Authors: Ali Gurel Goksel, Mugla Sitki Kocman University, Faculty of Sports Sciences, Turkey.
Corresponding Author:
Ali Gurel Goksel, PhD
Mugla Sitki Kocman University, Faculty of Sports Sciences
Kotekli/Mugla, 48000
[email protected]
002522111951
Ali Gurel Goksel is a research assistant in Sports Exercise Science at the Mugla Sitki Kocman University studying public relations and communications in sports.
The Examination of Opinions of Academicians Who Are Expert on Sport Sciences about the Impact of Social Media Consumption on Institutional Image in Turkey
ABSTRACT
The aim of this study was to examine opinions of academicians who are experts in sport sciences about the impact of social media consumption on institutional image, shared content, institutional representation of staff in social media and sanction related to shared content of academic staff in Turkey. 1512 academicians working at public universities in Turkey constitute the population of the study. 343 sport scientists voluntarily participated in this study. Data was collected by using Social Media Consumption and Institutional Image Scale, developed by Ozel (2014) and by using Personal Information form designed by the author. Collected data was analyzed by using descriptive test, independent t test for two groups, one-way ANOVA, Tukey test and Pearson Correlation test. Consequently, because universities make an effort to protect their institutional image in front of public, they can decide to suspend, investigate or remove the academicians sharing their political views including despiteful comments.
Keywords: University, Institutional Image, Social Media, Academician, Sport Sciences.
INTRODUCTION
Developments in information and communication technologies in the globalizing world brings with it changes (11). These changes influence public relations and its related fields. In recent conditions in which information and communication technologies are commonly used, public relations strategies should be revised and updated. Functions of image creation and extension, which are the most important responsibility of public relations, become increasingly and strategically important in today’s world in that postmodernism is particularly influential. One of the most important factors for creating an institutional image, which is defined as impression of an institution on target group, is the employee (20).
Researchers have revealed that employees are important for institutional image with the dimensions such as institutional communication, perspective and behavior (24).
Institutional Image
Institutional image can be defined as all of the emotional and rational thoughts and perceptions of the institution’s target group (10). Institutional image, which is a source that can introduce and explain institution to internal and external stakeholders, provide a strategic competition advantage to influence the target group, has an important role for corporations (30).
An institution should run the communication sources in a perfect way to provide the environment with a good image and healthy communication; in short, it should create an in-house image (16). Infusing employees into institutional image and creating a perception about this image for them can make employees, who are important stakeholders, envoys of the corporation (15).
Institutional Image of Universities and Social Media
For institutions, achieving institutional goals depends on making differences and creating positive institutional image. Because the costumers may have no chance to test this before buying service, they prefer institutions having a positive image not to risk what they buy in this process (30). Accordingly, as a serving institution, institutional image of universities has a critical role. The efficiency of universities having positive image to set agenda and give a reference about their graduated students increases; correspondingly, these universities captivate qualified students and academicians (8). Universities having a culture to support image, good relations with employees, students and environment, high level of organizational identity and perceptions raise the perception of organizational image (25).
Social media is a common term used for “websites and online tools creating interaction by providing users with opportunities such as sharing information, opinion, and interest” (26). Even it has “media” term; social media differs from traditional media in various ways. The most important characteristics making difference are that any person can create the content, comment and contribute (32, 33). Social media, which develops and renews day by day, provides the opportunity to share text, voice, video and picture, and offers a wide usage possibility (27).
However, these new developments bring risks as well as opportunities for universities and employees. As a matter of fact, the number of employees being dismissed because of a tweet, shared video or a comment is increasing day by day; moreover, some institutions check their employee’s social media usage on account to determine if their image has been damaged (20). In this regard, it can be said that social media has a critical impact on corporate strategic communication activities (7). In literature, there are studies examining institutional image and social media Theus, (1993); Parameswaran and Glowacka, (1995); Ivy, (2001); Kazoleas, Kim and Moffitt, (2001); Nguyen and LeBlanc, (2001); Palacio, Meneses and Perez, (2002); Arpan, Raney and Zivnuska, (2003); Melewer and Akel, (2005); Paden and Stell, (2006); Eyrich et al., (2008); Curtis et al., (2010); Isler et al., (2013); Kucuksuleymanoglu, (2015); Sobaih et al., (2016).
Websites of Facebook, Twitter, Instagram, Youtube, LinkedIn and Google+ included in the study as social media tools. These social media tools are more recent and preferred application by academicians in Turkey.
