Assessment of the reliability of information collected from social networks

Authors: Kharlamov N.L., Latysheva L.A.
Published in issue: #3(32)/2019
DOI: 10.18698/2541-8009-2019-3-452

Category: Informatics, Computer Engineering and Control | Chapter: Methods and Systems of Information Protection, Information Security

Keywords: social network, social graph, community highlighting, search for bots, public opinion leaders, virtual users, algorithm for detecting bots
Published: 18.03.2019

A brief review of existing methods for detecting bots, based on statistical and semantic analysis of texts, behavioral analysis and graph-theoretic approach, is presented. An example of the application of the algorithm for allocating communities to solve the accompanying problem - the search for leaders of public opinion is given. A new approach to the detection of bots, based on the analysis of communities in the graph of the nearest environment of the user, is proposed. The proposed method was tested on two samples of virtual users from the social network VKontakte: managed bots and bots manually collected by one of the users. For verification, a sample of 700 legitimate users was used.


[1] Bazenkov N.I, Gubanov D.A. Information systems for social networks analysis: a survey. Upravlenie bol’shimi sistemami: sbornik trudov [Large-Scale Systems Control], 2013, no. 41, pp. 357–394 (in Russ.).

[2] Riquelme F. Measuring user influence on Twitter: a survey. Inf. Process. Manag., 2016, vol. 52, no. 5, pp. 949–975. DOI: 10.1016/j.ipm.2016.04.003 URL: https://www.sciencedirect.com/science/article/abs/pii/S0306457316300589

[3] Ratkiewicz J., Conover M., Meiss M. et al. Detecting and tracking political abuse in social media. Proc. 5th AAAI ICWSM, 2011. URL: https://www.aaai.org/ocs/index.php/ICWSM/ICWSM11/paper/view/2850/0

[4] Tang L., Liu H. Community detection and mining in social media. Synth. Lect. Data Mining Knowl. Discov., 2010, vol. 2, no. 1, pp. 1–137. DOI: 10.2200/S00298ED1V01Y201009DMK003 URL: https://www.morganclaypool.com/doi/abs/10.2200/S00298ED1V01Y201009DMK003

[5] Gubanov D.A., Novikov D.A., Chkhartishvili A.G. Informational influence and informational control models in social networks. Problemy upravleniya, 2009, no. 5, pp. 28–35. (in Russ.). (Eng. version: Autom. Remote Control, 2011, vol. 72, no. 7, pp. 1557–1567. DOI: 10.1134/S0005117911070216 URL: https://link.springer.com/article/10.1134%2FS0005117911070216)

[6] Lyfenko N.D. Virtual users in social networks: myths and realities. Voprosy kiberbezopasnosti [Cybersecurity issues], 2014, no. 5(8), pp. 17–20 (in Russ.).

[7] Ghosh R., Surachawala T., Lerman K. Entropy-based classification of ‘retweeting’ activity on Twitter. arXiv.org: website. URL: https://arxiv.org/abs/1106.0346 (accessed: 25.01.2019).

[8] Dickerson J.P., Kagan V., Subrahmanian V.S. Using sentiment to detect bots on Twitter: are humans more opinionated than bots? Proc. ASONAM, 2014, pp 620–627. DOI: 10.1109/ASONAM.2014.6921650 URL: https://ieeexplore.ieee.org/document/6921650

[9] Wang A.H. Detecting spam bots in online social networking sites: a machine learning approach. Data and Applications Security and Privacy XXIV. Springer, 2010, pp. 335–342.

[10] Wang J., Paschalidis I.Ch. Botnet detection using social graph analysis. arXiv.org:website. URL: https://arxiv.org/abs/1503.02337 (accessed: 25.01.2019).

[11] Cao Q., Sirivianos M., Yang X., et al. Aiding the detection of fake accounts in large scale social online services. Proc. 9th USENIX Symp. NSDI 12, 2012, pp. 469–493.

[12] Dunbar R.I.M. Neocortex size as a constraint on group size in primates. J. Hum. Evol., 1992, vol. 22, no. 6, pp. 469–493. DOI: 10.1016/0047-2484(92)90081-J URL: https://www.sciencedirect.com/science/article/pii/004724849290081J

[13] Vel’ts S.V. Modelling information warfare in social networks based on game theory and dynamic Bayesian networks. Inzhenernyy zhurnal: nauka i innovatsii [Engineering Journal: Science and Innovation], 2013, no. 11(23). DOI: 10.18698/2308-6033-2013-11-991 URL: http://engjournal.ru/catalog/it/security/991.html

[14] Khondker H.H. Role of the new media in the Arab spring. Globalizations, 2011, vol. 8, no. 5, pp. 675–679. DOI: 10.1080/14747731.2011.621287 URL: https://www.tandfonline.com/doi/abs/10.1080/14747731.2011.621287

[15] Yang C., Harkreader R.Ch., Gu G. Die free or live hard? Empirical evaluation and new design for fighting evolving twitter spammers. Proc. RAID 2011. Springer, 2011, pp. 318–337.