Citation of Mass Media Resources in Social Network

© Media Watch 9 (3) 361-371, 2018
ISSN 0976-0911 e-ISSN 2249-8818
DOI: 10.15655/mw/2018/v9i1/49481
 

Citation of Mass Media Resources in Social Network

ELENA N. FOKINA1, NATALYA I. NIKITINA2, & MARINA V. VINOGRADOVA3
1Tyumen Industrial University, Russian Federation
2Pirogov Russian National Research Medical University, Russian Federation
3Russian State Social University, Russian Federation
 
Abstract
The role of social networks in the formation of collective behaviour and a sustainable point of view/position regarding the information events or facts is studied herein. The purpose of the study is to analyse the reaction of the users of popular social networks, expressed in quotations and responses to the messages of mass media resources. A statistical measure of interest in the media news is identified through unique messages from queries on the topic. The approach used is aimed at improving the scientific argumentation on the assumption of a direct relationship between these phenomena. The empirical evaluation is carried out according to the data obtained from the Russian segment of social networks. The trends in the distribution of media content in social media and social networks are revealed using structural and correlation analysis. It is determined that the publications in online media correlate directly with the activities of social networks and are caused by the release of one or another information event. The results of the study also convincingly point out that the importance of the media resources, expanding due to the integration of social networks, increases, while the classical model of online media (media edition as own website) is gradually losing popularity and audience.
 
Keywords: Media resources, social networks, citation index, mass media, media content
 
