Social Media Addiction and Social Skills: Implications for Societal Learning Systems, Technology, Social Economy, and Societal Challenges

Abstract

This study aims to examine the relationship between social media addiction and social skill levels of university students from the perspective of social learning systems, systems thinking and social economy. Furthermore, the objective is to reveal how these dynamics are related to larger challenges at the societal level. Social media addiction has emerged as an important factor shaping individuals’ social interactions, social participation and personal development. The population of the study consists of students studying at a university in Turkey, and the sample consists of 394 university students selected by convenience sampling method. The research was conducted using the relational survey model, with the data being collected through scales. The research was conducted using the relational survey model, with the data being collected through scales. The findings indicate that individuals experience a decline in social skill levels with the increase in social media use. Furthermore, an examination of the impact of demographic characteristics on this relationship utilized independent sample t-test and one-way ANOVA analyses, revealing that female students exhibited higher levels of social media addiction, while male students demonstrated higher levels of social skills. Moreover, the findings underscore the notion that social media addiction is not merely an individual problem, but rather a phenomenon that exerts influence on learning systems, social interactions and economic factors at the societal level. The impact of social media use on societal challenges and individual development can be more effectively understood through the utilization of a systems thinking approach. The current study offers significant implications for the manner in which social media addiction and social skills are shaped in the context of social learning systems, technology and the social economy and explores the social effects of social media addiction and suggests effective interventions in the fields of education, policy and social work. Systems thinking helps to understand addiction in a broad context.

1. Introduction

The prevailing trend of technological advancement has led to a notable increase in the amount of time individuals spend using technological devices [1]. Technological devices that we encounter every day provide great convenience in our daily life, education life, business life and communication. Thanks to the convenience they provide, the use of mobile phones, tablets and computers has become widespread [2]. This widespread use has also manifested itself in the applications in the mass communication tools used, and this has brought the concept of social media to the forefront [3].

The concept of social media can be defined as the way in which users with similar thoughts and ideas communicate with each other using web services [4]. With the uncontrolled use of social media, the concept of social media addiction has come to the fore [5]. Social media addiction is a psychological problem characterized by preoccupation with social media, imbalance in the emotion regulation process, repetition of the addiction process and the state of imbalance or conflict brought about by the situation that the individual is in [6].

University students’ competition with each other, increasing life problems, the development of technology day by day and the effort to keep up with this change, economic difficulties, psychological pressures or physical health problems can lead young people to the virtual world. These individuals may neglect their real-world relationships by spending more time on digital platforms and engaging in social interactions in virtual environments [7]. Therefore, while social media emphasizes the good aspects of technology as it is a free medium that is accessible at any time and free from restrictions, it also draws a reaction by harboring asociality within sociality [8].

Social media has become a platform that young people use frequently as a means of socializing. The number of social networks is increasing day by day, and thanks to the changes made in their use, they have become attractive for people of all ages to use. As a result of intensive use, psychosocial development has been negatively affected. Individuals interact with school, family and friends in a virtual environment. In such a situation, it becomes difficult to establish and maintain interpersonal relationships, and social skill development is negatively affected. Therefore, there is a linear relationship between the overuse of social media platforms and loneliness, depression and social performance [9].

Throughout history and across the globe, the significance of communication and social skills has remained constant, playing a pivotal role in every stage of life. Although there are periodic differences, human beings have continuously improved their development in order to get along. Although interpersonal relationships are important in every period, the increase in the number of nuclear families, the weakening of the relationship with other family members and the long duration of education life have made today’s society individualistic [10]. Social skills are all the accumulations necessary for people to try to transfer what they are going through to other parties in confidence by using verbal and behavioral skills in relationships, to solve problems that may occur while maintaining communication, to share mutual feelings, to fulfill responsibilities and to be placed in the necessary position in the human community [11]. In order to comprehend this complex and multidimensional structure, it is insufficient to see social media addiction only as an individual problem; this phenomenon should be considered as a systemic issue that emerges in the interaction of technology, social norms and economic factors. The systems thinking approach considers individual behavior as part of a complex system in which technology infrastructure, social norms and economic factors interact. The concepts of system dynamics and learning organizations facilitate the comprehension of the causes and consequences of social media addiction within the context of multi-layered feedback processes [12].

University students are a very important segment in increasing the socio-economic welfare of the country and making a breakthrough for the future. At this point, university students are the main force that will determine the future of our country. In this context, university students need to improve themselves and prepare themselves well for the future. Some of the skills they need to improve themselves are social skills, which are considered 21st-century skills. Nowadays, it is observed that young adults spend a significant part of their time on social media. When social media is used appropriately, it can be said that it is extremely useful for individuals in many aspects, especially the development of social skills. However, if social media addiction develops in university students, it can also have extremely harmful effects. Therefore, it is important to determine the social media addiction and social skill levels of these young adults at university and to examine the relationship between social media addiction and social skill levels. Therefore, this study examining the relationship between social media addiction and the social skill levels of university students will contribute to the literature.

2. Literature Review

2.1. Social Media and Social Media Addiction

Social media plays an important role in people’s communication activities. Although the concept of social media has many definitions in the literature, there is no common definition. In most of the definitions, it is emphasized that social content is shared through websites and created by the user [5]. Social media is a type of social communication that can be communicated and shared regardless of time and space. Social media enables individuals to communicate without coming face to face [13]. The interaction that can be established in the virtual environment facilitates people’s work. Social media is an internet-based platform where individuals can interact with others and share content [14]. In short, social media is the socialization environment of individuals.

Social media networks are a system that allows users to exchange content, create a personal profile with different users and interact with other users. The main purpose of using social media is to enable users to interact socially with each other [15]. For this purpose, the most frequently used social media applications such as Facebook, Instagram, X (Twitter), YouTube, TikTok, etc., provide opportunities for individuals to communicate among themselves, follow various interests of individuals, and share photos [16].

Social media provides users with opportunities such as communication environment, information exchange and entertainment activities and allows individuals to participate in various groups and activities related to their interests [17]. Social media consists of social networks where information communities coexist and disseminate this information among users [18].

Social media has transformed the processes of living, learning, working and communicating. Although each individual uses social media for different purposes, there are essentially common purposes for everyone. It is stated that social media platforms are generally used for socializing [19].

In a study conducted by Solmaz et al. on university students, it was determined that they use social media to make new friends and communicate with their existing friends. Subrahmanyam et al. also found that students use social media for messaging, posting on their profile and following their friends. It was found that the most common use of social media was to communicate with friends with whom users do not meet frequently [20]. If individuals cannot control themselves within the scope of the time they spend on social media, they may face the problem of social media addiction.

Addiction is defined as a condition that increases individual and social problems, causes the individual to lose control, and persists despite repeated attempts to quit and avoid a behavior [21].

The concept of social media addiction can be defined as the individual spending too much time on social media, this time gradually increasing, and the time spent on social media negatively affecting other functions of the person in daily life [22]. Social media addiction is the tendency to be online continuously and an individual’s difficulty in staying away from social media for more than an hour [23].

