METHODS FOR ASSESSING THE TEMPORAL STRUCTURE OF INTERNET DISCUSSIONS BASED ON THE NUMBER AND DURATION OF USER INTERACTIONS

Abstract

The aim of the research is to develop and test methods for assessing the temporal structure of online discussions based on the analysis of the number and duration of user interactions on the internet (in social networks, forums, etc.). The article describes new methods for assessing the temporal structure of online discussions, developed within the scope of this work, based on the analysis of the number and duration of user interactions on the internet. Particular attention is given to methods for determining both the intensity and duration of discussions, which enables a more accurate assessment of the real-time dynamics of discussions. The intensity of a discussion is assessed through the ratio of the number of interactions (such as comments, replies, likes) and the duration of an online discussion. Methods for accurately determining the duration of a discussion are proposed, which take into account not only the time since a post was published but also the activity of users during the discussion, making these methods more flexible and precise. The methods were tested using real data from VKontakte communities in the cities of Taganrog and Sarov. The results of the practical study confirmed the existence of expected patterns, such as daily fluctuations in user activity levels and bursts of activity associated with significant social and political events. The developed methods for assessing the temporal structure of online discussions based on the number and duration of user interactions allow for effective analysis of the dynamics of discussion participants' involvement, identifying key moments and significant events in the process of online communication. These methods can be useful in various fields, such as social research, marketing, political analysis, reputation risk management, and others, where the analysis of online activity and involvement is required.

Authors

  • А.Y. Taranov Scientific Research Institute of Multiprocessor Computer and Control Systems, Co Ltd

References

1. Serdyuk A.A. Osobennosti agressivnykh reaktsiy podrostkov s raznoy stepen'yu vovlechennosti v sotsi-al'no-kul'turnuyu deyatel'nost' [Features of aggressive behaviors of adolescents with varying degrees of involvement in socio-cultural activity], Innovatsionnaya nauchnaya sovremennaya akademicheskaya is-sledovatel'skaya traektoriya (INSAYT) [Innovative Scientific Modern Academic Research Trajectory (INSAJT)], 2022, No. 1 (9), pp. 28-38. DOI: 10.17853/2686-8970-2022-1-28-38. EDN EBATOC.

2. Fofanova G.A., Pozdnyakova A.V. Emotsional'nyy intellekt studentov s razlichnoy stepen'yu vovlechennosti v elektronnye sotsial'nye seti [Emotional intelligence of students with different degrees of involvement in electronic social networks], Zhurnal Belorusskogo gosudarstvennogo universiteta. Filosofiya. Psikhologiya [Journal of the Belarusian State University. Philosophy and Psychology], 2017, No. 1, pp. 120-126. EDN XYZQXZ.

3. Dong X., Lian Y. A review of social media-based public opinion analyses: Challenges and recommenda-tions, Technology in Society, 2021, Vol. 67, pp. 101724. DOI: 10.1016/j.techsoc.2021.101724.

4. Yusha A.E. Metody verifikatsii informatsii v period postpravdy [Methods of information verification in the post-truth period], Mediasreda [Media environment], 2019, No. 15, pp. 181-187. EDN OGUFWQ.

5. Beynenson V.A. Proverka dostovernosti informatsii v usloviyakh novykh media: problemy i vozmozhnosti [Verification of the reliability of information in the context of new media: problems and opportunities], Zhurnalistika v sisteme al'ternativnykh istochnikov informatsii: Sb. materialov nauchnoy konferentsii kafedry zhurnalistiki, Nizhniy Novgorod, 14 marta 2017 goda [Journalism in the system of alternative sources of information: Collection of materials of the scientific conference of the Department of Journalism, Nizhny Novgorod, March 14, 2017]. Nizhniy Novgorod: Natsional'nyy issledovatel'skiy Nizhegorodskiy gosudarstvennyy universitet im. N.I. Lobachevskogo, 2017, pp. 79-89. EDN YPRIYB.

6. Ignat'eva I.V., Zedgenizova I.I. Marketing sotsial'nykh setey kak instrument prodvizheniya [Social media marketing as a promotion tool], Innovatsii i investitsii [Innovations and Investments], 2019,

No. 7, pp. 125-129. EDN UYFEBO.

7. Tatarinov K.A. Osobennosti internet-marketinga na B2B-rynkakh [Features of internet marketing on b2b-markets], Izvestiya Baykal'skogo gosudarstvennogo universiteta [News of the Baikal State Univer-sity], 2018, Vol. 28, No. 3, pp. 517-528. DOI: 10.17150/2500-2759.2018.28(3).517-528.

EDN ZDYJNR.

8. Masson Z., Parmentier G. Drivers and mechanisms for online communities performance: A systematic literature review, European Management Journal, 2023, Vol. 41 (4), pp. 590-606. DOI: 10.1016/j.emj.2022.08.005.

