=Paper=
{{Paper
|id=Vol-2392/paper5
|storemode=property
|title=Social Networks as a Tool for a Higher Education Institution Image Creation
|pdfUrl=https://ceur-ws.org/Vol-2392/paper5.pdf
|volume=Vol-2392
|authors=Olha Anisimova,Valeriia Vasylenko,Solomia Fedushko
|dblpUrl=https://dblp.org/rec/conf/coapsn/AnisimovaVF19
}}
==Social Networks as a Tool for a Higher Education Institution Image Creation==
https://ceur-ws.org/Vol-2392/paper5.pdf
Social Networks as a Tool for a Higher Education
Institution Image Creation
Olha Anisimova1 [0000-0002-8016-9361], Valeriia Vasylenko2[0000-0002-2370-5615],
Solomia Fedushko3 [0000-0001-7548-5856]
1
Vasyl’ Stus Donetsk National University, Vinnytsia, Ukraine
3
Lviv Polytechnic National University, Ukraine
o.anisimova@donnu.edu.ua1, v.vasilenko@donnu.edu.ua2,
3
solomiia.s.fedushko@lpnu.ua
Abstract. The article presents the dynamics of social networks users increase,
depending on the total world population from 2010 to 2018. It also identifies
the most popular social networks in Ukraine. The systematic risk indicator of
using social networks relative to the total number of Internet resources users is
determined. Types of social intercourse in the process of the higher education
institution image creation are presented. The peculiarities of using social net-
works in the formation of a positive image of an educational institution are
highlighted. The statistical indicators of user actions in the official group of the
Faculty of Mathematics and Information Technologies of Vasyl’ Stus Donetsk
National University in January, February and March 2019 are presented, as well
as the average attraction coefficient of users depending on the subject of publi-
cations. The main technologies of astroturfing in the creation process of the
higher education institution negative image are considered.
Keywords: image, higher education institution, social networks, social inter-
course, engagement rate, astroturfing.
1 Introduction and Motivation
There is a rapid increase of the global Internet user numbers in the XXI century. First
of all, this is due to the convenience and practicality of using a variety of tools for
searching pertinent information, storage of data in cloud technologies, creation and
support of communications, operative news reporting, etc. Social network is one of
such tool that provides the ability to create private virtual space.
The analytical agency “Statista” represents the data demonstrating that number of
social networks users has reached 3,196 billion people (in 2019), with the age group
of the majority falling from 16 to 24 years old [22]. In other words, it can be assumed
that the vast majority of users are schoolchildren and graduates of educational institu-
tions that are enrollees and constitute a significant part of the target audience of the
institution of higher education (IHE).
It leads to the formation and maintenance of a quality information policy using infor-
mation resources of modern social networks in order to create a positive image for
university enrollees, establishing and maintaining partnerships with similar educa-
tional and scientific institutions comes to the fore.
2 Related Research
A large number of scholars engaged in the formation of the image of a higher educa-
tion institution. N. V. Horbenko [8] considers the need to introduce image manage-
ment in the marketing system of the modern university; the problem of a IHE positive
image creation by conducting a quality information policy is considered by S. M.
Pavlov [15, 16], R. Korzh, A. Peleshchyshyn, S. Fedushko [10], Y. Syerov [12]; the
problem of universities image creation through the prism of the image components
itself and the signs of student satisfaction are engaged by N. Azoury, L. Daou,
C. E. Khoury [1].
The use of social networks as an influence tool on behavior, the activity of the IHE
target audience are considered by Ukrainian and foreign researches. G. I Batychko,
O. R. Veliyeva [2] consider the using impact of the IHE Internet representation in
social networks. A. Toda, R. Carmo, A. Silva, I. Bittencourt, S. Isotani [23] explores
the use of social networks in educational contexts in order to increase of consumers’
productivity, engage and motivation. M. Vitoropoulou and V. Karyotis [25], on the
one hand, define the possibilities of tracking the distribution of various kinds of in-
formation in social sources; on the other hand, examine the characteristics of using
the metrics of social networks analysis.
O. S. Petrenko [18], D. Holland, A. Krause, J. Provencher, T. Seltzer [7] are worth
noticing. Authors consider technologies specifics of positive and negative influence of
social networks on public opinion.
The peculiarities of the astroturfing technologies as the creation of artificial public
opinion are considered by J. Peng, S. Detchon, K. R. Choo, H. Ashman [17].
R. Korzh, A. Peleshchyshyn, S. Fedushko, Y. Syerov [11] investigate possible meth-
ods for protecting the university's information image from short-term and ongoing
aggressive actions in social networks.
