Abstract
With the enhancement of the usage of the Internet, various problems of social state shifted to the network. As a result, many techniques which were used by sociologists and psychologists lost their relevance. In this paper a problem of the automatic social tension detection is considered in terms of combined content, including video and static pictures with texts. We presuppose that social tension can be detected by means of particular language markers and individuals emotional states identification.
The main contribution of this paper is as follows:
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a set of language markers and emotional state markers, which allow to detect the social tension and unrest in video- and static Internet-content;
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forming of the cognitive maps which can be used as clear classifier in the field of the social tension detection.
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Acknowledgements
The reported study was funded by RFBR, grants №20–04- 60485 and 18-29-22086.
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Korovin, I., Pavlenko, A., Klimenko, A., Safronenkova, I. (2021). A Complex Cognitive-Based Technique for Social Tension Detection in the Internet. In: Silhavy, R. (eds) Artificial Intelligence in Intelligent Systems. CSOC 2021. Lecture Notes in Networks and Systems, vol 229. Springer, Cham. https://doi.org/10.1007/978-3-030-77445-5_16
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