The main reason for being addicted to social media is that people who need to live collectively in society and cannot cope with individualization try to fill the feeling of loneliness and emptiness with social media communities [24]. Although there are many reasons both for the society and the individual, the ease of access to the internet and other tools with the development of technology is one of the reasons for this addiction [25]. Social activities, social relationships, responsibilities and even health may be harmed due to social media addiction [26].

Social media addiction is the inability to allocate time for daily tasks due to the use of social media above the optimum level and the inability to prevent this, the negative impact on social relations, the use of social media as a way to get away from negative emotions, the inability to stay away from social media and excessive stress when staying away [27]. Important symptoms of social media addiction are listed as follows [28,29,30,31]:

• Continuous desire to spend time on social media;
• Failure in social relationships;
• Feeling uneasy in case of not using social media;
• Negative impact on the individual’s family and work life;
• Lying to those around the individual about the duration of daily use of social media;
• Disruption in daily activities;
• Negative impact on academic success;
• Imbalance in the perception of reality due to virtual situations;
• Focus and perception problems;
• Failure in time management.

Social media addiction can lead to various problems. People who spend too much time on social media are more likely to compare themselves to others, leading to lower self-esteem [32]. Following the standards of living reflected on social media can lead to negative consequences such as depression, low self-esteem and asociality [33].

2.2. Concept of Social Skills

Human beings want to have behaviors that are socially accepted and that will enable interaction with other people. The basis of being able to interact with people is the ability to understand the emotions of others correctly and the ability to direct these emotions. This skill is called social ability [34]. The concept of social skills is a broad concept that includes the ability to establish positive relationships with other people, the ability to recognize and direct one’s own emotions, the ability to make one’s own decisions and to have the strength to stand behind these decisions, and the ability to act ethically and constructively [35]. Social skills can be defined as learned behaviors that enable individuals to receive positive feedback in the environments in which they interact, initiate social relationships and ensure their continuity [36].

Social skills are the most important skills for happiness and success both in private and professional life. Social skills include the activities of maintaining interpersonal relationships that start with appropriate behaviors accepted by the group and society [37]. At the same time, social skills positively affect the performance of individuals. According to Liberman (1986), the concept of social skills is the verbal and non-verbal interpersonal and cognitive behaviors that are necessary to survive in society and lead a life of appropriate quality [38]. Whether individuals have social skills or not can be understood from their behaviors in the process of social relations. Social skills contribute to the strengthening of social relations and adaptation to the environment [39].

Some of the social skills are listed as follows [35,38]:

• Recognizing emotions;
• Managing emotions;
• Expressing oneself;
• Empathizing;
• Establishing good interpersonal relationships;
• Motivating oneself;
• Regulating mood;
• Developing solutions to existing problems;
• Producing effective solutions in conflict situations;
• Adapting to conditions and environment.

It is argued that inadequacy in social skills arises from not acquiring the behaviors in this area, not finding alternative behaviors that can be used instead, using the wrong alternatives, not knowing how to use the acquired behaviors or not remembering them [40]. Individuals with well-developed social skills include many positive characteristics such as being accepted and loved in society, having high popularity, having no difficulty in acquiring an environment, being free from aggression, being able to control anger and having high problem-solving skills [41]. Therefore, social skills include observable behaviors in social interaction [42]. Those with social skill deficiency may experience problems such as anxiety, depression, asociality, academic failure, thoughts of not continuing their education, social relationship problems, sleep disorders, irregular nutrition and substance abuse [43].

Riggio (1986) examined social skills in depth by dividing them into different groups and subheadings and explained social skills in six sub-dimensions [44,45]:

Emotional Expressivity: This dimension is related to a person’s non-verbal communication skills. People with high emotional expressivity have cheerful, lively and energetic characteristics. With these characteristics, they can easily influence others.

Emotional Sensitivity: The ability to understand and interpret other individuals’ non-verbal messages is an essential component of human interaction and communication. Furthermore, individuals with emotional sensitivity have the capacity to accurately, rapidly and comprehensively discern the emotional states of others. Furthermore, these individuals are also sensitive to the feelings of others. The emotional communication exhibited by these individuals is characterized by its adequacy and expediency.

Emotional Control: This is the individual’s ability to regulate and control non-verbal messages and emotions. People with this skill are successful in controlling their emotions. Such people tend to control their emotions instead of showing their emotions directly. They can express their emotions when necessary and hide them when necessary. These people are characterized as good emotional actors and have emotions appropriate to the situation.

Social Expressivity: This can be expressed as the ability to speak verbally and the ability to engage in social communication with others. People with social expressivity skills are self-confident, extroverted, sincere and comfortable speakers.

Social Sensitivity: This is the ability to interpret the verbal communication of others. It also refers to an individual’s sensitivity and understanding of the norms that determine appropriate social behavior. It involves individuals’ knowledge of norms of appropriate social behavior and their ability to perceive verbal communication. These individuals are generally polite to others, and at the same time, they are good observers and listeners. At this point, it can be said that these individuals have knowledge about social rules.

Social Control: This is the ability to be self-confident in social settings, to play social roles and to adjust oneself. People with this skill can easily adapt to all kinds of social situations. Social control is also important in guiding the content and direction of communication in social interaction.

Based on the idea that those with high levels of social media addiction may have low levels of social skills, this study examined the relationship between social media addiction and social skills.

3. Materials and Methods

In this section of the study, information about the purpose and importance of the research, the model of the research, the hypotheses of the research, the population and sample of the research, the data collection tools used in the research and data analysis is given.

3.1. Purpose of the Study

This study aims to examine the relationship between social media addiction and social skill levels of university students from the perspective of social learning systems, systems thinking and social economy. Furthermore, the objective is to reveal how these dynamics are related to larger challenges at the societal level.

3.2. Research Model

The relational and descriptive survey model, one of the quantitative research methods, was used as the research technique. The relational survey model is the model used by researchers to measure the level of a relationship between two or more variables [46]. The model shown in Figure 1 was created to determine the relationship between the social media addiction levels and social skill levels of university students and whether there is a significant difference in social media addiction and social skill levels according to demographic characteristics.

The hypotheses formed in line with the purpose and model of the study are as follows:

Hypothesis 1. 

University students have a high level of social media addiction.

Hypothesis 2. 

University students have low levels of social skills.

Hypothesis 3. 

There is a significant and negative relationship between social media addiction and its sub-dimensions (social tolerance, social communication) and social skills and their sub-dimensions (social sensitivity, affective sensitivity, social expressiveness, affective expressiveness, social control, affective control).

Hypothesis 4. 

The social media addictions of university students differ according to demographic characteristics (gender, age, academic unit, grade level, family income).

Hypothesis 5. 

The social media addictions of university students differ according to daily social media usage time.

Hypothesis 6. 

The social media addictions of university students differ according to the social media application they use the most.

Hypothesis 7. 

The social skills of university students differ according to demographic characteristics (gender, age, academic unit, grade level, family income).

Hypothesis 8. 

The social skills of university students differ according to the duration of daily social media use.

Hypothesis 9. 

The social skills of university students differ according to the social media application they use the most.