However, it should be noted that there are no studies that fully disclose and compre-
hensively characterize the specifics of the use of social networks in the IHE image
creation process. It determines the purpose of this study.
The purpose of the present research is to determine the peculiarities of the use of so-
cial networks in the process of higher education institution image creation.
3 Methodology of research
The methodology involves the number of general scientific and special methods of
cognition. In particular, there are the following: the method of analysis and systemati-
zation of scientific literature, logical method, monitoring, observation and method of
research results visualization.
4 Basic Points Statement
There is no single interpretation of the term «image» in modern science. Let's single
out one of the most accurate definitions of the image in the era of modern information
days. It defines an image as a communicative unit of influence on mass consciousness
[9].
Conducting an analogy with the process of forming the image of a higher education
institution, the consciousness control of a particular target audience, which can in-
clude enrollees and their parents, partner institutions, competitors, employers, and
state could take place.
Two main components of the image have to be used in order to create a holistic image
of the IHE. The information component includes a set of all representations
(knowledge) about the institution itself: history, values, traditions of the IHE, peculi-
arities of its functioning. The estimated component includes a general idea of the
educational institution characteristics and determines the relationship of the audience
to the institution itself. The second one involves the features of its emotional percep-
tion, the formation of the readiness of the audience to act in different ways, con-
sciously relying on those rules and regulations that operate in an educational institu-
tion [5, 15].
Social networks are one of the modern tool for providing the ability to establish
communication links and work with the audience consciousness from all social and
communication technologies.
Social networks are defined as a platform, an online service or a website created for
social relationship formation, reflection and organization. [6].
The popularity of social networks is beyond doubt. Thus, according to the analytical
agency “Statista”, the number of Internet users in 2019 reached 4,021 billion people,
almost 66 percent of which are social networks users.
The dynamics of the social networks users increase, depending on the total population
in the world from 2010 to 2018, is presented in Fig. 1. [13, 14, 19].
To establish the necessity of using the information resources of social networks in the
process of forming the image of the institution of higher education, we will determine
the dependence, the coefficient of sensitivity (reliability) of the number of users of
social networks.
First of all, use the formula for determining the systematic risk:
𝑉𝑅 𝑖 𝑅
𝛽= 2 (1)
𝜎𝑅
where 𝑅 – a random variable characterizing the entire economy; 𝑅𝑖 – a random varia-
ble characterizing a particular industry.
It should be noted that the industry with the indicator:
𝛽 = 1 has a fluctuation of results equaled to the market;
𝛽 < 1 – less marketable;
𝛽 > 1 – more marketable.
7,52 7,6
7,35 7,43
7,1 7,18 7,27
6,93 7,01
3,86 4,02
3,58
3,15
2,88
2,63 2,46 2,62
2,42 2,28
2,18 2,14
1,99 1,91
1,59
1,22 1,4
0,97
2010 2011 2012 2013 2014 2015 2016 2017 2018
Total population Internet users Social media users
Fig. 1. Statistics on the use of social networks in the world from 2010 to 2018 (in billion).
The higher 𝛽 means the higher industry risk [20].
We will carry out the calculations on three stages:
I. Determination of the sensitivity coefficient of the number of Internet resources
users (Ri = y) relative to the total population in the world (R = z).
II. Determination of the sensitivity coefficient of the number of social networks users
(Ri = x) relative to the total population in the world (R = z).
III. Determination of the coefficient of sensitivity of the number of social networks
users (Ri = x) relative to users of Internet resources in general (R = y).
The coefficient of sensitivity (reliability) of the number of social networks users is
determined by the formula:
𝑉
𝛽 = 𝑥𝑦
2, (2)
𝜎𝑦
where
𝑉𝑥𝑦 = xy
̅̅̅ − 𝑥̅ ∙ 𝑦̅ (3)
and
𝜎𝑦2 = ̅̅̅
𝑦 2 − (𝑦̅)2 . (4)
The sensitivity ratio of the number of Internet resources users relative to the total
population in the world (𝛽1 ) is 3,11. The sensitivity ratio of the number of social net-
works users relative to the total population in the world (𝛽2 ) is 2,51. 𝛽3 is the coeffi-
cient of sensitivity of the number of social networks users in relation to users of Inter-
net resources in general is 0,77. It means the systematic risk index 𝛽3 less than 1. In
this case it is possible to conclude the following: the use of information resources of
social networks is a prerequisite for the formation of the image of the IHE in the
modern information and communication space.
If we consider the Ukrainian audience, then more than 11 million people are active
users of Facebook. Instagram and Youtube take the second and the third place respec-
tively (Fig. 2) [27].