The aim of this study was to examine opinions of academicians who are experts in sport sciences about the impact of social media consumption on institutional image, shared content, institutional representation of staff in social media and sanction related to shared content of academic staff in Turkey. The opinions of academicians have been examined in terms of gender, marital status, title, working year as an academician in recent university, year of using social media, the time they spent using social media in a day. For this purpose, following questions will be answered:
- How does the scale, used in the research, show a distribution?
- Are there any differences between genders in terms of the academicians’ opinions about the impact of social media usage on institutional image?
- Are there any differences between age groups in terms of the academicians’ opinions about the impact of social media usage on institutional image?
- Are there any differences between marital statuses in terms of the academicians’ opinions about the impact of social media usage on institutional image?
- Are there any differences between academic titles in terms of the academicians’ opinions about the impact of social media usage on institutional image?
- Are there any differences between working years in terms of the academicians’ opinions about the impact of social media usage on institutional image?
- Are there any differences between years of using social media in terms of the academicians’ opinions about the impact of social media usage on institutional image?
- Are there any differences between the time ranges they spend using social media in a day in terms of the academicians’ opinions about the impact of social media usage on institutional image?
This study has the importance to provide a reference for public affairs managers and human resource managers to protect institutional image in social media and impose sanctions and make an audit when new strategies are set.
METHODS
Population and Sample
Academicians working in the field of sport sciences at public universities in Turkey constitute the population of the study. According to January 2016 data of the Council of Higher Education, it has been stated that there are 1512 academicians (professor, associate professor, assistant professor, research assistant, teaching assistant, lecturer, and specialist) working in the field of sport sciences in Turkey. The calculation to specify the sample group in the level of 95% reliability and 5% of error mean has showed that 306 academician should be included in the study. Because of the uneven distribution of the number of academicians working in the field of sport sciences, simple random sampling method has been used. Data collection tool was sent to academicians’ mail addresses given in websites of universities as an online survey. 396 sport scientists voluntarily participated in this study; however, 343 of the data included in analysis after leaving incomplete and incorrect surveys out of assessment.
Data Collection Tool
Data was collected by using Social Media Consumption and Institutional Image Scale, developed by Ozel (2014). The scale has 12 items and 3 subscales (The Impacts of Social Media on Institution, Institutional Sanctions and Representing Institution on Social Media) and the items are scaled between 1 and 5 (1=Strongly agree, 2=Agree, 3=no opinion, 4=not agree, 5=strongly disagree). The highest score that can be taken from the scale is 60.00 and the lowest one is 12.00. Personal Information form designed by the author was used to determine age, gender, marital status, academic title, working years, years of using social media, the time ranges they spend using social media in a day.
According to Alpha value, if the scale is between the following values, it is interpreted as follows:
– 0.00≤a≤0.40 not reliable
– 0.40≤a≤0.60 low reliability
– 0.60≤a≤0.80 reasonably reliable
– 0.80≤a≤1.00 highly reliable (12).
Cronbach’s Alpha Internal Consistency Coefficient of the scale was found to be 0,855. The value showed that the scale was highly reliable.
Data Analysis
Collected data was analyzed by using descriptive test, independent t test for two groups, One-Way ANOVA, Tukey test and Pearson Correlation test. It was decided whether data provided the precondition of parametric tests by examining the results of Skewness and Kurtosis values and Levene test (2). Kline (2005) has suggested that data displays normal distribution when Kurtosis is between -3 and +3; Skewness is between -10 and +10. Additionally, Equality of variances assumption is ensured when F value, calculated with Levene test, is not significant (p>0.05) (3). It was reported that analysis ensured the parametric test assumption of the data. Cronbach’s Alpha internal consistency coefficient was calculated for the reliability of scale.
Limitations
This study has confined to the participation of academicians working in the field of sport sciences at Universities.
