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A Technique to Infer Symbolic and Socio-symbolic Micro Patterns

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Networks in the Global World V (NetGloW 2020)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 181))

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Abstract

The interplay between symbolic and social structures in groups is often analysed at the whole-network level of their semantic and socio-semantic networks, e.g. via comparison of graph distributions, multidimensional scaling, or QAP correlations. Meanwhile, the interplay between the symbolic and the social operates through the usage of signs (e.g. words) and their associations by interacting individuals. Hence, structural properties of the whole network can be explained by analysing specific instances of symbolic and socio-symbolic micro patterns – elementary configurations linking signs, and signs and individuals – occurring in practical contexts. This paper introduces a technique and a customisable pattern retriever tool (an R script) to (1) programme socio-symbolic patterns of theoretical importance, (2) use them as ‘search terms’ to query network data, (3) extract from the data instances of the patterns and text quotes corresponding to them, (4) store and represent these instances and quotes in a form convenient for their subsequent qualitative analysis – to uncover the contextual meanings of the patterns. We illustrate the proposed technique with an analysis of a mixed dataset on the interplay between expert and local symbolic structures in the context of social structures of two local groups engaged in flood risk management in 2019 England.

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Notes

  1. 1.

    Note that to trace symbolic patterns in the most accurate way, the ‘independent’ symbolic structure has to be captured at least at a single point in time, and the ‘dependent’ symbolic structure has to be captured at least at two points in time. This way, it is possible to trace changes in appearance of signs and sign associations in the ‘dependent’ symbolic structure at t2 compared to the same symbolic structure at t1 and to the ‘independent’ symbolic structure at t1. While longitudinal data are desirable, cross-sectional data can also be used.

  2. 2.

    Considering unshared signs and associations between them allows us to trace their introduction into group symbolic structure presupposed by several socio-symbolic patterns.

  3. 3.

    The semantic networks were mapped based on co-occurrence of signs within the window of 9 (i.e. separated by 7 signs) in the texts. Signs from a customized stop list as well as those with part of speech other than noun, verb, or adjective, were not included in the networks. Semantic networks for local symbolic structures contain signs and their associations used at least two times. Semantic networks for expert symbolic structures contain signs and their associations used at least eight times.

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Acknowledgements

This work was supported by the Russian Science Foundation (grant 19-18-00394 ‘Creation of knowledge on ecological hazards in Russian and European local communities,’ 2019–ongoing). The authors would like to thank two anonymous reviewers for providing valuable comments on an earlier draft of the paper.

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Authors and Affiliations

  1. Centre for German and European Studies, St. Petersburg State University, St. Petersburg, Russia

    Artem Antonyuk, Kseniia Puzyreva, Darkhan Medeuov & Nikita Basov

  2. Faculty of Sociology, St. Petersburg State University, St. Petersburg, Russia

    Artem Antonyuk & Nikita Basov

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  1. Artem Antonyuk
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Correspondence to Artem Antonyuk .

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  1. St. Petersburg University, Centre for German and European Studies, St. Petersburg, Russia

    Artem Antonyuk

  2. St. Petersburg University, Centre for German and European Studies, St. Petersburg, Russia

    Nikita Basov

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Antonyuk, A., Puzyreva, K., Medeuov, D., Basov, N. (2021). A Technique to Infer Symbolic and Socio-symbolic Micro Patterns. In: Antonyuk, A., Basov, N. (eds) Networks in the Global World V. NetGloW 2020. Lecture Notes in Networks and Systems, vol 181. Springer, Cham. https://doi.org/10.1007/978-3-030-64877-0_7

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