3.3. Population and Sample of the Study

The population of the study consists of 2610 students studying at Manisa Celal Bayar University Salihli Vocational School and Salihli Faculty of Economics and Administrative Sciences in the spring semester of the 2024–2025 academic year. The sample consists of 394 volunteer students, 218 female and 176 male, determined by a convenience sampling method. In total, 15.1% of the research population was reached.

3.4. Data Collection Tools

The survey method was used to collect data in the study. The questionnaire used in the research consists of 3 parts. The first part of the data collection tool includes the “Personal Information Form” created by the researcher to determine the demographic information of the participants in the study. In the second part, the “Social Media Addiction Scale—Adult Form” was used, and in the third part, the “Social Skill Level Scale” was used. Permission was obtained from the relevant authors for the scales.

3.4.1. Social Media Addiction Scale—Adult Form (SMAS-AF)

This scale was developedto determine the social media addiction levels of adults aged 18–65 [47].

Within the framework of the validity studies, exploratory and confirmatory analyses were conducted, and it was determined that the SMAS-AAD has a five-point Likert-type structure consisting of 2 sub-dimensions (virtual tolerance and virtual communication) and 20 descriptions. The virtual tolerance sub-dimension consists of items 1–11, and virtual communication consists of items 12–20. Items 5 and 11 are reverse-scored. The Cronbach Alpha internal consistency coefficient was 0.94 for the overall scale, 0.92 for virtual tolerance and 0.91 for virtual communication. The test–retest reliability coefficients were 0.93 for the overall scale, 0.91 for virtual tolerance and 0.90 for virtual communication. The analyses revealed that the SMBS-SF is a valid and reliable scale for determining adults’ social media addiction. The highest score that can be obtained from the scale is 100, and the lowest score is 20. A high score indicates that the individual perceives himself/herself as a “social media addict” [47].

3.4.2. Social Skills Inventory—Short Form (SSI-SF)

In the study, the Social Skills Inventory—Short Form (SSI-SF) was used to determine the social skill levels of university students [44,48,49]. The scale consists of 6 dimensions and 30 items. Cronbach’s alpha coefficient was obtained for the total scale. A value of 85 was found to be 85%. The scale measures social skill levels with its main dimensions. The scale analyzes 6 basic social skill traits: social expressiveness, social sensitivity, social control, emotional expressiveness, emotional sensitivity and emotional control. Of the 30 items that make up the scale, items 1, 3, 7, 9, 12, 13, 18, 25 and 27 are reverse-scored. As the scores of the individuals increase, their social skill levels also increase.

3.5. Reliability Analysis of Scales

Cronbach Alpha values of the scales between 0.70 and 0.99 indicate that the scales are reliable [50]. Both scales used in this study are within these reliability limits (

Table 1. Results of reliability analysis of scales.

Scales	Cronbach’s Alpha	No. of Items
Social Tolerance	0.78	11
Social Communication	0.83	9
Social Media Addiction Total	0.87	20
Emotional Expressivity	0.73	5
Emotional Sensitivity	0.70	5
Emotional Control	0.81	5
Social Expressivity	0.74	5
Social Sensitivity	0.69	5
Social Control	0.72	5
Social Skill Total	0.79	30

).

3.6. Data Analysis

Data collected through the survey method was analyzed using the SPSS (Statistical Package for Social Science Version 26) program. In the study, distribution analysis, descriptive statistics, normality tests, Pearson correlation analysis, independent sample t-tests and one-way ANOVA were performed. The results were evaluated at a significance level of 95% (p < 0.05).

4. Findings

Under this heading, the findings obtained as a result of the analysis of the data are categorized and presented in tables.

4.1. Findings Regarding Demographic Characteristics

In order to determine the demographic characteristics of the participants, questions were asked including gender, age, unit, class, monthly income status, daily social media usage time and the most used social media application (

Table 2. Distribution of participants according to demographic characteristics.

Variables	Group	n	%
Gender	Female	218	55.3
	Male	176	44.7
Age	18–20	230	58.4
	21–23	126	32
	24 and over	38	9.6
Academic Unit	Salihli VS	228	57.9
	Salihli FEAS	166	42.1
Grade Level	1st grade	162	41.1
	2nd grade	136	34.5
	3rd grade	54	13.7
	4th grade	42	10.7
Monthly Income	Very low	30	7.6
	Low	58	14.7
	Middle	290	73.6
	High	10	2.5
	Very High	6	1.5
Daily Social Media Usage Time	Less than 1 h	6	1.5
	1–2 h	52	13.2
	3–4 h	176	44.7
	4 h and over	160	40.6
Most Used Social Media	Facebook	10	2.5
	WhatsApp	8	2
	X (Twitter)	40	10.2
	TikTok	32	8.1
	YouTube	20	5.1
	Instagram	284	72.1

).

As seen in Table 2, 394 students, 218 (55.3%) female and 176 (44.3%) male, participated in the study.

The distribution according to age is as follows: 230 (58.4%) of the participants are between the ages of 18 and 20, 126 (32%) are between the ages of 21 and 23, and 38 (9.6%) are 24 and over.

The distribution of the participants in terms of academic unit is as follows: 228 (57.9%) of the participants are students of Salihli Vocational School and, 166 (42.1%) are students of Salihli Faculty of Economics and Administrative Sciences.

The distribution by grade level is as follows: 162 (41.1%) of the participants are first-year students, 136 (34.5%) are second-year students, 54 (13.7%) are third-year students and 42 (10.7%) are fourth-year students.

The distribution of participants’ family monthly income is as follows: 290 (73.6%) participants are at the middle income level, 58 (14.7%) participants are at the low income level, 30 (7.6%) participants are at the very low income level, 10 (2.5%) participants are at the high income level and 8 (1.5%) participants are at the very high income level.

The distribution of the frequency of daily social media use of the participants is as follows: 176 (44.7%) of the participants used social media for 3–4 h, 160 (40.6%) for 4 h or more, 52 (13.2%) for 1–2 h, and 6 (1.5%) for less than 1 h.

The majority of participants (72.1%, n = 284) reported Instagram as their most frequently used social media platform. This was followed by X (formerly Twitter) (10.2%, n = 40), TikTok (8.1%, n = 32), YouTube (5.1%, n = 20), Facebook (2.5%, n = 10) and WhatsApp (2.0%, n = 8).

4.2. Descriptive Statistical Analysis Results of the Scales

The descriptive statistical analysis results of the scales used in the study, namely the mean, standard deviation, minimum value, maximum value, skewness, standard deviation of skewness, kurtosis and standard deviation of kurtosis, are given in

Table 3. Descriptive statistics, skewness and kurtosis values of the social media addiction scale.

Dimensions	n	Mean	SD	Min	Max	Skewness	SD	Kurtosis	SD
Social Tolerance	394	2.96	0.712	1.36	4.73	−0.017	0.123	−0.276	0.245
Social Communication	394	2.52	0.789	1.00	5.00	0.446	0.123	0.138	0.245
Social Media Addiction Total	394	2.76	0.663	1.40	4.60	−0.314	0.123	−0.146	0.245

and

Table 4. Descriptive statistics, skewness and kurtosis values of the social skill scale.

