Development of the Hierarchical Model of Internet Communities’ Integration Index
DOI:
https://doi.org/10.22213/2410-9304-2019-4-78-87Keywords:
internet community, hierarchy analysis, system analysis, T. Saati method, automatic control, analytic hierarchy processAbstract
The complexity of the problem lies in the multilevel Internet sociality. In fact, it stands out the virtual sociality - the autonomous developing in its laws world of Internet communities, the Internet economy, etc., which can be described as e-sociality. But along with this level there is a level that can only be understood as a segment embedded in the functioning of real sociality; it is a level that remains in real sociality, but transfers a part of its interactions - for example, communication - into the world of the Internet. This is the level characterized by offline to online transitions and back. The mentioned above hierarchical model describes a system of indicators for online communities.
The paper considers a three-level model of the integration indicator. It presents the influence of forces (level I1), system actors (level I2), actor indicators (level I3) that affect the integration process (level I0). As a result of the study, it was found that the minimum necessary parameters for obtaining an objective and reliable degree of integration of the mobilization online community include (in the decreasing order of importance): sociocultural aspects, goals and values of the group, the amount of internal communications and mobilization potential. The selection of parameters is made based on the Pareto principle. The actors that act within each force can be ranked by importance as follows. “The community itself”: level of cohesion, volume of internal communications, mobilization potential, dynamics of volume, qualitative composition of the core of the group, level of trust, modularity, volume of external communications, size of the community, and age of the group. “Community Dynamics”: goals and values of the group, features of the topics of publications, features of online and offline activities, features of leadership and participants. “External factors”: sociocultural aspects, features of the software and hardware platform, political and legal aspects, financial aspects.
References
Стёпин В. С. Постнеклассическая рациональность и информационное общество // Философия искусственного интеллекта : труды Всероссийской междисциплинарной конференции, посвященной шестидесятилетию исследования искусственного интеллекта, 17-18 марта 2016 года, философский факультет МГУ им. М. В. Ломоносова, г. Москва / под ред. В. А. Лекторского, Д. И. Дубровского, А. Ю. Алексеева. М. : ИИнтелл, 2017. С. 59–69.
Glaser, B., Strauss, A., The Discovery of Grounded Theory: Strategies for Qualitative Research // New Brunswick-London: Transaction Publishers, 2009. 271 p.
Смирнов С. В. Инструментальное исследование дружеских связей в социальных сетях на наличие гендерных зависимостей // Социально-экономическое управление: теория и практика. 2018. № 4 (35). С. 202–207.
Saaty T. L., The Analytic Hierarchy Process: Planning, Priority Setting, Resource Allocation (Decision Making Series). New York: McGraw-Hill. 1980. 287 p.
Saaty, R.W., 1987. The Analityc Hierarchy Process – What it is and How it is Used. Mathematical Modelling. Vol. 9(3-5), pp. 161-176.
Quyen, Nlhtt, Nguyen, P. T., Huynh, V. D. B. A hybrid multi criteria decision analysis for engineering project manager evaluation // International Journal of Advanced and Applied Sciences. 2017. Vol. 4. No. 4. Pp. 49-52.
Lambert, J.M. The Extended Analytic Hierarchy Decision Method // Mathematical and Computer Modelling, 1991. Vol. 15 (11), pp. 141-151.
Ho, W., Ma, X. The State-of-the-art Integrations and Applications of the Analytic Hierarchy Process // European Journal of Operational Research. In Press. 2017. https://doi.org/10.1016/j.ejor.2017.09.007 (дата обращения: 10.10.2018).
Ivanco, M., Hou, G., Michaeli, J. Sensitivity Analysis Method to Address User Disparities in the Analytic Hierarchy Process // Expert Systems with Applications. 2017.Volume 90. с. 111–126.
Alberto A. Aguilar-Lasserre, Marco A. Bautista Bautista, Antonin Ponsich, Magno A. González Huerta, An AHP-based decision-making tool for the solution of multiproduct batch plant design problem under imprecise demand // Computers & Operations Research. 2009. Volume 36, Issue 3. Pp. 711-736, ISSN 0305-0548, https://doi.org/10.1016/j.cor.2007.10.029 (дата обращения: 10.10.2018).
Alessio Ishizaka, Ashraf Labib, Review of the main developments in the analytic hierarchy process // Expert Systems with Applications. 2011, № 38. Pp. 14336 – 14345, http://dx.doi.org/10.1016/j.eswa.2011.04.143 (дата обращения: 10.10.2018).
Жиров Д. К. АСУ процессом механоактивации многокомпонентных материалов и ее системный анализ по критерию качества конечного продукта // Вестник ИжГТУ. 2011. № 4 (52). С. 132–135.
Благодатский Г. А. Создание математической модели анализа структуры аккредитационных показателей вуза с применением метода анализа иерархий // Вестник ИжГТУ. 2010. № 2 (46). С. 115–118.
Переведенцев Д. И. Моделирование системы нечеткого логического вывода оценки наукоемких проектов // Автоматизация процессов управления. 2017. № 2 (48). С. 82–89.
Горохов М. М. Программно-инструментальное средство оценки тренированности спортсменов высших квалификаций // Вестник ИжГТУ имени М. Т. Калашникова. 2016. № 2 (70). С. 87–90.
Благодатский Г. А. Программно-инструментальные средства повышения эффективности внутренних бизнес-процессов предприятий. Ижевск : Издательство ИжГТУ имени М. Т. Калашникова, 2015. 188 с.
Калиткин Н. Н. Численные методы. М. : Наука, 1990. С. 190–191.
