https://oldena.lpnu.ua/handle/ntb/44901| Title: | Ranking the social media platform user pages using Big Data |
| Other Titles: | Ранжування сторінок користувачів платформ соціальних середовищ Інтернету засобами Big Data |
| Authors: | Мастикаш, О. Любінський, Б. Топилко, П. Пеняк, І. Mastykash, O. Liubinskyi, B. Topylko, P. Penyak, I. |
| Affiliation: | Національний університет "Львівська політехніка" Lviv Polytechnic National University |
| Bibliographic description (Ukraine): | Ranking 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. |
| Bibliographic description (International): | Ranking 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. |
| Is part of: | Mathematical Modeling and Computing, 1 (5), 2018 |
| Journal/Collection: | Mathematical Modeling and Computing |
| Issue: | 1 |
| Volume: | 5 |
| Issue Date: | 15-Jan-2018 |
| Publisher: | Lviv Politechnic Publishing House |
| Place of the edition/event: | Lviv |
| UDC: | 004.773.2 004.45 |
| Keywords: | соцiальна медiа-платформа великi данi рейтинг сторiнки оцiнка рейтингу сторiнок вiртуальна спiльнота social media platform big data page ranking measuring of page ranking virtual community |
| Number of pages: | 10 |
| Page range: | 56-65 |
| Start page: | 56 |
| End page: | 65 |
| Abstract: | Проаналiзовано 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. The 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. |
| URI: | https://ena.lpnu.ua/handle/ntb/44901 |
| Copyright owner: | © 2018 Lviv Polytechnic National University CMM IAPMM NASU © 2018 Lviv Polytechnic National University CMM IAPMM NASU |
| References (Ukraine): | [1] ElMorrC., MaretP. Virtual Community Building and the Information Society: Current and Future Directions”, IGI Global (2012). [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). [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). [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). [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). [6] Howard˙T. Design to Thrive: Creating Social Networks and Online Communities that Last. Elsevier (2015). [7] LuoQ., CuiH., ZhangB., ZhangD. Ranking social network objects. US Patent 9,081,823 (2015). [8] Papadopoulos S., KompatsiarisY. Social multimedia crawling for mining and search. Computer. 47 (5), 84–87 (2014). [9] ZuckerbergM., SittigA. Mapping relationships between members in a social network. US Patent 9,183,599 (2015). [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). |
| References (International): | [1] ElMorrC., MaretP. Virtual Community Building and the Information Society: Current and Future Directions", IGI Global (2012). [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). [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). [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). [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). [6] Howard˙T. Design to Thrive: Creating Social Networks and Online Communities that Last. Elsevier (2015). [7] LuoQ., CuiH., ZhangB., ZhangD. Ranking social network objects. US Patent 9,081,823 (2015). [8] Papadopoulos S., KompatsiarisY. Social multimedia crawling for mining and search. Computer. 47 (5), 84–87 (2014). [9] ZuckerbergM., SittigA. Mapping relationships between members in a social network. US Patent 9,183,599 (2015). [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). |
| Content type: | Article |
| Appears in Collections: | Mathematical Modeling And Computing. – 2018. – Vol. 5, No. 1 |
| File | Description | Size | Format | |
|---|---|---|---|---|
| 2018v5n1_Mastykash_O-Ranking_the_social_media_56-65.pdf | 1.5 MB | Adobe PDF | View/Open | |
| 2018v5n1_Mastykash_O-Ranking_the_social_media_56-65__COVER.png | 399.06 kB | image/png | View/Open |
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