Linguistic means to expose the human rights aspect of citizens’ surveillance


  • Elena S. Danilova Belgorod State University, 14 Studencheskaya St. Belgorod 308015 Russia
  • Elena V. Pupynina Belgorod State University, 14 Studencheskaya St. Belgorod 308015 Russia
  • Yulia A. Drygina Belgorod State University, 14 Studencheskaya St. Belgorod 308015 Russia
  • Vladimir S. Pugach Belgorod State University, 14 Studencheskaya St. Belgorod 308015 Russia
  • Oxana V. Markelova Belgorod State University, 14 Studencheskaya St. Belgorod 308015 Russia


criticism, extra-linguistic reality, human rights, impartial judgement, linguistic means, prejudiced attitudes


The paper focuses on English lexemes used in mass media publications about a new security development. The use of artificial intelligence for facial recognition and enhanced surveillance of citizens pose several ethical issues discussed in major broadsheet newspapers. Studies into the evaluation as a cognitive category have been used as the theoretical basis of the research. The contexts revealed lexical units displaying evaluation of surveillance and human rights issues. The lexemes fall within three semantic groups. Negative connotations are connected with personal experience or associations, as well as with human rights breaches, while advantages tend to be described with verbs denoting purpose. The use of AI is a highly controversial issue that deserves cross-disciplinary consideration.


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Alston, P. (2017). The populist challenge to human rights. Journal of Human Rights Practice, 9(1), 1-15.

Apodaca, C. (2007). The whole world could be watching: Human rights and the media. Journal of Human Rights, 6(2), 147-164.

Bates, R. (2004). A critical analysis of evaluation practice: the Kirkpatrick model and the principle of beneficence. Evaluation and program planning, 27(3), 341-347.

Bauer, J. C. (2017). Statistical Analysis for Decision Makers in Healthcare: Understanding and Evaluating Critical Information in Changing Times. CRC Press.

Berg, C. (2018). The Classical Liberal Case for Privacy in a World of Surveillance and Technological Change. Springer.

Castelli, L., & Tomelleri, S. (2008). Contextual effects on prejudiced attitudes: When the presence of others leads to more egalitarian responses. Journal of Experimental Social Psychology, 44(3), 679-686.

Chekulai, I.V., & Prokhorova, O.N. (2010). The principles of evaluative actualization as mental and speech variants of the principles of value quasi-categorization and their characteristic features. Questions of journalism, pedagogy, linguistics , 7 (18 (89)).

Correia da Silva Andrade, L. P., Will, M., Breda Mascarenhas, L. A., Campos da Silva, R., & de Oliveira Gomes, J. (2015). Evaluation of Technological Trends and Demands of the Manufacturing Industry to a Center of R & D & I. Journal of technology management & innovation, 10(3), 104-119.

Dodd, V. (2020). Met police to begin using live facial recognition cameras in London. The Guardian, 24, 2020.

Domaneschi, F. (2016). Introduction: Presuppositions philosophy, linguistics and psychology. Topoi, 35(1), 5-8.

Drew, N., Funk, M., Tang, S., Lamichhane, J., Chávez, E., Katontoka, S., ... & Saraceno, B. (2011). Human rights violations of people with mental and psychosocial disabilities: an unresolved global crisis. The Lancet, 378(9803), 1664-1675.

García-Díaz, N., Verduzo-Ramirez, A., Garcia-Virgen, J., & Muñoz, L. (2016). Applying Absolute Residuals as Evaluation Criterion for Estimating the Development Time of Software Projects by Means of a Neuro-Fuzzy Approach.

Gill, P. (2009). Security Intelligence and Human Rights: Illuminating the ‘Heart of Darkness’?. Intelligence and National Security, 24(1), 78-102.

Glassman, L. H., Weierich, M. R., Hooley, J. M., Deliberto, T. L., & Nock, M. K. (2007). Child maltreatment, non-suicidal self-injury, and the mediating role of self-criticism. Behaviour research and therapy, 45(10), 2483-2490.

