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Information Technology and Management Science

The Journal of Riga Technical University

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2255-9094
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The Analysis and Modelling of Social Networks: Leader Identification and Information Dissemination

Aleksejs Cumiks / Andrejs Romanovs
Published Online: 2013-01-31 | DOI: https://doi.org/10.2478/v10313-012-0017-4

Abstract

Individuals, who have more connections with others in the social network, can have more chances to influence others. Therefore, this study aims to identify groups of users with maximum joint influential power in order to help companies to conduct online marketing and reputation management. The method proposed in this study can be used to identify influential groups, on the basis of data from SNS. The proposed method will allow building a social network model, which will be used to simulate different scenarios in order to predict the speed of information dissemination.

Autoru pētījums koncentrējas uz sociālo tīklu analīzi, līderu noteikšanu un grupu izveidošanu ap tiem. Pievērsta uzmanība arī vispārējām matemātiskajām sistēmām, lai modelētu grupu, un izpētītas sociālā tīkla vizualizācijas metodes. Sociālo tīklu modelēšanā tiek izmantotas diagrammas, lai aprakstītu saites, kas pārstāv attiecības vai plūsmas starp entītijām. Dažādos pētījumos indivīdi pārsvarā ir uzskatīti kā atsevišķi elementi, bet grupas tiek izveidotas vairāku indivīdu mijiedarbības procesā. Šī pētījuma mērķis ir identificēt lietotāju grupas ar maksimālu kopējo ietekmes spēku, lai palīdzētu uzņēmumiem veiksmīgi īstenot tiešsaistes mārketingu un reputācijas vadību. Šā pētījuma laikā tika izstrādāta metode, kuru var izmantot, lai noteiktu ietekmīgākās grupas, pamatojoties uz datiem no sociālajiem tīkliem. Metode sastāv no trīs posmiem: datu vākšana, ietekmes tīkla izveidošana, mērķa grupu identificēšana. Autori plāno izstrādāt sociālo tīkla modeli vienam no finanšu nozares pārstāvjiem, izmantojot piedāvāto metodi. Izmantojot šo modeli, tiks modelēti dažādi scenāriji, piemēram, veicinot jaunu produktu vai konkurentu negatīvu reklāmu, lai prognozētu informācijas izplatīšanas ātrumu un samazinātu reakcijas laiku. Turpmākie pētījumi tiks vērsti uz dažām interesantām jaunām metodēm, izmantojot vispārinātus pasākumus grupu identificēšanai, kas maksimizē attiecīgo centralitāti (grāds, tuvība utt.), lai optimizētu grupas "efektivitāti", vai lai identificētu grupu parādīšanos tīklā. Turklāt ir nepieciešams turpināt darbu, kas ir saistīts ar ietekmes izplatīšanos sociālajā tīklā.

Исследование авторов сосредоточено на анализе социальных сетей, выявлении лидеров и создании групп вокруг них. Также уделено внимание общим математическим системам для моделирования групп, и рассмотрены методы визуализации социальных сетей. В частности, в моделировании социальной сети диаграммы используются для описания связей, которые представляют собой отношения между субъектами. В различных исследованиях индивиды в основном указаны в качестве отдельных элементов, а группы формируются из нескольких индивидов в процессе взаимодействия. Это исследование направлено на выявление групп пользователей с максимальной совместной силой влияния с целью помочь компаниям успешно проводить онлайн-маркетинг и управление репутацией. Во время данного исследования был разработан метод, который может быть использован для идентификации влиятельных групп на основе данных из социальных сетей. Метод состоит из трех этапов: сбор данных, создание сети влияния, выявление целевых групп. Авторы планируют разработать модель социальной сети для одного из представителей финансовой индустрии, используя разработанный в этом исследовании метод. Используя эту модель, будут промоделированы различные сценарии, такие как продвижение нового продукта или негативная реклама конкурентов с целью предсказать скорость распространения информации и сократить время реакции на возникшие инциденты. Дальнейшие исследования будут направлены на интересные новые методы с использованием обобщенных для поиска групп, которые максимизируют данную централизованность (степень, близость и т.д.), чтобы оптимизировать "эффективность" группы, или для выявления возникающих в сети групп. Кроме того, необходимо продолжить работу, которая связана с распространением влияния в социальных сетях.

Keywords : social network; modelling; social network visualization; pretopology; leader identification

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About the article

Aleksejs Cumiks

Aleksejs Cumiks is a master student at the Information Technology Institute, Riga Technical University (Latvia). He received his Bachelor degree in Information Technology from Riga Technical University in 2011. His research interests include electronic commerce and social networks. Since 2011 he has been working as a Research Assistant at the Department of Modelling and Simulation, Riga Technical University (Latvia). Since May 2012, A. Cumiks has been working as an Application Specialist at JSC Itella Information (Latvia). He has worked as a Web Design Project Manager at Ltd. Artcom IT for 3 years. A. Cumiks is a member of IEEE and Society for Modelling & Simulation International

Andrejs Romanovs

Andrejs Romanovs, Dr.sc.ing, Associate Professor and Senior Researcher at the Information Technology Institute, Riga Technical University. He has 25 years of professional experience in teaching postgraduate courses at RTU and developing more than 50 industrial information systems as an IT project manager. His professional interests include modelling and design of management information systems, information systems for healthcare, IT security and risk management, IT governance, integrated information technologies in business, as well as education in these areas. A. Romanovs is a senior member of the IEEE and LSS, Council Member of RTU ITI. He is the author of 2 textbooks and more than 30 papers in scientific journals and conference proceedings in the field of Information Technology. He also participated in 25 international scientific conferences, as well as in 7 national and European-level scientific technical projects


Published Online: 2013-01-31

Published in Print: 2012-12-01


Citation Information: Information Technology and Management Science, Volume 15, Issue 1, Pages 127–133, ISSN (Online) 2255-9094, ISSN (Print) 2255-9086, DOI: https://doi.org/10.2478/v10313-012-0017-4.

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