9. Limam H., Slaimi A. Web Community Management in the Digital Era: Review, Journal of Computer Information Systems, 10 Jun 2024, pp. 1-15. DOI: 10.1080/08874417.2024.2361651.

10. Gubenkov A.O. Aktual'nye problemy kiberbezopasnosti v sotsial'nykh setyakh [Current problems of cybersecurity in social networks], Avtonomiya lichnosti [Autonomy of the Individual], 2021, No. 3 (26), pp. 46-53. EDN INGAIE.

11. Khomyakov D.O. Sravnitel'nyy analiz funktsionala i vozmozhnostey sotsial'nykh setey s tsel'yu ratsion-al'nogo ikh ispol'zovaniya v politicheskom SMM [Comparative analysis of the functionality and possi-bilities of social networks for the purpose of their rational use in political SMM], Voprosy politologii [Questions of Political Science], 2021, Vol. 11, No. 6 (70), pp. 1930-1942. DOI: 10.35775/PSI.2021.70.6.037. EDN DCTDWK.

12. Glinskaya A.R. Vliyanie sotsial'nykh setey na ekonomicheskie sistemy [The impact of social media on economic systems], Aktual'nye problemy aviatsii i kosmonavtiki: Sb. materialov IX Mezhdunarodnoy nauchno-prakticheskoy konferentsii, posvyashchennoy Dnyu kosmonavtiki. V 3-kh t., Krasnoyarsk, 10–14 aprelya 2023 goda [Actual problems of aviation and cosmonautics: Collection of materials of the IX International scientific and practical conference dedicated to Cosmonautics Day. In 3 volumes, Krasno-yarsk, April 10-14, 2023]. Krasnoyarsk: Sibirskiy gosudarstvennyy universitet nauki i tekhnologiy imeni akademika M.F. Reshetneva, 2023, pp. 481-483. EDN OKULRQ.

13. Shageeva G.R., Safiullin M.R. Sotsial'nye seti kak istochnik reputatsionnogo riska predpriyatiya [Social networks as a source of the reputational risk of an enterprise], Problemy sovremennoy ekonomiki [Prob-lems of the Modern Economy], 2023, No. 1 (85), pp. 50-53. EDN CHDUNB.

14. Kachalin D.V., Vyshegorodtsev M.V., Andreev S.V. Model' avtomatizirovannoy sistemy analiza to-nal'nosti publichnoy deyatel'nosti sotrudnikov predpriyatiya v sotsial'nykh setyakh [Model of an auto-mated system for analyzing the tonality of public activities of enterprise employees in social networks], Modern Science, 2020, No. 4-1, pp. 350-359. EDN VNFVSN.

15. Yu Y., Jiang J., Dhillon P.S. Characterizing the Structure of Online Conversations Across Reddit, Proc. ACM Hum.-Comput. Interact., 2024, Vol. 8, pp. 23. DOI: 10.1145/3686913.

16. Dan Y., Svoboda V. Pennisi. Analysing interactions in online discussions through social network analy-sis, Journal of Computer Assisted Learning, 2022, Vol. 38 (3), pp. 784-796. DOI: 10.1111/jcal.12648.

17. Spatariu A., Hartley K., Bendixen L.D. Defining and Measuring Quality in Online Discussions, J. Inter-act. Online Learn, 2004, Vol. 2 (4), pp. 1-15.

18. Chen G., Lo C.K., Hu L. Sustaining online academic discussions: Identifying the characteristics of mes-sages that receive responses, Computers & Education, 2020, Vol. 156, pp. 103938. DOI: 10.1016/j.compedu.2020.103938.

19. Schneider S.J., Kerwin J., Frechtling J., Vivari B.A. Characteristics of the Discussion in Online and Face-to-Face Focus Groups, Social Science Computer Review, 2002, No. 20 (1), pp. 31-42. DOI: 10.1177/089443930202000104.

20. Samrose S., Hoque E. Quantifying the Intensity of Toxicity for Discussions and Speakers, 9th Interna-tional Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW), 2021, pp. 1-5. DOI: 10.1109/ACIIW52867.2021.9666258.

21. Symoneaux R., Galmarini M.V., Mehinagic E. Comment analysis of consumer’s likes and dislikes as an alternative tool to preference mapping. A case study on apples, Food Quality and Preference, 2012, Vol. 24, Issue 1, pp. 59-66. DOI: 10.1016/j.foodqual.2011.08.013

Скачивания

Published:

2025-10-01

Issue:

Section:

SECTION II. DATA ANALYSIS, MODELING AND CONTROL

Keywords:

Social networks, activity analysis, discussion intensity, discussion duration, time series

For citation:

А.Y. Taranov METHODS FOR ASSESSING THE TEMPORAL STRUCTURE OF INTERNET DISCUSSIONS BASED ON THE NUMBER AND DURATION OF USER INTERACTIONS. IZVESTIYA SFedU. ENGINEERING SCIENCES – 2025. - № 4. – P. 155-162.