Greene, A. (2017). The Human Rights Act in a Culture of Control. The Future of Human Rights in the UK (Cambridge Scholars Press, 2017).

La Fors-Owczynik, K. (2016). Monitoring migrants or making migrants ‘misfit’? Data protection and human rights perspectives on Dutch identity management practices regarding migrants. Computer Law & Security Review, 32(3), 433-449.

Lieber, R., & Štekauer, P. (Eds.). (2014). The Oxford handbook of derivational morphology. Oxford University Press, USA.

Lomas, N. (2020). London’s Met Police switches on live facial recognition, flying in face of human rights concerns. Bay Area, TechCrunch – Startup and Technology News. (in press).

Lundberg, F. C. (2006). Evaluation: definitions, methods and models. ITPS, Östersund, Sweden.

Nelson, P. J. (2007). Human rights, the Millennium Development Goals, and the future of development cooperation. World development, 35(12), 2041-2055.

Peterson, E. R., Rubie-Davies, C., Osborne, D., & Sibley, C. (2016). Teachers' explicit expectations and implicit prejudiced attitudes to educational achievement: Relations with student achievement and the ethnic achievement gap. Learning and Instruction, 42, 123-140.

Sabri, A. (2017, August). A proposed social web of things business framework. In 2017 International Conference on Engineering and Technology (ICET) (pp. 1-5). IEEE.

Satariano, A. (2020). London police are taking surveillance to a whole new level. The New York Times. https://www. nytimes. com/2020/01/24/business/london-police-facial-recognition. html.

Sinclair, S., Dunn, E., & Lowery, B. (2005). The relationship between parental racial attitudes and children’s implicit prejudice. Journal of Experimental Social Psychology, 41(3), 283-289.

Solum, L. B. (2017). Triangulating Public Meaning: Corpus Linguistics, Immersion, and the Constitutional Record. BYU L. Rev., 1621.

Song, A. M., & Soliman, A. (2019). Situating human rights in the context of fishing rights–Contributions and contradictions. Marine Policy, 103, 19-26.

Tagay, A. A., & Ballesteros, L. I. (2016). Ilocano familism in the chichacorn industry in Paoay, Ilocos Norte, Philippines. Humanities & Social Sciences Reviews, 4(1), 27-40.

Terrizzi Jr, J. A., Shook, N. J., & Ventis, W. L. (2010). Disgust: A predictor of social conservatism and prejudicial attitudes toward homosexuals. Personality and individual differences, 49(6), 587-592.

Valentino-DeVries, J. (2020). How the police use facial recognition, and where it falls short. New York Times, 12.

Vedung, E. (2017). Public policy and program evaluation. Routledge.

Venable, J., Pries-Heje, J., & Baskerville, R. (2016). FEDS: a framework for evaluation in design science research. European journal of information systems, 25(1), 77-89.

Vincent, S. (2019). History Shows Why Police Use of Facial Recognition Tech Can Threaten Rights. New York: Human Rights Watch. (in press).

Xu, D. (2016). Speech community theory and the language/dialect debate. Journal of Asian Pacific Communication, 26(1), 8-31.

Zuo, K. J., Saun, T. J., & Forrest, C. R. (2019). Facial recognition technology: a primer for plastic surgeons. Plastic and reconstructive surgery, 143(6), 1298e-1306e.

Zysset, A. (2016). Searching for the Legitimacy of the European Court of Human Rights: The Neglected Role of ‘Democratic Society’. Global constitutionalism, 5(1), 16-47.



How to Cite

Danilova, E. S., Pupynina, E. V., Drygina, Y. A., Pugach, V. S., & Markelova, O. V. (2021). Linguistic means to expose the human rights aspect of citizens’ surveillance. Linguistics and Culture Review, 5(S1), 37-45.



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