Dimensions	n	Mean	SD	Min	Max	Skewness	SD	Kurtosis	SD
Emotional Expressivity	394	3.05	0.652	1	5	−0.198	0.123	−0.558	0.245
Emotional Sensitivity	394	3.53	0.840	1	5	−0.099	0.123	−0.623	0.245
Emotional Control	394	3.23	0.785	1	5	−0.394	0.123	−0.016	0.245
Social Expressivity	394	3.26	0.916	1	5	−0.083	0.123	−0.682	0.245
Social Sensitivity	394	2.60	0.873	1	5	−0.400	0.123	−0.445	0.245
Social Control	394	3.40	0.693	1	5	0.075	0.123	−0.162	0.245
Social Skill Total	394	3.17	0.420	2.07	3.17	0.216	0.123	−0.309	0.245

.

As seen in Table 3, the mean of the participants’ SMAS-AF was 2.76 ± 0.663 (skewness: −0.314 ± 0.123; kurtosis: −0.146 ± 0.245); the mean of virtual tolerance, one of the sub-dimensions of the SMAS-AF was 2.96 ± 0.712 (skewness: −0.017 ± 0.123; kurtosis: −0.276 ± 0.245); and the mean of virtual communication: 2.52 ± 0.789 (skewness: 0.446 ± 0.123; kurtosis: −0.138 ± 0.245). According to the normality test results of the social media addiction scale, it is seen that the total values of skewness and kurtosis are in the range of ±1.5. When skewness and kurtosis values are within the ±1.5 range, it is accepted that the data are normally distributed [51]. Therefore, parametric statistical analyses were applied in the study. According to the results, hypothesis H1 is rejected.

As seen in Table 4, the participants’ total mean for social skills is 3.17 ± 0.420 (skewness: 0.216 ± 0.123; kurtosis: −0.309 ± 0.245); mean of affective expressiveness, one of the sub-dimensions of social skills, 3.05 ± 0.652 (skewness: −0.198 ± 0.123; kurtosis: −0.558 ± 0.245); mean of affective sensitivity, 3.53 ± 0.840 (skewness: −0.099 ± 0.123; kurtosis −0.623 ± 0.245); mean of affective control, 3.23 ± 0.785 (skewness: −0.394 ± 0.123; kurtosis −0.016 ± 0.245); mean of social expressiveness, 3.26 ± 0.916 (skewness: −0.083 ± 0.123; kurtosis −0.682 ± 0.245); mean of social sensitivity, 2.60 ± 0.873 (skewness: −0.400 ± 0.123; kurtosis: −0.445 ± 0.245); and mean of social control, 3.40 ± 0.693 (skewness: −0.075 ± 0.123; kurtosis: −0.162 ± 0.245). According to the normality test results of the social skill scale; it is seen that the total values of skewness and kurtosis are within the range of ±1.5. When skewness and kurtosis values are within the ±1.5 range, it is accepted that the data are normally distributed [51]. Therefore, parametric statistical analyses were applied in the study. According to the results, hypothesis H2 is rejected.

4.3. Correlation Analysis Findings Between Variables

Correlation analysis was conducted to determine the relationship between social media addiction and social skills. The results of the Pearson correlation analysis are given in

Table 5. The relationship between participants’ social media addiction and social skills.

Variables	Social Tolerance	Social Communication	Social Media Addiction Total
Emotional Expressivity	0.084	0.082	0.093
Emotional Sensitivity	052	0.002	0.032
Emotional Control	−0.268 **	−0.149 **	−0.238 **
Social Expressivity	−0.218 **	−0.129 **	−0.205 **
Social Sensitivity	−0.334 **	−0.400 **	−0.379 **
Social Control	−0.249 **	−0.293 **	−0.272 **
Social Skill Total	−0.303 **	−0.195 **	−0.338 **

** p < 0.001.

.

According to the results of Pearson correlation analysis, there was a significant and inverse relationship between social media addiction and social skills (r = −0.338 **, p < −0.001). According to this result, it can be said that as the level of social media addiction increases, students’ social skill levels decrease.

Significant and inverse relationships were found between social tolerance, one of the sub-dimensions of social media addiction, and social sensitivity (r = −0.334 **, p < −0.001), social expressiveness (r = −0.218 **, p < −0.001), social control (r = −0.249 **, p < 0.001) and affective control (r = −0.268 **, p < −0.001). According to this result, it can be said that as the level of social tolerance increases, students’ social sensitivity, social expressiveness, social control and affective control levels decrease.

Significant and inverse relationships were found between social communication, one of the sub-dimensions of social media addiction, and social sensitivity (r = −0.400 **, p < 0.001), social expressiveness (r = −0.129 **, p < 0.001), social control (r = −0.293 **, p < 0.001) and affective control (r = −0.149 **, p < 0.001), which are sub-dimensions of social skills. According to this result, it can be said that as the level of social communication increases, students’ social sensitivity, social expressiveness, social control and affective control levels decrease.

No significant relationship was found between social media addiction and its sub-dimensions and the affective sensitivity and affective expressiveness sub-dimensions of social skills. According to this result, it can be said that social media addiction has no effect on affective sensitivity and affective expressiveness.

4.4. Difference Analysis Findings

In our study, it was examined whether the mean scores of social media addiction and social skills differed depending on the demographic characteristics of the students participating in the study. Correlation analysis, t-tests (Independent Two-Group t-tests) and one-way analysis of variance (ANOVA) were used to test the hypotheses.

4.5. Difference Analysis Findings of Social Media Addiction Regarding Demographic Characteristics and Social Media Use

As shown in

Table 6. t-test results of social media addiction and its sub-dimensions by gender.

Dimensions	Groups	n	Mean	SD	df	t	p
Social Tolerance	Female	218	2.96	0.685	392	−0.080	0.123
	Male	176	2.97	0.746
Social Communication	Female	218	2.47	0.761	392	−0.687	0.115
	Male	176	2.57	0.820
Social Media Addiction Total	Female	218	2.74	0.634	392	−0.694	0.026
	Male	176	2.78	0.699

, while no statistically significant difference was found in the social tolerance and social communication sub-dimensions of social media addiction according to gender (p > 0.05), a statistically significant difference was found in the total score of social media addiction according to gender (p < 0.05).

The reason for the significant difference is that male students have higher total social media addiction scores than female students.

As seen in

Table 7. ANOVA results of social media addiction and its sub-dimensions by age groups.

Dimensions	Source of Variance	Sum of Squares	df	Mean Square	F	p
Social Tolerance	Between Groups	0.446	2	0.223	0.439	0.645
	Within Groups	198.563	391	0.508
	Total	199.009	393
Social Communication	Between Groups	0.783	2	0.391	0.628	0.534
	Within Groups	243.576	391	0.623
	Total	244.359	393
Social Media Addiction Total	Between Groups	0.574	2	0.287	0.652	0.522
	Within Groups	172.302	391	0.441
	Total	172.876	393

, no statistically significant difference was found in social media addiction and its sub-dimensions according to the age range of the participants (p > 0.05).

As seen in

Table 8. t-test results of social media addiction and its sub-dimensions regarding academic unit.