RESULTS
Table 1. Descriptive analysis of demographic variables
| Demographic Variables |
|
Percentage |
Frequency |
|
Gender |
Female |
25.4% |
87 |
|
Male |
74.6% |
256 |
|
|
Age |
30 years and under |
17,5% |
60 |
|
Between 31-40 years |
32,7% |
112 |
|
|
Between 41-50 years |
30,3% |
104 |
|
|
51 years and over |
19,5% |
67 |
|
|
Marital Status |
Married |
70.8% |
243 |
|
Single |
29.2% |
100 |
|
|
Academic Title |
Prof. Dr. |
8.7% |
30 |
|
Assoc. Dr. |
16.9% |
58 |
|
|
Assist. Prof. Dr. |
26.8% |
92 |
|
|
Res. Assist. |
24.5% |
84 |
|
|
Other (teach. Assist., lect., spec.) |
23.0% |
79 |
|
|
Working year in present institution |
Less than a year |
7.3% |
25 |
|
Between 1 – 3 years |
21.9% |
75 |
|
|
Between 4 – 6 years |
17.8% |
61 |
|
|
More than 7 years |
53.1% |
182 |
|
|
Year of using social media |
Less than a year |
2.6% |
9 |
|
Between 1 – 3 years |
12.0% |
41 |
|
|
Between 4 – 6 years |
37.6% |
129 |
|
|
More than 7 years |
47.8% |
164 |
|
|
The time spent on social media per day |
Less than 30 min. |
30.3% |
104 |
|
Between 31 – 60 min. |
46.4% |
159 |
|
|
Between 61 – 120 min. |
15.7% |
54 |
|
|
More than 2 hours |
7.6% |
26 |
Demographic information of academician working in the field of sport sciences has displayed in table 1. 87 of participants were female (25.4%), 256 of them were male (74.6%). When participations were classified in terms of ages; 60 of the participants were in the group of 30 years old and under (17.5%), 112 of them were between 31-40 years old (32.7%), 104 of them were between 41-50 years old (30.3%), 67 of them were 50 years old and over (19.5%). 243 of the participants were married (70.8%) and 100 of them were single (29.2%). 30 of the participants were Professors (8.7%), 58 of them were Associate Doctor (16.9%), 92 of them were Assistant Professor (26.8%), 84 of them were Research Assistant (24.5%), and 79 of them had other titles (teaching assistant, lecturer, and specialist). 25 of the participants reported the working year in present institution as less than a year (7.3%). 75 of them reported between 1-3 years (7.3%), 61 of them reported between 4-6 years (17.8%), 182 of them were more than 7 years (%53.1). According to year of using social media, 9 of the participants reported less than a year (2.6%), 41 of them reported between 1-3 years (12.0%), 129 of them reported between 4-6 years (37.6%), 164 of them reported more than 7 years (47.8%). According to analysis of the time spent on social media per day, 104 of the participants reported less than 30 minutes (30.3%), 159 of them reported between 31-60 minutes (46.4%), 54 of them reported 61-120 minutes (15.7%), and 26 of them reported more than 2 hours (7.6%).
Table 2. Scale sore distribution
|
|
N |
Min. |
Max. |
X |
σ |
Skewness |
Kurtosis |
|
Using Social Media and Institutional Image |
343 |
13,00 |
54,00 |
2,48 |
0,79 |
,339 |
-,414 |
According to normal distribution analysis, minimum and maximum scores taken from the scale in this study were found to be 13.00 and 54.00, respectively. Average score of the scale was found to be 2.48 and standard deviation was found to be 0.79. The scale showed normal distribution according to Skewness and Kurtosis scores (table 2).
Table 3. Differences between genders in terms of using social media and institutional image
| Subscales |
Gender |
N |
X |
σ |
t |
p |
|
The Impacts of Social Media on Institution |
Female |
87 |
2.51 |
1.03 |
-1.464 |
.144 |
|
Male |
256 |
2.71 |
1.05 |
|||
|
Institutional Sanctions |
Female |
87 |
2.03 |
.97 |
-2.586 |
.010 |
|
Male |
256 |
2.40 |
1.11 |
|||
|
Representing Institution on Social Media |
Female |
87 |
2.34 |
.90 |
-1.238 |
.217 |
|
Male |
256 |
2.47 |
.81 |
Differences between genders in terms of using social media and institutional image were displayed in table 3. According to t test analysis, while no significant differences were found between genders in terms of the impacts of social media on institution and representing institution on social media (p>0.05), statistically significant difference was found between genders in terms of institutional sanctions (p<0.05, t=-2.58). Female academicians reported lower scores than males in terms of institutional sanctions.