References
 
Adler, R.B., Rodman, G.R., & Hutchinson, C.C. (2012). Understanding Human Communication. Oxford University Press.
Agency ComScore. (n.d.). Retrieved April 27, 2018, from https://www.comscore.com
Aggarwal, C.C. (Ed). (2011). Social Network Data Analytics. Springer US.
AMEC (International Association for Measurement and Evaluation of Communication). (n.d.). Retrieved April 27, 2018, from http://amecorg.com
Asur, S., & Huberman, B.A. (2010). Predicting the Future with Social Media. In 2010 IEEE/ACM International Conference on Web Intelligence-Intelligent Agent Technology (WI-IAT), Toronto, ON (pp. 492-499).
Bao, Y., Yi, C., Xue, Y., & Dong, Y. (2015). Precise Modeling Rumor Propagation and Control Strategy on Social Networks. In: P. Kazienko, N. Chawla (Eds.), Applications of Social Media and Social Network Analysis. Lecture Notes in Social Networks. Cham: Springer.
Barnes, J.A. (1954). Class and Committees in a Nor­wegian Island Parish. Human Relations,7, 39-58.
Bollen, J., Mao, H., & Zeng, X.-J. (2012). Twitter Mood Predicts the Stock Market. In Proceedings of the 6th International AAAI Conference on Weblogs and Social Media (ICWSM’12). Dublin.
Boyd, D.M., & Ellison, N.B. (2007). Social Network Sites: Definition, History, and Scholarship. Journal of Computer-Mediated Communication, 13(1), 210-230.
Brand Analytics. (n.d.). Retrieved April 27, 2018, from https://br-analytics.ru
Burt, R.S. (1980). Models of Network Structure. Annual Review of Sociology, 6.
Castells, M. (1999). Becoming of a Network Society. In A New Post-Industrial Wave in the West. Anthology. Moscow.
Chadwick, A., & Howard, Ph. (2009). Introduction: New Directions in Internet Politics Research. In Routledge Handbook of Internet Politics. London.
Christakis, N.A., & Fowler, J.H. (2009). Connected: The Surprising Power of Our Social Networks and How They Shape Our Lives. New York: Back Bay Books.
ComScore. (n.d.). Retrieved April 27, 2018, from https://www.comscore.com/
Fletcher, R. (1966). Human Needs and the Social Order. Schocken Books.
Granovetter, M. (2009). The Strength of Weak Links. Economic Sociology, 10.
Gusev, A.P. (2015). Citation as a Means of Creating a Dialogue in Publicistic Discourse. The Symbol of Science, 6, 204-207.
Hägerstrand, T. (1966). Aspects of the Spatial Structure of Social Communication and the Diffusion of Information. Papers of the Regional Science Association, 16(1), 27-42.
Hannak, A., Anderson, E., Feldman-Barrett, L., Lehmann, S., Mislove, A., & Riedewald, M. (2012). Tweetin’ in the Rain: Exploring Societal-Scale Effects of Weather on Mood. In Proceedings of the 6th International AAAI Conference on Weblogs and Social Media (ICWSM’12). Dublin.
Hoggart, R. (1982). The Future of Broadcasting. In R. Hoggart, An English Temper. Essays on Education, Culture and Communication. London. (p. 164).
Huckfeldt, R., & Sprague, J. (1995). Citizens, Parties, and Social Communication. New York: Cambridge University Press.
Jackson, M.O. (2008). Social and Economic Networks. Princeton University Press.
Jones, S. (1999). Doing Internet Research: Critical Issues and Methods for Examining the Net. London.
Kemova, K.V. (2011). Citation as a Means of Media Representation of Countries and Their Leaders. Bulletin of Chelyabinsk State University, 11, 74-76.
Lazarfeld, P.F., Berelson, B., & Gaudet, H. (1944). The People’s Choice. New York: Columbia University.
LeHong, H., & Fenn, J. (2012). Key Trends to Watch in Gartner 2012 Emerging Technologies Hype Cycle. Retrieved April 27, 2018, from http://www.forbes.com/sites/gartnergroup/2012/09/18/key-trends-to-watch-in-gartner-2012-emerging-technologies-hype-cycle-2
Leontiev, A.A. (2003). Psycholinguistic Features of the Media Language. In Mass Media as an Object of Interdisciplinary Research. Tutorial (pp. 66-88). Moscow: Moscow State University.
Lymperopoulos, I.N., & Ioannou, G.D. (2016). Understanding and Modeling the Complex Dynamics of the Online Social Networks: A Scalable Conceptual Approach. Evolving Systems, 7(3), 207-232.
Merkulova, T.V., & Kononova, E.Yu. (2009). Modeling the Dynamics of Users of Social Networks. Biznesinform, 2(1), 44-47.
Mislove, A., Lehmann, S., Ahn, Y., Onnela, J., & Rosenquist, J.N. (2011). Understanding the Demographics of Twitter Users. In Proceedings of the 5th International AAAI Conference on Weblogs and Social Media (ICWSM’11). Barcelona.
O’Connor, B., Balasubramanyan, R., Routledge, B., & Smith, N. (2010). From Tweets to Polls: Linking Text Sentiment to Public Opinion Time Series. In Proceedings of the 6th International AAAI Conference on Weblogs and Social Media (ICWSM’10). Washington.
Public Opinion Foundation. (2017). Internet in Russia: The Dynamics of Penetration. Winter of 2017-2018. Retrieved April 27, 2018, from http://fom.ru/SMI-i-internet/13585
Radaev, V.V. (1997). Economic Sociology: A Course of Lectures. Moscow: Aspect Press.
Sarvaiya, M. (2013). Human Communication. Amazon International.
Schenk, M. (1983). Das Konzept des sozialen Netzwerkes. Kölner Zeitschrift für Soziologie und Sozialpsychologie, 25, 88-104.
Terentyeva, E.D. (2016a). Pragmatic Aspects of Citation in the Spanish Mediatexts. Bulletin of Russian Peoples’ Friendship University. Series Linguistics, 20(3), 43-56.
Vaca Ruiz, C., Aiello, L.M., & Jaimes, A. (2014). Modeling Dynamics of Attention in Social Media with User Efficiency. EPJ Data Science, 3(5).
Varchenko, V.V. (2012). Quotation in the Media Text (2nd ed.). Moscow: LIBROKOM. (p. 240).
Volynets, Yu.P. (2015). Analysis of Modern Citation Research in the Media Discourse. XXI Century: Resumes of the Past and Challenges of the Present Plus, 3(6(28), 213-217.
Watts, D. (2004). Six Degrees: The Science of a Connected Age. New York: W.W. Norton & Company.
Zadorin, I., Strebkov, D., Syutkina, A., & Khalkina, E. (2000). The Influence of Mass Media on the Mass Political Consciousness of Russians during the Election Campaign of 1999. Independent Media Measurements, 4-5.
 
 
Dr. Elena N. Fokina is an assistant professor in the Department of Business Informatics and Mathematics at Tyumen Industrial University, Russian Federation. Her areas of scientific interest are: mathematical methods of research in the economy, information technology, social aspects of vocational training, social networks.
Dr. Natalya I. Nikitina is a professor in the Department of Social Work of the Psychological and Social Faculty, Pirogov Russian National Research Medical University (RNRMU); Russian State Social University, Russian Federation. Her areas of scientific interest are: information technologies, rehabilitation technologies in psychology and social work, continuous education of specialists in the socionic profile, mass media.
Dr. Marina V. Vinogradova is a professor and director of Research Institute of Advanced Directions and Technologies, Russian State Social University, Russian Federation. Her area of scientific interests is socio-economic development of macro and microsystems, socio-cultural problems, forecasting, planning and monitoring of the development of socio-economic systems, information security and information systems.