Dimensions	Groups	n	Mean	SD	df	t	p
Social Tolerance	Salihli VS	228	2.91	0.705	392	−1.856	0.961
	Salihli FEAS	166	3.04	0.715
Social Communication	Salihli VS	228	2.51	0.879	392	−0.220	0.001
	Salihli FEAS	166	2.53	0.645
Social Media Addiction Total	Salihli VS	228	2.73	0.702	392	−1.210	0.261
	Salihli FEAS	166	2.81	0.604

, no statistically significant difference was found in the total social media addiction and social tolerance sub-dimension according to academic unit (p > 0.05). A statistically significant difference was found in the social communication dimension according to the unit (p < 0.05).

The reason for the significant difference is that the social communication scores of the students of Salihli Faculty of Economics and Administrative Sciences are higher than the scores of the students of Salihli Vocational School.

As seen in

Table 9. ANOVA results of social media addiction and its sub-dimensions by grade level.

Dimensions	Source of Variance	Sum of Squares	df	Mean Square	F	p
Social Tolerance	Between Groups	4.842	3	1.614	3.242	0.022
	Within Groups	194.167	390	0.498
	Total	199.009	393
Social Communication	Between Groups	3.412	3	1.137	1.841	0.139
	Within Groups	240.947	390	0.618
	Total	244.359	393
Social Media Addiction Total	Between Groups	3.246	3	1.082	2.488	0.060
	Within Groups	169.630	390	0.435
	Total	172.876	393

, no statistically significant difference was found in the social media addiction and social communication dimension of the participants according to their grade levels (p > 0.05). A statistically significant difference was found in the social tolerance dimension (p < 0.05).

In the Tukey test conducted for the class level variable, it was determined that there was a significant difference between third- and fourth-year students. Accordingly, while the social tolerance score of third-year students is at the lowest level, the social tolerance score of fourth-year students is at the highest level.

As seen in

Table 10. ANOVA of social media addiction and its sub-dimensions in relation to monthly income status.

Dimensions	Source of Variance	Sum of Squares	df	Mean Square	F	p
Social Tolerance	Between Groups	0.773	4	0.193	0.379	0.824
	Within Groups	198.236	389	0.510
	Total	199.009	393
Social Communication	Between Groups	4.282	4	1.070	1.734	0.142
	Within Groups	240.077	389	0.617
	Total	244.359	393
Social Media Addiction Total	Between Groups	0.868	4	0.217	0.491	0.742
	Within Groups	172.008	389	0.442
	Total	172.876	393

, no statistically significant difference was found in the total social media addiction and the social tolerance and social communication sub-dimensions of the students participating in the study according to the monthly income variable (p > 0.05).

According to the results of the analysis on whether social media addiction differs according to demographic characteristics, as seen in

Table 11. ANOVA results of social media addiction and its sub-dimensions regarding daily social media use duration.

Dimensions	Source of Variance	Sum of Squares	df	Mean Square	F	p
Social Tolerance	Between Groups	41.621	3	13.874	34.379	0.000
	Within Groups	157.387	390	0.404
	Total	199.009	393
Social Communication	Between Groups	26.179	3	8.726	15.598	0.000
	Within Groups	218.180	390	0.559
	Total	244.359	393
Social Media Addiction Total	Between Groups	33.972	3	11.324	31.795	0.000
	Within Groups	138.904	390	0.356
	Total	172.876	393

, a statistically significant difference was found according to the daily social media usage time of the participants in the study regarding social media addiction and its sub-dimensions, social tolerance and social communication (p < 0.05). In the Tukey test conducted on the daily social media usage time variable, it was determined that there was a significant difference between students who used social media less than 1 h a day and students who used social media for 4 h or more. Accordingly, students who use social media less than 1 h a day have the lowest scores in total social media addiction, social tolerance and social communication sub-dimensions, while students who use social media for 4 h or more have the highest scores.

As seen in

Table 12. ANOVA results of social media addiction and its sub-dimensions regarding which social media platform is used the most.

Dimensions	Source of Variance	Sum of Squares	df	Mean Square	F	p
Social Tolerance	Between Groups	4.630	5	0.926	1.848	0.103
	Within Groups	194.379	388	0.501
	Total	199.009	393
Social Communication	Between Groups	1.746	5	0.349	0.558	0.732
	Within Groups	242.613	388	0.625
	Total	244.359	393
Social Media Addiction Total	Between Groups	2.258	5	0.452	1.027	0.401
	Within Groups	170.618	388	0.440
	Total	172.876	393

, no statistically significant difference was found in the total social media addiction and the social tolerance and social communication sub-dimensions of the students participating in the study according to the variable of which social media platform is used the most (p > 0.05).

4.6. Difference Analysis Findings of Social Skills Regarding Demographic Characteristics and Social Media Use

As seen in

Table 13. t-test results of social skills and sub-dimensions by gender.

Dimensions	Groups	n	Mean	SD	df	t	p
Emotional Expressivity	Female	218	3.05	0.695	392	0.021	0.075
	Male	176	3.05	0.596
Emotional Sensitivity	Female	218	3.51	0.872	392	−0.484	0.607
	Male	176	3.55	0.800
Emotional Control	Female	218	3.20	0.786	392	−0.932	0.865
	Male	176	3.27	0.782
Social Expressivity	Female	218	3.19	0.940	392	−1.571	0.081
	Male	176	3.34	0.879
Social Sensitivity	Female	218	2.50	0.858	392	−2.450	0.015
	Male	176	2.72	0.878
Social Control	Female	218	3.35	0.650	392	0.245	0.018
	Male	176	3.33	0.744
Social Skill Total	Female	218	3.13	0.419	392	−1.798	0.073
	Male	176	3.21	0.417

, while no statistically significant difference was found in the total social skill score and the affective expressiveness, affective sensitivity, affective control and social expressiveness sub-dimensions according to gender (p > 0.05), a statistically significant difference was found in the social sensitivity and social control sub-dimensions (p < 0.05). When the reason for the significant difference is examined, it is seen that the average scores of female students are higher than male students in the social sensitivity sub-dimension, and the average scores of male students are higher than female students in the social control sub-dimension.

As seen in

Table 14. ANOVA results of social skills and sub-dimensions by age intervals.

Dimensions	Source of Variance	Sum of Squares	df	Mean Square	F	p
Emotional Expressivity	Between Groups	3.972	2	1.986	4.754	0.009
	Within Groups	163.333	391	0.418
	Total	167.305	393
Emotional Sensitivity	Between Groups	1.123	2	0.562	0.794	0.453
	Within Groups	276.493	391	0.707
	Total	277.616	393
Emotional Control	Between Groups	4.908	2	2.454	4.047	0.018
	Within Groups	237.071	391	0.606
	Total	241.978	393
Social Expressivity	Between Groups	4.248	2	2.124	2.553	0.079
	Within Groups	325.323	391	0.832
	Total	329.572	393
Social Sensitivity	Between Groups	3.494	2	1.747	2.307	0.101
	Within Groups	296.105	391	0.757
	Total	299.600	393
Social Control	Between Groups	3.221	2	1.611	3.394	0.035
	Within Groups	185.557	391	0.475
	Total	188.778	393
Social Skill Total	Between Groups	0.441	2	0.221	1.253	0.287
	Within Groups	68.837	391	0.176
	Total	69.278	393

, while no statistically significant difference was found in the total social skill score and the affective sensitivity, social expressiveness and social sensitivity sub-dimensions (p > 0.05), a statistically significant difference was found in the affective expressiveness, affective control and social control sub-dimensions (p < 0.05). When Tukey test results were examined to determine the reason for the significant difference, it was found that there was a significant difference between the age ranges of 18–20 and 21–23 (18–20 age range scores higher) in the affective expressiveness and social control sub-dimensions, and between the age ranges of 18–20 and 21–23 (21–23 age range scores higher) in the affective sub-dimension.