Table 4. Differences between age groups in terms of using social media and institutional image
| Subscales |
Age groups |
X±σ |
F |
p |
Post hoc |
|
The Impacts of Social Media on Institution |
30 years and under |
2.67±1.06 |
2.207 |
.087 |
– |
|
Between 31-40 years |
2.51±1.04 |
||||
|
Between 41-50 years |
2.67±1.04 |
||||
|
51 years and over |
2.98±1.05 |
||||
|
Institutional Sanctions |
30 years and under |
1.97±0.95 |
5.526 |
.001 |
30 years and under <51 years and over |
|
Between 31-40 years |
2.26±0.73 |
||||
|
Between 41-50 years |
2.32±1.10 |
||||
|
51 years and over |
2.79±1.27 |
||||
|
Representing Institution on Social Media |
30 years and under |
2.34±0.95 |
3.262 |
.022 |
Between 31-40 years <51 years and over |
|
Between 31-40 years |
2.96±0.99 |
||||
|
Between 41-50 years |
3.02±1.06 |
||||
|
51 years and over |
3.47±1.17 |
Differences between age groups in terms of using social media and institutional image were displayed in table 4. Statistically significant differences were found between age groups in terms of institutional sanctions and representing institution on social media (p<0.05). Academicians aged 51 years and over reported higher scores than those aged 30 years and under and between 31-40 years in terms of institutional sanctions while those aged over 51 years and over reported higher scores than those aged between 31-40 years in terms of representing institution on social media.
Table 5. Differences between marital statuses in terms of using social media and institutional image
| Subscales |
Marital Statuses |
N |
X |
σ |
t |
p |
|
The Impacts of Social Media on Institution |
Married |
243 |
2.67 |
1.06 |
.270 |
.787 |
|
Single |
100 |
2.64 |
1.03 |
|||
|
Institutional Sanctions |
Married |
243 |
2.36 |
1.11 |
1.283 |
.201 |
|
Single |
100 |
2.19 |
1.02 |
|||
|
Representing Institution on Social Media |
Married |
243 |
2.48 |
.86 |
1.250 |
.212 |
|
Single |
100 |
2.35 |
.78 |
Differences between marital statuses in terms of using social media and institutional image were displayed in table 5. According to analysis, no significant differences were found between marital statuses in terms of subscales (p>0.05).
Table 6. Differences between academic titles in terms of using social media and institutional image
| Subscales |
Academic Titles |
X±σ |
F |
p |
Post hoc |
|
The Impacts of Social Media on Institution |
Prof. Dr. |
3.50±.90 |
5.252 |
.000 |
Prof.Dr .> Assoc. Dr. |
|
Assoc. Dr. |
2.59±1.03 |
||||
|
Assist. Prof. Dr. |
2.59±1.01 |
||||
|
Res. Assist. |
2.70±1.08 |
||||
|
Other |
2.44±1.01 |
||||
|
Institutional Sanctions |
Prof. Dr. |
3.25±1.46 |
6.719 |
.000 |
Prof.Dr .> Assoc. Dr. |
|
Assoc. Dr. |
2.36±.97 |
||||
|
Assist. Prof. Dr. |
2.17±.99 |
||||
|
Res. Assist. |
2.07±.97 |
||||
|
Other |
2.35±1.05 |
||||
|
Representing Institution on Social Media |
Prof. Dr. |
3.08±.97 |
2.684 |
.000 |
Prof.Dr .> Assoc. Dr. |
|
Assoc. Dr. |
2.42±.75 |
||||
|
Assist. Prof. Dr. |
2.43±.86 |
||||
|
Res. Assist. |
2.35±.73 |
||||
|
Other |
2.32±.82 |
Differences between academic titles in terms of using social media and institutional image were displayed in table 6. It was found that professors reported higher scores than the other academicians in terms of the impacts of social media on institution, representing institution on social media and institutional sanctions (p<0.05).
Table 7. Differences between working years in present institutions in terms of using social media and institutional image
| Subscales |
Working Years |
X±σ |
F |
p |
Post hoc |
|
The Impacts of Social Media on Institution |
Less than a year |
2.63±1.04 |
.406 |
.749 |
– |
|
Between 1 – 3 years |
2.78±1.09 |
||||
|
Between 4 – 6 years |
2.61±1.01 |
||||
|
More than 7 years |
2.63±1.06 |
||||
|
Institutional Sanctions |
Less than a year |
2.53±1.05 |
2.098 |
.100 |
– |
|
Between 1 – 3 years |
2.13±.98 |
||||
|
Between 4 – 6 years |
2.12±.96 |
||||
|
More than 7 years |
2.42±1.16 |
||||
|
Representing Institution on Social Media |
Less than a year |
2.75±.91 |
1.988 |
.116 |
– |
|
Between 1 – 3 years |
2.34±.79 |
||||
|
Between 4 – 6 years |
2.32±.75 |
||||
|
More than 7 years |
2.48±.86 |
Differences between working years in present institutions in terms of using social media and institutional image were displayed in table 7. No significant differences were found between working years in present institutions in terms of the impacts of social media on institution, ınstitutional sanctions and representing institution on social media (p>0.05).
