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Social Profiles - Methods of Solving Socio-Economic Problems Using Digital Technologies and Big Data

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Digital Transformation and Global Society (DTGS 2018)

Abstract

One of the research directions of Internet public data is the social profiling task. Various analytical tools and technologies are used to quickly process large arrays of heterogeneous data within this task. The result is a social profile or a set of profiles. It represents value in various socio-economic spheres.

This article offers practical examples of social profiles application in various socio-economic tasks. A survey of existing works on social profiling task has been reviewed. There are suggestions of using social profiles built by Big Data technologies in the future of Russia and the world.

This work is carried out with the support of RFBR grant №18-07-00408 in a research project named “Fundamental theoretical bases development for self-adaptation of applied software systems”.

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References

  1. Findface – Innovative service for people search by photo (2018). https://findface.ru

  2. Google Analytics Solutions - Marketing Analytics & Measurement (2018). https://www.google.com/analytics/

  3. Graph theory and social networks. Eggheado: Science (2014). https://medium.com/eggheado-science/778c92d20cea

  4. Social Computing - Microsoft Research (2018). https://www.microsoft.com/en-us/research/group/social-computing/

  5. Usalytics Careers, Funding, and Management Team | AngelList (2014). https://angel.co/usalytics

  6. Bakkar, N., Kovalik, T., Lorenzini, I.: Artificial intelligence in neurodegenerative disease research: use of IBM Watson to identify additional RNA-binding proteins altered in amyotrophic lateral sclerosis. Acta Neuropathol. 135(2), 227–247 (2018). https://doi.org/10.1007/s00401-017-1785-8

    Article  Google Scholar 

  7. Chin D., Wright W.: Social media sources for personality profiling. In: UMAP 2014 Extended Proceedings, EMPIRE 2014: Emotions and Personality in Personalized Services, pp. 79–85 (2014). http://ceur-ws.org/Vol-1181/empire2014_proceedings.pdf

  8. Eskes, P., Spruit, M., Brinkkemper, S., Vorstman, J., Kas, M.J.: The sociability score: app-based social profiling from a healthcare perspective. Comput. Hum. Behav. 59, 39–48 (2016). https://doi.org/10.1016/j.chb.2016.01.024

    Article  Google Scholar 

  9. Izmestyeva, E.: 12 tools for social media monitoring and analytics (2014). https://te-st.ru/tools/tools-monitoring-and-analysis-of-social-media/

  10. Kaczmarek, L., et al.: Smile intensity in social networking profile photographs is related to greater scientific achievements. J. Posit. Psychol. 13, 435–439 (2017). https://doi.org/10.1080/17439760.2017.1326519

    Article  Google Scholar 

  11. Kristjansson, A.L., Mann, M.J., Smith, M.L.: Social profile of middle school-aged adolescents who use electronic cigarettes: implications for primary prevention. Prev. Sci. 19, 1–8 (2017). https://doi.org/10.1007/s11121-017-0825-x

    Article  Google Scholar 

  12. Kwon, D., Park, S., Ryu, J.-T.: A study on big data thinking of the internet of things-based smart-connected car in conjunction with controller area network bus and 4G-long term evolution. Symmetry 9, 152. (2017). https://doi.org/10.3390/sym9080152

    Article  Google Scholar 

  13. Mitrou L., Kandias M., Stavrou V., Gritzalis D.: Social media profiling: a Panopticon or Omniopticon tool? In: Proceedings of the 6th Conference of the Surveillance Studies Network (2014). https://www.infosec.aueb.gr/Publications/2014-SSN-Privacy%20Social%20Media.pdf

  14. Mustafa, H., Anwer, M.J., Ali, S.S.: Measuring the correlation between social profile and voting habit and the moderation effect of political contribution for this relationship. Int. J. Manag. Organ. Stud. 5(1), 44–57 (2016). http://www.ijmos.net/wp-content/uploads/2016/05/Haseeb-et.-al.pdf

  15. Poulin, C., et al.: Predicting the risk of suicide by analyzing the text of clinical notes. PLoS ONE. 9(1), e85733 (2014). https://doi.org/10.1371/journal.pone.0085733

    Article  Google Scholar 

  16. Rajeswari, M.: Collaborative filtering approach for big data applications in social networks. Int. J. Comput. Sci. Inf. Technol. 6(3), 2888–2892 (2015). https://www.scribd.com/document/289535998/Collaborative-Filtering-Approach-for-Big-Data-Applications-Based-on-Clustering-330-pdf

  17. Rangel, F., Rosso, P.: On the multilingual and genre robustness of EmoGraphs for author profiling in social media. In: Mothe, J., et al. (eds.) CLEF 2015. LNCS, vol. 9283, pp. 274–280. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-24027-5_28

    Chapter  Google Scholar 

  18. Richelson, J.T.: The U.S. Intelligence Community, 7th edn. Routledge, 650 pages, London (2015)

    Book  Google Scholar 

  19. Rossi, S., Ferland, F., Tapus, A.: User profiling and behavioral adaptation for HRI: a survey. Pattern Recognit. Lett. 99, 3–12 (2017). https://doi.org/10.1016/j.patrec.2017.06.002

    Article  Google Scholar 

  20. Timonin, A.Y., Bozhday, A.S., Bershadsky, A.M.: Analysis of unstructured text data for a person social profile. In: Proceedings of the International Conference on Electronic Governance and Open Society: Challenges in Eurasia, eGose 2017, St. Petersburg, Russia, pp. 1–5. ACM New York (2017). https://doi.org/10.1145/3129757.3129758

  21. Timonin, A.Y., Bozhday, A.S., Bershadsky, A.M.: Research of filtration methods for reference social profile data. In: Proceedings of the International Conference on Electronic Governance and Open Society: Challenges in Eurasia, EGOSE 2016, pp. 189–193. ACM, New York (2016). https://doi.org/10.1145/3014087.3014090

  22. Timonin, A.Y., Bozhday, A.S., Bershadsky, A.M.: The process of personal identification and data gathering based on big data technologies for social profiles. In: Chugunov, A.V., Bolgov, R., Kabanov, Y., Kampis, G., Wimmer, M. (eds.) DTGS 2016. CCIS, vol. 674, pp. 576–584. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-49700-6_57

    Chapter  Google Scholar 

  23. Tsalis, T., Avramidou, A., Nikolaou, I.E.: A social LCA framework to assess the corporate social profile of companies: Insights from a case study. J. Clean. Prod. 164, 1665–1676 (2017). https://doi.org/10.1016/j.jclepro.2017.07.003

    Article  Google Scholar 

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Correspondence to Alexey Y. Timonin .

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Timonin, A.Y., Bershadsky, A.M., Bozhday, A.S., Koshevoy, O.S. (2018). Social Profiles - Methods of Solving Socio-Economic Problems Using Digital Technologies and Big Data. In: Alexandrov, D., Boukhanovsky, A., Chugunov, A., Kabanov, Y., Koltsova, O. (eds) Digital Transformation and Global Society. DTGS 2018. Communications in Computer and Information Science, vol 858. Springer, Cham. https://doi.org/10.1007/978-3-030-02843-5_35

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  • DOI: https://doi.org/10.1007/978-3-030-02843-5_35

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