As seen in

Table 15. t-test results of social skills and sub-dimensions by academic unit.

Dimensions	Groups	n	Mean	SD	df	t	p
Emotional Expressivity	Salihli VS	228	3.06	0.572	392	0.442	0.000
	Salihli FEAS	166	3.03	0.750
Emotional Sensitivity	Salihli VS	228	3.40	0.875	392	−3.556	0.026
	Salihli FEAS	166	3.70	0.757
Emotional Control	Salihli VS	228	3.20	0.774	392	−0.768	0.286
	Salihli FEAS	166	3.27	0.799
Social Expressivity	Salihli VS	228	3.20	0.897	392	−1.420	0.156
	Salihli FEAS	166	3.33	0.936
Social Sensitivity	Salihli VS	228	2.52	0.847	392	−2.038	0.042
	Salihli FEAS	166	2.70	0.899
Social Control	Salihli VS	228	3.30	0.656	392	−1.491	0.137
	Salihli FEAS	166	3.40	0.738
Social Skill Total	Salihli VS	228	3.11	0.385	392	−2.951	0.003
	Salihli FEAS	166	3.24	0.453

, while there was no statistically significant difference in the affective control, social expressiveness and social control sub-dimensions according to academic unit (p > 0.05), there was a statistically significant difference in the social skill total score and the affective expressiveness, affective sensitivity and social sensitivity sub-dimensions (p < 0.05).

When the reason for the significant difference is examined, it is seen that the scores of Salihli FEAS students are higher than those of Salihli Vocational School students in the affective sensitivity and social sensitivity sub-dimensions, and the scores of Salihli Vocational School students are higher than Salihli FEAS students in the affective expressiveness sub-dimension.

As seen in

Table 16. ANOVA results of social skills and sub-dimensions related to grade levels.

Dimensions	Source of Variance	Sum of Squares	df	Mean Square	F	p
Emotional Expressivity	Between Groups	2.399	3	0.800	1.892	0.130
	Within Groups	164.905	390	0.423
	Total	167.305	393
Emotional Sensitivity	Between Groups	2.995	3	0.998	1.418	0.237
	Within Groups	274.622	390	0.704
	Total	277.616	393
Emotional Control	Between Groups	14.574	3	4.858	8.331	0.000
	Within Groups	227.405	390	0.583
	Total	241.978	393
Social Expressivity	Between Groups	1.543	3	0.514	0.611	0.608
	Within Groups	328.029	390	0.841
	Total	329.572	393
Social Sensitivity	Between Groups	1.082	3	0.361	0.471	0.703
	Within Groups	298.518	390	0.765
	Total	299.600	393
Social Control	Between Groups	1.057	3	0.352	0.732	0.533
	Within Groups	187.721	390	0.481
	Total	188.778	393
Social Skill Total	Between Groups	446.597	3	148.866	0.938	0.422
	Within Groups	61,903.393	390	158.727
	Total	62,349.990	393

, while no statistically significant difference was found in the total social skill score and the affective expressiveness, affective sensitivity, social expressiveness, social sensitivity and social control sub-dimensions according to grade level (p > 0.05), a statistically significant difference was found in the affective control sub-dimension (p < 0.05). When the Tukey test results were analyzed to determine the reason for the significant difference, it was seen that there was a difference between the first year and other years. Accordingly, the affective control sub-dimension score of the participants studying in the first year is lower than that for all other years.

As seen in

Table 17. ANOVA results of social skills and sub-dimensions related to family income status.

Dimensions	Source of Variance	Sum of Squares	df	Mean Square	F	p
Emotional Expressivity	Between Groups	1.384	4	0.346	0.811	0.518
	Within Groups	165.920	389	0.427
	Total	167.305	393
Emotional Sensitivity	Between Groups	5.136	4	1.284	1.833	0.122
	Within Groups	272.480	389	0.700
	Total	277.616	393
Emotional Control	Between Groups	3.185	4	0.796	1.297	0.271
	Within Groups	238.794	389	0.614
	Total	241.978	393
Social Expressivity	Between Groups	6.126	4	1.532	1.842	0.120
	Within Groups	323.445	389	0.831
	Total	329.572	393
Social Sensitivity	Between Groups	5.029	4	1.257	1.660	0.159
	Within Groups	294.571	389	0.757
	Total	299.600	393
Social Control	Between Groups	1.991	4	0.498	1.037	0.388
	Within Groups	186.787	389	0.480
	Total	188.778	393
Social Skill Total	Between Groups	0.986	4	0.247	1.405	0.232
	Within Groups	68.291	389	0.176
	Total	69.278	393

, no statistically significant difference was found in the total and sub-dimensions of social skills of the participants according to family income status (p > 0.05).

As seen in

Table 18. ANOVA results of social skills and their sub-dimensions regarding daily social media use duration.

Dimensions	Source of Variance	Sum of Squares	df	Mean Square	F	p
Emotional Expressivity	Between Groups	6.133	3	2.044	4.947	0.002
	Within Groups	161.172	390	0.413
	Total	167.305	393
Emotional Sensitivity	Between Groups	6.253	3	2.084	2.996	0.031
	Within Groups	271.363	390	0.696
	Total	277.616	393
Emotional Control	Between Groups	9.266	3	3.089	5.176	0.002
	Within Groups	232.713	390	0.597
	Total	241.978	393
Social Expressivity	Between Groups	2.900	3	0.967	1.154	0.327
	Within Groups	326.672	390	0.838
	Total	329.572	393
Social Sensitivity	Between Groups	9.018	3	3.006	4.034	0.008
	Within Groups	290.582	390	0.745
	Total	299.600	393
Social Control	Between Groups	3.426	3	1.142	2.403	0.067
	Within Groups	185.352	390	0.475
	Total	188.778	393
Social Skill Total	Between Groups	0.883	3	0.294	1.678	0.171
	Within Groups	68.395	390	0.175
	Total	69.278	393

, there was no statistically significant difference (p > 0.05) in the social skill total score and the social expressiveness and social control sub-dimensions, while there was a statistically significant difference (p < 0.05) in the affective expressiveness, affective sensitivity, affective control and social sensitivity sub-dimensions according to the duration of daily social media use.

When the Tukey test results were analyzed to determine the reason for the significant difference, it was seen that there was a significant difference between students who used social media for less than 1 h and those who used it for 4 h or more.

