Abstract
The Internet forms not only new cyberspace but also has a significant impact on the perception of time and its organization. Focusing on the phenomenon of temporal behavior in social media, the current study aims to identify factors that can determine the dynamics of communication in the comments of the popular Russian social network Vkontakte. The research is based on data from six major online media: “Meduza,” “Lenta.ru,” “Rossiyskaya Gazeta,” “Novaya Gazeta,” “Mayak,” and “Russia Today.” We examine the frequency of publications, the dynamics of communication, the temporal distribution of comments, and the post response rate. The identified four temporal behavior models described as “Discussion media,” “Stimulus is a response,” “From call to call,” “Timeless or Silence is gold,” provoke assumptions about the possible causes of differences in the dynamics of communication between Russian Internet users.
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References
Ambarova, P.A.: The concept and typology of social communities temporal behavior strategies. Izvestia Ural Fed. Univ. J. Ser. 1 Issues Educ. Sci. Cult. 1 123, 123–139 (2014). (in Russian)
Bauman, Z.: Liquid Modernity. Polity, Cambridge (2000)
Bodrunova, S., Litvinenko, A.: Fragmentation of society and media hybridisation in today’s Russia: how Facebook voices collective demands. J. Soc. Policy Stud. 14(1), 113–124 (2016). https://jsps.hse.ru/en/2016-14-1/178312074.html
Caceres, R.: Measurements of Wide Area Internet Traffic. UCB/CSD. University of California, Berkley (1989)
Castells, M.: The Rise of the Network Society, 2nd edn. Wiley-Blackwell, Malden (2010)
Kasap, Y.: Cyberloafing behavior in the workplaces and management practices. A thesis submitted to the institute of social sciences of Ankara Yildirim Beyazit University. Partial fulfillment of the requirements for the degree of master of science in the department of management and organization (2019). http://afyonluoglu.org/PublicWebFiles/Reports-TR/Akademi/2019_Yasemin%20Kasap_İşyerlerindeki%20siber%20aylaklık%20davranışı.pdf
Duh, A., Slak Rupnik, M., Korosak, D.: Collective behavior of social bots is encoded in their temporal twitter activity. Big Data 6(2), 113–123 (2018). https://doi.org/10.1089/big.2017.0041
Niu, G., Long, Y., Li., V.O.K.: Temporal behavior of social network users in information diffusion. In: Proceedings of the 2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT) (WI-IAT 2014), vol. 02, pp. 150–157. IEEE Computer Society (2014). https://doi.org/10.1109/wi-iat.2014.92
Laguerre, M.: Virtual time. Inf. Commun. Soc. 7(2), 223–247 (2004). https://doi.org/10.1080/1369118042000232666
Lee, H., Whitley, E.A.: Time and information technology: temporal impacts on individuals, organizations, and society. Inf. Soc. 18, 235–240 (2002)
Milahache, A.: The cyber space-time continuum: meaning and metaphor. Inf. Soc. 18, 293–301 (2002)
Petridou, S., Koutsonikola, V., Vakali, A., Papadimitriou, G.I.: Time-aware web users’ clustering. IEEE Trans. Knowl. Data Eng. 20(5), 653–667 (2008)
Salihu, A., Shefkiu, M., Maraj, A.: Characteristics and temporal behavior of internet backbone traffic. Int. J. Bus. Technol. 6(3) (2018). Article 3 https://doi.org/10.33107/ijbte.2018.6.3.03
Strate, L.: Cybertime. In: Strate, L., Jacobson, R., Gibson, B. (eds.) Communication and Cyberspace: Social Interaction in an Electronic Environment, pp. 351–377. Hampton, Cresskill (1996)
Thompson, K., Miller, G.J., Wilder, R.: Wide-area internet traffic patterns and characteristics. IEEE Netw. 11(6), 10–23 (1997)
Urry, J.: Mobilities. Polity, Cambridge (2007)
Wong, J.I.: The internet has developed its own prime time, and it’s coming for TV (2016). https://qz.com/701016/the-internet-has-developed-its-own-prime-time-and-its-coming-for-tv/
Zalot, M.: Buying “time” on eBay: cybertime, nostalgia, and currency in online auctions. Atlantic J. Commun. 21(1), 17–28 (2013). https://doi.org/10.1080/15456870.2013.743317
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The reported study was funded by RFBR according to the research project № 18-011-00705 “Explanatory Potential of Network Theory in Political Research: Methodological Synthesis as Analytical Strategy.”
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Lukyanova, G., Martyanov, D., Budko, D. (2020). Factors of Temporal Behavior in Online Media: What Shapes Time on Internet?. In: Alexandrov, D.A., Boukhanovsky, A.V., Chugunov, A.V., Kabanov, Y., Koltsova, O., Musabirov, I. (eds) Digital Transformation and Global Society. DTGS 2020. Communications in Computer and Information Science, vol 1242. Springer, Cham. https://doi.org/10.1007/978-3-030-65218-0_7
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