Table 8. Differences between years of using social media in terms of using social media and institutional image
| Subscales |
Year of using social media |
X±σ |
F |
p |
Post hoc |
|
The Impacts of Social Media on Institution |
Less than a year |
2.53±.90 |
1.825 |
.143 |
– |
|
Between 1 – 3 years |
3.03±.94 |
||||
|
Between 4 – 6 years |
2.57±1.08 |
||||
|
More than 7 years |
2.65±1.05 |
||||
|
Institutional Sanctions |
Less than a year |
2.54±.71 |
5.571 |
.001 |
Between 1 – 3 years> Between 4 – 6 years |
|
Between 1 – 3 years |
2.90±1.08 |
||||
|
Between 4 – 6 years |
2.33±1.05 |
||||
|
More than 7 years |
2.12±1.08 |
||||
|
Representing Institution on Social Media |
Less than a year |
2.17±.60 |
2.013 |
.112 |
– |
|
Between 1 – 3 years |
2.68±.80 |
||||
|
Between 4 – 6 years |
2.49±.84 |
||||
|
More than 7 years |
2.35±.83 |
Differences between years of using social media in terms of using social media and institutional image were displayed in table 8. While no significant differences were found between years of using social media in terms of the impacts of social media on institution and representing institution on social media (p>0.05), significant differences were found between years of using social media in terms of institutional sanctions (p<0.05, F=5.57). The academicians using social media for 1-3 years reported higher scores than those using it for 4-6 years and more than 7 years.
Table 9. Differences between the times spent on social media per day in terms of using social media and institutional image
| Subscales |
The time spent on social media |
X±σ |
F |
p |
Post hoc |
|
The Impacts of Social Media on Institution |
Less than 30 min. |
2.66±.96 |
.616 |
.605 |
– |
|
Between 31 – 60 min. |
3.61±1.10 |
||||
|
Between 61 – 120 min. |
2.71±1.06 |
||||
|
More than 2 hours |
2.92±1.07 |
||||
|
Institutional Sanctions |
Less than 30 min. |
2.43±1.11 |
.657 |
.579 |
– |
|
Between 31 – 60 min. |
2.23±1.01 |
||||
|
Between 61 – 120 min. |
2.29±1.14 |
||||
|
More than 2 hours |
2.31±1.29 |
||||
|
Representing Institution on Social Media |
Less than 30 min. |
2.41±.80 |
1.317 |
.269 |
– |
|
Between 31 – 60 min. |
2.38±.86 |
||||
|
Between 61 – 120 min. |
2.65±.80 |
||||
|
More than 2 hours |
2.48±.87 |
Differences between the times spent on social media per day in terms of using social media and institutional image were displayed in table 9. No significant differences were found between groups in terms of subscales (p>0.05).
Table 10. Correlations between age, title, working year, YUSM, TSSM, IS, ISMI, RISM
|
|
1 |
2 |
3 |
4 |
5 |
6 |
7 |
8 |
|
|
41.46±9.88 |
– |
– |
– |
– |
2.66±1.05 |
2.30±1.08 |
2.44±.83 |
|
1) Age |
1 |
.336** |
.533** |
-.056 |
-.181** |
.100 |
.224** |
.162** |
|
2) Title |
|
1 |
.113* |
-.141* |
-.232** |
.172** |
.157** |
.178** |
|
3) Working year |
|
|
1 |
-.003 |
-.081 |
-.035 |
.055 |
-.009 |
|
4) YUSM |
|
|
|
1 |
.291** |
-.053 |
-.205** |
-.088 |
|
5) TSSM |
|
|
|
|
1 |
.052 |
-.040 |
.068 |
|
6) ISMI |
|
|
|
|
|
1 |
.352** |
.588** |
|
7) IS |
|
|
|
|
|
|
1 |
.487** |
|
8) RISM |
|
|
|
|
|
|
|
1 |
TUSM= Year using social media, TSSM=Time spent on social media, ISMI= The Impacts of Social Media on Institution, IS= Institutional Sanctions, RISM= Representing Institution on Social Media
Correlations between age, title, working year, YUSM, TSSM, IS, ISMI, RISM were displayed in table 10. According to analysis, negative correlations were found between age and the time spent on social media per day (p<0.01, r=-.181), positive correlations were found between age and institutional sanctions (p<0.01, r=.224), Representing Institution on Social Media (p<0.01, r=.162). Negative correlations were found between title and year of using social media (p<0.05, r=-.141), the time spent on social media per day (p<0.01, r=-.232) while positive correlations were found between title and institutional sanctions (p<0.01, r=.157), Representing Institution on Social Media (p<0.01, r=.178). Negative correlations were found between year of using social media and institutional sanctions (p<0.01, r=-.205).