Accordingly, while the scores of the students who use social media for 4 h or more per day in the affective expressiveness, affective sensitivity and affective control sub-dimensions are higher, the scores of the students who use social media for less than 1 h per day in the social control sub-dimension are higher.

As seen in

Table 19. ANOVA results of social skills and their sub-dimensions regarding which social media platform is used the most.

Dimensions	Source of Variance	Sum of Squares	df	Mean Square	F	p
Emotional Expressivity	Between Groups	3.973	5	0.795	1.888	0.095
	Within Groups	163.332	388	0.421
	Total	167.305	393
Emotional Sensitivity	Between Groups	7.738	5	1.548	2.225	0.051
	Within Groups	269.878	388	0.696
	Total	277.616	393
Emotional Control	Between Groups	10.915	5	2.183	3.666	0.003
	Within Groups	231.064	388	0.596
	Total	241.978	393
Social Expressivity	Between Groups	8.559	5	1.712	2.069	0.068
	Within Groups	321.012	388	0.827
	Total	329.572	393
Social Sensitivity	Between Groups	5.241	5	1.048	1.382	0.230
	Within Groups	294.358	388	0.759
	Total	299.600	393
Social Control	Between Groups	4.142	5	0.828	1.741	0.124
	Within Groups	184.636	388	0.476
	Total	188.778	393
Social Skill Total	Between Groups	0.360	5	0.072	0.406	0.845
	Within Groups	68.918	388	0.178
	Total	69.278	393

, while there was no statistically significant difference in the total social skill score and the emotional expressiveness, social expressiveness, social sensitivity and social control sub-dimensions (p > 0.05), there was a statistically significant difference in the emotional sensitivity and emotional control sub-dimensions (p < 0.05).

When Tukey test results were analyzed to determine the reason for the significant difference, it was observed that there was a significant difference between Facebook users and Instagram users (Instagram users had higher scores) in the affective sensitivity sub-dimension and between TikTok and YouTube users and Instagram users (Instagram users had higher scores) in the affective control sub-dimension. The results of the tested hypotheses are listed in

Table 20. Results regarding research hypotheses.

Hypotheses	Results
H1: University students have high levels of social media addiction.	Rejected
H2: University students have low levels of social skills.	Rejected
H3: There is a significant and negative relationship between social media addiction and its sub-dimensions (social tolerance, social communication) and social skills and their sub-dimensions (social sensitivity, affective sensitivity, social expressiveness, affective expressiveness, social control, affective control).	Supported
H4: The social media addictions of university students differ according to demographic characteristics (gender, age, academic unit, grade level, family income).	Partially Supported
H5: The social media addictions of university students differ according to daily social media usage time.	Supported
H6: The social media addictions of university students differ according to the social media application they use the most.	Supported
H7: The social skills of university students differ according to demographic characteristics (gender, age, academic unit, grade level, family income).	Partially Supported
H8: The social skills of university students differ according to the duration of daily social media use.	Partially Supported
H9: The social skills of university students differ according to the social media application they use the most.	Partially Supported

.

5. Discussion, Conclusions and Recommendations

Today, social media use is very common, especially among young people. Social media addiction is a type of behavioral addiction caused by the excessive use of social media. Social skill is an individual’s ability to establish and maintain social relationships. It is thought that individuals with high social media addiction will have low social skill levels. In this section, the results obtained by considering the hypotheses of the study will be interpreted by comparing them with the results of similar studies in the literature.

In the literature, the relationship between social media addiction and social skills is often treated as a complex interaction. Many studies have revealed that social media use can negatively affect social skill development, especially among teenagers and university students [3,6,8]. These studies emphasize that social media addiction can lead to a decrease in face-to-face interaction skills and the formation of more superficial social relationships. In addition, it has been stated that technology and digital environments can negatively affect individuals’ social skills such as empathy, communication and problem solving [22]. However, some studies also indicate that social media can contribute to the development of social skills, especially in areas such as social participation and information sharing [52]. These contradictory findings suggest that the individual and societal effects of social media use should be examined in a broader context. In our study, the negative effects of social media addiction on social skills were confirmed among university students in parallel with the existing findings in the literature.

In the study, the relationship between the social media addictions of university students and social skills was examined. At the same time, it was examined whether these variables differed according to gender, age, unit, grade level, monthly income of the family, daily social media usage time and the social media application they use the most.

In the study, 55.3% of the participants were female and 44.7% were male. The age distribution of the group was 18–20 years old, 58.4%; 21–23 years old, 32%; 24 and over, 9.6%. In addition, 57.9% of the participants were students at Salihli Vocational School, and 42.1% were students at Salihli Faculty of Economics and Administrative Sciences. Moreover, 41.1% of the participants were first-year students, 34.5% were second-year students, 13.7% were third-year students and 10.7% were fourth-year students. The majority of the participants’ families (73.6%) had middle income levels. In total, 44.7% of the participants stated that they use social media for 3–4 h a day, 40.6% for 4 h or more, 13.2% for 1–2 h a day and 1.5% for less than 1 h a day. The majority of the participants (72.1%) stated that they use Instagram the most.

When the results of the descriptive analysis of the scales were analyzed, it was found that the participants’ total average social media addiction scores was 2.76; the average scores for virtual tolerance and virtual communication, which are sub-dimensions of social media addiction, were 2.96 and 2.52, respectively. Accordingly, the level of social media addiction of the students participating in the study is below average. In other words, the social media addiction status of the participants was found to be at the level of “less addicted”. These findings support the literature [53,54,55]. There are also studies with different results [56].

The data collection tool used to determine the perceptions of the university students participating in the study about their social skills evaluates the social skills of university students in a total of six dimensions: “affective expressiveness”, “affective sensitivity”, “affective control”, “social expressiveness”, “social sensitivity” and “social control”. The total mean of the participants’ social skills was found to be 3.17; the mean of affective expressiveness, 3.05; affective sensitivity, 3.53; affective control, 3.23; social expressiveness, 3.26; social sensitivity, 2.60; and social control, 3.40. Accordingly, students’ social skills are above average. While affective sensitivity has the highest mean score, social sensitivity has the lowest mean score. In other words, while the students’ ability to understand and interpret the non-verbal messages of other individuals is quite high, their ability to interpret the verbal communication of others is low. These findings support the literature [36,38,57,58].

According to the results of the correlation analysis, it was concluded that there were significant negative relationships between virtual tolerance and virtual communication, which are the sub-dimensions of social media addiction and social media addiction scale, and social skills and their sub-dimensions: affective expressiveness, affective sensitivity, affective control, social expressiveness, social sensitivity and social control. According to the findings of our study, the social skills of university students decrease as social media use increases, or social skills increase as social media use decreases. These findings support the literature [22,59,60,61]. However, a small number of studies with different results were found in the literature. For example, Greitemeyer (2022) and D’Errico et al. (2022) found that social media addiction (video games) positively affected social behaviors [62,63].