Other 1,95%
Tumblr 1,43%
Vkontakte 2,94%
Twitter 5,80%
Pinterest 8,88%
YouTube 9,10%
Instagram 16,79%
Facebook 53,11%
0,00% 10,00% 20,00% 30,00% 40,00% 50,00% 60,00%
Fig. 2. The most popular Ukrainian social networks in 2018.
Consequently, it concludes that social networks are the tool affected the conscious-
ness of population because of virtue of its prevalence and popularity.
One of the peculiarities of using social networks is the possibility of forming commu-
nications, creating certain social connections.
It is possible to highlight such social connections in shaping the image of a higher
education institution (Fig. 3).
Fig. 2 shows strong social connections formed between the participants in the com-
munication process permanent connected between themselves and the institution of
higher education, using, besides social networks, other communication technologies
(e-mail, mobile communication).
Latent social ties are formed between those target audience members who have poten-
tially possible links, but have not yet established them.
Social networks allow ones to activate latent connections and transfer the members of
the target audience to the role of «acquaintances». In other words, there is a transition
to weak social ties [24].
Fig. 3. Types of social connections during the image of the IHE creation.
Determine the features of using social networks during the image of IHE creation on
their functional features (see Tab. 1) [21]. In such a manner, information resources of
social networks provide IHE the following ability:
─ to target users allocating the target audience by tracking the actions of the group
members: subscribing to the group, "posting" the publications, placing the likes /
dislikes;
─ determination of information requests of potential enrollees and implementation of
operational information services for users: holding consultations in personal corre-
spondence, providing public answers to questions in the comments;
─ create and support business relations with the target audience.
To determine the most popular content among Facebook social network users, it is
possible to calculate the average engagement rate.
Table 1. Features of using social networks during the image of IHE creation.
Social network Aspect of the IHE image Information resources of social
function creation networks
Communication Establishing business contacts Official groups of educational
with the target audience. institutions, faculty, faculty in
Possibility of operative infor- Facebook, Telegram, acounts in
mation exchange between the Instagram.
participants of the educational Social Networks for Scholars:
process (students, teachers) Google Scholar, Academia.edu,
ResearchGate.
Messengers for answering re-
quests, «posting» publications,
adding comments to them
Informational Determination of information Subscriptions and group calls,
requests of enrollees. individual publications.
Creating information services for Consultations of enrollees, stu-
users. dents, other participants of the
Publication of information on educational process in public and /
actual problems of the educational or personal correspondence.
process Comments of publications by
group members
Socializing Overcoming the communication Virtual communication (text,
barrier, obstacles in communi- audio, video messages) in personal
cating with classmates, and teach- correspondence.
ers. Adding friends and teachers to
Formation of a wide range of friends
participants for communication
Identification Comparison of different IHE, Searching IHE, users with prede-
students who study in them. fined parameters: age, gender,
Selection of the target audience: country; search for belonging to a
search for potential enrollees, particular group
partner institutions
Entertaining Attracting the target audience. Publication of photo-, audio-,
Ability to realize creative abilities video-records of cultural events
held in the IHE in official ac-
counts, the accounts of the IHE
themselves, «transferring» enrol-
lees by students, teachers to their
personal pages
For this purpose, let’s analyze all publications of the Faculty of Mathematics and
Information Technologies (FMIT) of Vasyl’ Stus Donetsk National University official
group in the period from January to March in 2019 [4]. Three main topics of pub-
lished records are defined:
1. «Festive» publications: birthday greetings of employees and students of the faculty;
conducting, celebrating of festive events.
2. Thematic publications about employees and students: participation in educational
events (olympiads, conferences), vocational guidance sessions, schedule of training
sessions, examination sessions, participation in professionals’ workshops.
3. University publications related to the organization of the educational process: the
selection of students’ free-choice courses; calls for study abroad; internships oppor-
tunities; job vacancies.
The table presents the main statistical performance of users, depending on the topics
of publications in the official group of the Faculty of Mathematics and Information
Technologies of Donetsk National University named after Vasyl’ Stus during the
defined period.
Table 2. Statistic representation of users in the official FMIT group on Facebook.
Involvement
The type of Number of Number of
publications users in publica- Clicks Reactions-
on the group tions for likes,
Facebook publication comments,
reposts
«Festive»
9 546 315
publications
Thematic
610 7 371 151
publications
University
11 193 66
publications
The formula for determining the average engagement rate for users is the follow [26]:
Engagement Volume (Likes + Clicks + Comments + Reposts)÷ 𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑝𝑜𝑠𝑡𝑠
Avrage Engagement Rate (AER) ==
Number of users
× 100% (5)
After conducting the calculations, it can be determined that the most popular among
the group's subscribers are the publications on celebratory themes, AER which made
up 15,7%. The second place takes thematic publications, the average rate of attraction
of which was 12,2%. The smallest popularity in general university records, where the
AER was 3,9%, although by statistic their number is the largest.
