Corporate system of network information resources monitoring based on multi-agent approach
In article the multi-agent model of distribution of the information messages containing references to information resources on the Internet is provided. Characteristics of growth of quantity of special retweets of the chosen messages were analyzed. Distribution of retweets in this case, as well as in model, corresponded to standard distribution of Weibull. Stages of corporate system of network information monitoring resources creation which structure is determined by references in microblogs are described. As a result of the described researches the multi-agent model of distribution of the information messages containing references to information resources in the Internet is constructed. Results of modeling are checked by research of a real network of microblogs Twitter. The found regularities can be used when forming databases of information and analytical systems, when studying anomalies in statistics of references to separate information materials, and respectively, and in identification of information transactions, artificially supported information campaigns. The provided approach has such advantages: Efficiency – the information message is included in the database of information and analytical system in real time; Spanning of the principal information materials on a subject; A possibility of ranging of information materials proceeding from interests of users of social networks; Compactness of databases, convenience of access for ultimate users. Predictability of volumes of databases, dynamics of their filling; Technological compatibility with the existing information and analytical systems and systems of content monitoring; Possibility of identification of information campaigns, operations.
Full Text:PDF (Русский)
D.V. Lande, A.A. Snarskii, and I.V. Bezsudnov, Internetika: Navigation in complex networks: models and algorithms.Moscow, Russia: Librokom (Editorial URSS), 2009.
R. Li, K. Lei, R. Khadiwala, and K. Chang, “TEDAS: A Twitter-based Event Detection and Analysis System”, in Proc. IEEE 28th Int. Conf. Data Engineering (ICDE), Washington, USA, 2012, pp. 1273-1276. doi: 10.1109/ICDE.2012.125.
A.G. Dodonov, D.V. Lande, V.V. Prishchepa, and V.G. Putiatin, Opponent intelligence in computer networks. Kyiv, Ukraine: IIR NAS of Ukraine, 2013.
J. Woo, and H. Chen, “Epidemic model for information diffusion in web forums: experiments in marketing exchange and political dialog”, Springerplus, no. 22, pp. 5-66, 2016. doi: 10.1186/s40064-016-1675-x.
K. Lerman, “Information Is Not a Virus, and Other Consequences of Human Cognitive Limits”, Future Internet, vol. 8, iss. 2, pp. 1-11, 2016. doi: 10.3390/fi8020021.
D.V. Lande, A.N. Graivoronskaia, and B.A. Berezin, “Multi-agent model of information dissemination in social networks”, Registration, storage and processing, т. 18. № 1, pp. 70-77, 2016.
A.G. Dodonov, D.V. Lande, and V.A. Dodonov, “Information Operations Recognition: multiagent approach”, in Proc. IVth Int. Conf. Open Semantic Technology for Intelligent Systems (OSTIS-2016), Minsk, 2016, pp. 253-256.
This work is licensed under a Creative Commons Attribution 4.0 International License.
ISSN 2411-1031 (Print), ISSN 2518-1033 (Online)