No statistically significant difference was found in the social tolerance and social communication sub-dimensions of social media addiction according to gender. However, a significant difference was found in the total score of social media addiction according to gender. Accordingly, the average score of male students’ social media addiction is higher than that of female students. When the literature is examined, similar to the findings of our study, there are studies showing that the gender factor is significantly related to social media addiction [64,65,66]. In contrast to this finding, there are also studies showing that girls are more addicted to social media and use social media more than boys [67,68,69]. In addition, there are studies conducted with university students showing that there is no significant difference in the levels of social media addiction between male and female students [53,55,70,71].

No statistically significant difference was found in social media addiction and its sub-dimensions according to age. According to this finding, it can be said that the age factor is not important for students’ social media addiction level. These findings support the literature [6,70]. There are also studies with different results [72].

While there was no statistically significant difference in the total and social tolerance sub-dimensions of social media addiction according to the academic unit, a statistically significant difference was found in the social communication dimension. The reason for the significant difference is that the social communication scores of the students of Salihli Faculty of Economics and Administrative Sciences are higher than the scores of the students of Salihli Vocational School. These findings support the literature [55].

While there was no statistically significant difference in social media addiction and social communication dimension according to grade levels, a statistically significant difference was found in the social tolerance dimension. Accordingly, while the social tolerance score of third-year students was at the lowest level, the social tolerance score of fourth-year students was at the highest level. These findings support the literature [54,55,72,73]. There are also studies with different results [74].

There was no statistically significant difference in total social media addiction and the social tolerance and social communication sub-dimensions according to the monthly income of the family. These findings support the literature [8,72,75]. There are also studies with different results [55].

A statistically significant difference was found in social media addiction and its sub-dimensions of social tolerance and social communication according to the duration of daily social media use. The reason for the difference is that students who use social media less than 1 h a day have the lowest total social media addiction and social tolerance and social communication sub-dimension scores, while students who use social media for 4 h or more have the highest scores. Therefore, the increase in the time that the participants spend on social media on a daily basis has an effect on their social media addiction. Accordingly, as the daily time spent on social media increases, the level of social media addiction also increases. These findings support the literature [53,55,69,76].

No statistically significant difference was found in the total social media addiction and the social tolerance and social communication sub-dimensions according to which social media platform is used the most. However, it is seen that Instagram and X (Twitter), which have recently increased in use, are also used intensively by university students. These findings support the literature [60]. There are also studies with different results [77].

There was no statistically significant difference in total social skill score and the affective expressiveness, affective sensitivity, affective control and social expressiveness sub-dimensions according to gender. However, statistically significant differences were found in the social sensitivity and social control sub-dimensions according to gender. The significant difference is due to the fact that the mean scores of female students are higher than those of male students in the social sensitivity sub-dimension and the mean scores of male students are higher than those of female students in the social control sub-dimension. These findings support the literature [78,79]. There are also studies with different results [36,80,81].

There was no statistically significant difference in total social skill score and the affective sensitivity, social expressiveness and social sensitivity sub-dimensions according to age variable. However, a statistically significant difference was found in affective expressiveness, affective control and social control sub-dimensions according to age. The reason for the significant difference is that the mean scores of those in the 18–20 age range are higher than those in the 21–23 age range in the affective expressiveness and social control sub-dimensions, and the mean scores of those in the 21–23 age range are higher than those in the 18–20 age range in the affective sub-dimension. These findings support the literature [82]. There are also studies with different results [36,83].

While no statistically significant difference was found in affective control, social expressiveness and social control sub-dimensions, statistically significant differences were found in social skill total score and the affective expressiveness, affective sensitivity and social sensitivity sub-dimensions. The reason for the significant difference is that the scores of Salihli FEAS students are higher than Salihli Vocational School students in affective sensitivity and social sensitivity sub-dimensions, and the scores of Salihli Vocational School students are higher than Salihli FEAS students in the affective expressiveness sub-dimension. In the literature, it was observed that different results were mostly reached [36,84,85].

According to the grade level, no statistically significant difference was found in the total social skill score and the affective expressiveness, affective sensitivity, social expressiveness, social sensitivity and social control sub-dimensions. A statistically significant difference was found only in the affective control sub-dimension. The reason for the significant difference was that the affective control sub-dimension score of the first-year students was lower than that for all other years. These findings support the literature [61,80]. There are also studies with different results [81,86].

No statistically significant difference was found in the total and sub-dimensions of social skills according to the income status of the family. These findings support the literature [86]. There are also studies with different results [87].

According to the duration of daily social media use, no statistically significant difference was found in the total social skill score and the social expressiveness and social control sub-dimensions, while a statistically significant difference was found in affective expressiveness, affective sensitivity, affective control and social sensitivity sub-dimensions. The reason for the significant difference is that the mean scores of the students who use social media for 4 h or more a day are higher than the others, and the mean scores of the students who use social media for less than 1 h a day are higher in the social control sub-dimension. In the literature, it was observed that mostly different results were reached [52].

This study presents important findings on the relationship between social media addiction and the social skill levels of university students from the perspective of systems thinking in order to understand the effects at the social level. The findings show that social media addiction negatively affects individuals’ social skill development and that this relationship differs with demographic factors. In particular, it was found that female students had higher levels of social media addiction, while male students had higher levels of social skills. This is an important finding from the perspective of social learning systems and social economy [88,89], showing how social media use shapes individuals’ social participation and interaction. Our study reveals that the relationship between social media addiction and social skills is not only an individual problem, but also a phenomenon linked to social dynamics. It is concluded that future studies should address the social effects of social media use more comprehensively and develop policy recommendations in this context.

According to the most used social media, no statistically significant difference was found in the total social skill score and the affective expressiveness, social expressiveness, social sensitivity and social control sub-dimensions, while a statistically significant difference was found in the affective sensitivity and affective control sub-dimensions. The reason for the significant difference was that the mean scores of Instagram users in the affective sensitivity and affective control sub-dimensions were higher than the others.

In line with these results, it can be concluded that

• Trainings on conscious media use can be provided for university students.
• As a result of the research, it was found that university students are less addicted to social media. However, there is a need to follow up on the social media addiction of young people with new research.
• Seminars can be delivered to students about the negative effects of social media addiction.
• Affective sensitivity levels of university students were found to be higher than other dimensions, while social sensitivity skills were found to be lower. Seminars can be delivered to improve students’ social skills.
• The relationship between social skill level and variables such as shyness, loneliness, motivation and problem-solving skills can be investigated.
• Students can be directed to different activities to reduce the time spent on social media.
• Social skill training programs can be developed, and teachers can be trained starting from preschool.
• In another study on private and public university students, similar issues can be studied, and the results can be compared.
• Social media addiction and social skills were examined in terms of some variables in this study, but they can also be analyzed in terms of different variables.
• This research on the relationship between social media addiction and social skills can be applied to different participants in different fields.
• This study is a descriptive study, and it can be suggested that future studies should be planned as experimental studies.
• One of the limitations of the study is that the sample group of the research consists of students studying at only one university. Therefore, the findings of the study cannot be generalized.
• Social media addiction distances individuals from reality, internalizes the effect of the virtual world at a high level and starts to create difficulty in making distinctions. In this case, social skills gradually atrophy. It is important to draw the attention of young people, who are our future, to this issue.
• Since there are very few studies examining the relationship between social media addiction and social skills, this study can make an important contribution to the literature.