Liang F., WangB., Zha L., Xu Z. DataMPI: extending MPI to hadoop-like big data computing. In: Parallel and Distributed Processing Symposium, 2014 IEEE 28th International. IEEE, 829–838 (2014).
dc.rights.holder© 2018 Lviv Polytechnic National University CMM IAPMM NASU
dc.rights.holder© 2018 Lviv Polytechnic National University CMM IAPMM NASU
dc.subjectсоцiальна медiа-платформа
dc.subjectвеликi данi
dc.subjectрейтинг сторiнки
dc.subjectоцiнка рейтингу сторiнок
dc.subjectвiртуальна спiльнота
dc.subjectsocial media platform
dc.subjectbig data
dc.subjectpage ranking
dc.subjectmeasuring of page ranking
dc.subjectvirtual community
dc.subject.udc004.773.2
dc.subject.udc004.45
dc.titleRanking the social media platform user pages using Big Data
dc.title.alternativeРанжування сторінок користувачів платформ соціальних середовищ Інтернету засобами Big Data
dc.typeArticle

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Mathematical Modeling And Computing. – 2018. – Vol. 5, No. 1