In the such way, the main features of using social networks in the creation of a posi-
tive image of higher education institution is identified. However, it should be noted
that social networks are only at first glance a transparent instrument, objective and
free of ideologies. In fact, social networks can be used to generate artificial public
opinion that could mean the creation of an astroturfing process.
Under astroturfing we will mean «using modern software, or specially hired paid
users for artificial management of public opinion». The main goal of astroturfing is to
crowd out the thoughts of real people on web forums, to organize counterfeit online
campaigns that create the impression that a large number of people require something
specific or oppose something [3].
Consider the basic technologies of astroturfing implemented in social networks for the
formation of a negative image of the institution of higher education [18]:
1. Invited comments and «posts» on Internet resources.
2. For example, competitor institutions may leave comments under publications in the
official IHE group, indicating false information that the institution closes or the in-
stitution has not get a license for the activity.
3. Prepaid trolling including posting messages of provocative, humiliating content in
order to provoke a controversy, to indulge the indignation, the rage of opponents.
4. For example, posting a post that professor of a IHE faculty, require bribes, from
students for successful assignments, examinations or dissemination of information
about an «intimate» scandal with the participation of an adult teacher and minor
student.
5. Creating pages of «clones» or «fake» pages.
6. Social networks allow the free creation of pages of «artificial» personalities which
false information disseminated through personal posts, commentary on publica-
tions; distribution of publications with a mark on other social network users.
7. The placement of «viral» photographic, audio and video materials in public access
and distribution among users of the social network.
More effective is the placement of such materials in the «top», the most popular
groups, or «promotion» (artificial increase) of likes, comments on such publications.
Consequently, the use of the above mentioned technologies of social networks can
provide an opportunity to form an «artificial» negative public opinion about a particu-
lar institution of higher education, thereby reducing its rating and spoiling the overall
impression. The change in the behavior of the target audience will be observed as
follows: entrants and their parents will not have the will and in future to join the sub-
mitted IHE; potential employers, other educational and scientific institutions do not
want to establish business relations, and students will be deducted or transferred to
other departments / other institutions of higher education.
As we see, the use of social networks in the process of forming the image of a higher
education institution is a very interesting and innovative direction that needs further
research.
5 Conclusions
The dynamics of increase of social networks users on the total population and Internet
users in the world from 2010 till 2018 is presented. The necessity of using infor-
mation resources of social networks in the creation of the image of the higher educa-
tion institution in the modern information and communication space due to the deter-
mination of the indicator of the systematic risk of using social networks in relation to
the total number of users of Internet resources has been proved. Three main types of
social connections are considered in shaping the image of a higher education institu-
tion depending on its target audience. The aspects of the higher education institution
positive image in the functional use of information resources of social networks are
described. An analysis of all publications of the Faculty of Mathematics and Infor-
mation Technologies of the Vasyl’ Stus Donetsk National University official group in
the period from January to March 2019 has been analyzed. The average coefficient of
attraction of users for three types of publications is defined. The main technologies of
astroturfing that can be implemented in social networks for creation of a negative
image of a higher education institution are represented. There are: custom comments
and «posts» on Internet resources are considered; ordered trolling; creation of pages –
«clones» or pages –«fake»; placing «viral» photographs, audio and video materials in
public access and distribution among users of the social network.
References
1. Azoury, N., Daou, L., Khoury, C. E.: University image and its relationship to student satis-
faction- case of the Middle Eastern private business schools. International Strategic Man-
agement Review 2, 1–8 (2014).
2. Batychko, G. I., Veliyeva, O. R.: Social networks as a forming factor of positive image
and positioning space of the university at the educational service market. Bulletin of the
Mariupol State University. Series: Philosophy, Culturology, Sociology 3, 17–25 (2012).
3. Danko, Yu. A.: Asturfing as an instrument of virtual manipulation and political propagan-
da in the information age. Modern society: political sciences, sociological sciences, cultur-
al sciences 2, 38–49 (2015).
4. Facebook. Faculty of Mathematics and IT of Vasyl Stus DonNU. URL:
https://www.facebook.com/math.donnu/ last accessed 2019/04/15.
5. Fadeeva, M. V.: Psychological conditions of training of heads of general educational insti-
tutions. author's abstract dis. for the sciences. Degree Candidate ps. sciences. Kyiv (2010).