DISCUSSION
According to analysis between genders, statistically significant difference was found between genders in terms of institutional sanctions. Female academicians reported lower scores than males in terms of institutional sanctions. Eryilmaz and Zengin (2014) found no significant differences between genders in their study in which people staying in hotel participated. Islek (2012) examined the effect of social media on consumer behaviors.
Significant differences were found between age groups in terms of institutional sanctions and representing institution on social media. Academicians aged 51 years and over reported higher scores than those aged 30 years and under and between 31-40 years in terms of institutional sanctions while those aged over 51 years and over reported higher scores than those aged between 31-40 years in terms of representing institution on social media. Eryilmaz and Zengin (2014) found no significant differences between age groups. Eryilmaz and Zengin (2014) also found no significant differences between marital statuses.
While no significant differences were found between years of using social media in terms of the impacts of social media on institution and representing institution on social media (p>0.05), significant differences were found between years of using social media in terms of institutional sanctions (p<0.05, F=5.57). The academicians using social media for 1-3 years reported higher scores than those using it for 4-6 years and more than 7 years. ın the study conducted by Solmaz et al. (2013), participants reported they used social media every day. Vural and Bat (2010) examined the frequency of using social media by students and they reported that most of the participants used it every day. No significant differences were found between groups in terms of the impacts of social media on institution, institutional sanctions and representing institution on social media.
CONCLUSION
The competition conditions and the transformation of the world to a global village has changed the way of doing business and increased the importance of new communication technologies in terms of institutions. The social media has become an area where the employees of an institution can consistently communicate with the entire stakeholders of the institution considering utilization of new communication technologies such as websites and social networks to create institutional image obligatory (20). Institutions realizing this fact may bring limitations to using social media networks such as Facebook, Twitter, YouTube, and Instagram by setting policies how the employees use. On the other hand, the number of employees being dismissed because of comment and shares is increasing day by day. In this regard, it has become important how the institutional image is affected by social media usage of the employees.
More recently, it is know that some academicians have been under investigation, some have been suspended and some have been removed of public office. The most recent example to this is a research assistant, working at a public university in Eskisehir, who shared a comment in which there were severe statements for martyred soldiers and polices on social media. The university started investigation about this academician for the reflected statements including hate speeches and decided suspension. Afterwards, The Council of Higher Education decided to remove that academician of public office (http://www.hurriyet.com.tr/o-akademisyen-memurluktan-atildi-40106567). In another example, a professor working at state university in Aydin were decided to be suspended because of the shares about conquest of Istanbul (http://www.hurriyet.com.tr/istanbulun-fethini-elestiren-profesor-aciga-alindi-40111645).
Consequently, because universities make an effort to protect their institutional image in front of public, they can decide to suspend, investigate or remove the academicians sharing their political views including despiteful comments. As a result, these academicians may face some sanctions about their shares on social media. It has been found that professors have the highest scores about thinking to impose sanctions and check the social media. It can be concluded that this results may have result from that professors may be in the managerial duty more than the other academicians.
RECOMMENDATION
For institutions, while social media create important opportunities for advertisement, publicity and reaching target group, the shares of employees on social media can cause misunderstandings and result in important problems. Accordingly, the importance of preventing problems before they occur by checking social media accounts of employees on time increases.
The critical point here is that creating an institutional image for universities can be possible to ensure the academicians displaying attitudes and behaviors having parallels with the image. It can be said that it is important for providing and maintaining social peace not to do sharing including anger, hate, racism and it is also important that academicians who are the intelligentsia of the Turkish society should avoid actuator and incentive behaviors on social media.
Moreover, organizing seminars and conferences including information about how academic and administrative staff should use social media, what rules they should follow, how the language of social media should be is important to create, develop and maintain institutional image of universities. Future studies should include participant working different public and private sectors.
In this study, the major problem that we faced was finding literature for our results because there are limited studies including social media and institutional image.
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