6. Gorbatiuk, T. V.: The development of Internet: perspective and prospects. Scientific Bulle-
tin of NUBiP of Ukraine. Series: Humanities Studies 274, 44–51 (2017).
7. Holland, D., Krause, A., Provencher, J., Seltzer, T.: Transparency tested: The influence of
message features on public perceptions of organizational transparency. Public Relations
Review. 44(2), 256–264 (2018).
8. Horbenko, N. V.: Features of shaping the image of a modern university. Educational dis-
course 1(5), 36–43 (2014).
9. Kirichok, A.: The use of new media in shaping the image of universities. Bulletin of the
Book Chambe 2, 42–44 (2015).
10. Korzh, R., Fedushko, S., Peleschyshyn, A.: Methods for forming an informational image
of a higher education institution. Webology 12(2), 1–10 (2015).
http://www.webology.org/2015/v12n2/a140.pdf
11. Korzh, R., Peleshchyshyn, A., Fedushko, S., Syerov, Y.: Protection of University Infor-
mation Image from Focused Aggressive Actions. Advances in Intelligent Systems and
Computing: Recent Advances in Systems, Control and Information Technology, SCIT
2016, 543, pp. 104–110. Springer, Poland (2017). DOI: 10.1007/978-3-319-48923-0_14.
12. Korzh, R., Peleshchyshyn, A., Syerov, Yu., Fedushko, S.: University’s Information Image
as a Result of University Web Communities’ Activities. Advances in Intelligent Systems
and Computing: Selected Papers from the International Conference on Computer Science
and Information Technologies, CSIT 2016, 512, pp. 115-127. Springer, Ukraine (2017).
DOI: 10.1007/978-3-319-45991-2_8.
13. Number of internet users worldwide from 2005 to 2018 (in millions).
https://www.statista.com/statistics/273018/number-of-internet-users-worldwide/. last ac-
cessed 2019/04/12.
14. Number of social media users worldwide from 2010 to 2021 (in billions).
https://www.statista.com/statistics/278414/number-of-worldwide-social-network-users.
15. Pavlov, S. N.: Information factor in formation of image of higher educational institution.
Fundamental research 9, 635–640 (2012).
16. Pavlov, S. N.: Main principles of the conception of the effective image formation of the
higher educational institution. Fundamental research 4, 1216–1221 (2013).
17. Peng, J., Detchon, S., Choo, K. R.: Astroturfing detection in social media: a binary ngram–
based approach. Concurrency and Computation. Practice and Experience 29(17), (2016).
18. Petrenko, O. S.: Specificity of Technologies for Influence on Public Opinion in Electronic
Social Networks and Social Media. Modern social problems in the measurement of sociol-
ogy of management: a collection of scientific works of the DonNUU 281, 241–249 (2014).
19. Pyramid of world population from 1950 to 2100,
https://www.populationpyramid.net/ru/%D0%BC%D0%B8%D1%80-
%D0%B7%D0%B5%D0%BC%D0%BB%D1%8F/2015/, last accessed 2019/04/12.
20. Rassokhin, V. V., Chaprak, N. V.: Assessment of the investment market using the relative
range of asset price fluctuations. Finance and credit 29, 13–28 (2015).
21. Sadigora, T. S.: Social and psychological functions of social networks. TSU Science Vec-
tor 3, 192–194 (2012).
22. Social networks in 2018: a global study, https://www.web-canape.ru/business/socialnye-
seti-v-2018-godu-globalnoe-issledovanie/, last accessed 2019/04/19.
23. Toda, A., Carmo, R., Silva, A., Bittencourt, I., Isotani, S.: An approach for planning and
deploying gamification concepts with social networks within educational contexts. Interna-
tional Journal of Information Management 46, 294–303 (2019).
24. Tsykhovska, E. D.: Self-presentation in social networks: Facebook account as a tool of im-
age creation. Dnipropetrovsk University Bulletin 17, 137–147 (2017).
25. Vitoropoulou, M., Karyotis, V., Papavassiliou, S.: Sensing and monitoring of information
diffusion in complex online social networks. Peer-to-Peer Networking and Applications
12(3), 604–619 (2018).
26. What is the engagement rate and how to calculate it?
https://geniusmarketing.me/lab/koefficient-vovlechennosti/ last accessed 2019/04/16.
27. What social networks are popular among residents of Ukraine: statistics by year,
https://tech.informator.ua/2018/11/01/kakie-sotsseti-populyarny-u-zhitelej-ukrainy-
statistika-po-godam/, last accessed 2019/04/14.