14 BEHAVIOR OF STUDENTS IN USE OF SOCIAL NETWORK Samra JUSUFI ¹* Edisa KORO 2 ¹ University “UKSHIN HOTI” Prizren, Faculty of Economics, Business Administration Master Student, Jusufisamra@gmail.com *Correspondent Author. 2 University “UKSHIN HOTI” Prizren, Faculty of Economics, Business Administration Master Student, edisakoro2@gmail.com Article history: Submission 24 November 2022 Revision 30 February 2023 Accepted 05 April 2023 Available online 30 April 2023 Keywords: Students, Behaviour, Social Media. DOI: https://doi.org/10.32936/pssj.v7i1.406 A b s t r a c t The purpose of this article is to examine how students use social media based on six factors: field of study, level of study, year of study, gender, age, and income. To collect the data for this study, we conducted an online survey with an appropriate sample. In this study, a single construct was used to assess students' social media usage habits. We investigated the link between students' social media behaviors and their academic orientation, degree of study, year of study, gender, age, and income. According to the results of this study, students' social media use varies by field of study, does not differ by level of study, differs by year of study, differs by gender, differs by age, and does not differ by income. The sample was restricted to survey respondents due to time and financial limitations. Consequently, the study findings cannot be generalized to the entire population. 1. Introduction Websites and applications that stress conversation, community- based posts, engagement, content sharing, and cooperation are referred to as social media. People use social media to remain in contact with peers, family, and community members (Lutkevich, 2021). Youth people have a plethora of options for interacting with social media. This enables them to interact with the broader universe around them virtually. Students use social media in various ways depending on their hobbies, communities, peers, and family. Because of the environment that allows us to communicate quickly, sharing information has become extremely easy, and the flow of information between individuals through social media is very intense. In a brief amount of time, information can spread to a very large extent. The purpose of this study is to examine how students who use social media differ by age, gender, level of study, field of study, year of study, and student income. In this study, we focused on the following social media platforms: Facebook, YouTube, Dailymotion, Vimeo, Instagram, LinkedIn, MySpace, Twitter, Wikis (Wikipedia), Google, Pinterest, Flickr, and others (Reachout.com, ND). Studying the students’ social media usage by income is an important area of research due to its significant implications for educational equity, digital divide, mental health, and consumer behavior. According to a study by Pew Research Center, individuals with higher incomes are more likely to use social media than those with lower incomes, which highlights the importance of examining this issue further (Perrin, 2019). Studying the behavior of students in the use of social networks is important for several reasons. Firstly, social media has become an integral part of the daily lives of many young people, and studying their behavior in using these platforms can provide valuable insights into their attitudes, values, and behaviors. Additionally, social media can have both positive and negative effects on mental health, academic performance, and social relationships, so understanding how students use social media can help identify potential risks and opportunities for intervention (Rosen et al., 2013). 2. Literature Review When social media sites like Facebook, YouTube, and Twitter first appeared, our world was still split into online and offline realms. Social media is an online technology tool that connects individuals from all over the world. They are used to foster mailto:Jusufisamra@gmail.com mailto:edisakoro2@gmail.com https://doi.org/10.32936/pssj.v7i1.406 https://orcid.org/0000-0002-5763-1327 https://orcid.org/0000-0001-7732-5661 15 interpersonal connections. We can speak with each other across countries, listen to music, read books, view pictures, and do a variety of other things thanks to their assistance. Social media has greatly streamlined our lives and strengthened our bonds with others. They enter into various relationships and have the opportunity to talk to a relatively unlimited number of people, participate in premium meetings with a variety of identities, hear a significant number of stories, share assumptions, and discuss issues that are important to them during the time they spend getting to know people. As a result, most social network users are members of the younger age (Talaue et al., 2018). Social media is used to improve contact by utilizing media tools and webpages known as "social networking sites." Online blogs, wikis, social bookmarks, media sharing spaces, RSS feeds, microblogging sites, Facebook, and LinkedIn are examples of social networking sites with auditory and visual elements that can encourage engagement and simultaneous or asynchronous communication (Armstrong & Franklin, 2008). Social media has become ubiquitous and essential for information exchange in recent years (Sitaram & Huberman 2010). According to Mushtaq and Benraghda (2018), social media use among the younger population worldwide is quickly growing. College students make significant use of social media. As a result, they have an effect on the emotional and professional lives of students. Social media is a popular way for students to communicate with each other (Alwagait et al., 2014). They have infiltrated the lives of many young people. Their use among American adults ages 18-29 has increased from 12% in 2005 to 90% in 2015. (Pew Research Center, 2015). However, excessive use of social media may raise concerns about whether academic performance is being affected (Alwagait et al., 2014). As college students participate in a variety of social media activities daily, there is growing concern about the potential harmful effects of social media on students' social well-being (Lau, 2007). Social media has developed into a type of online discourse in which people on an unprecedented scale produce, share, tag, and network material. Facebook, MySpace, Digg, Twitter, and the JISC list-serves are noteworthy in academics. Social media is changing public dialogue in society due to its ease of use, speed, and size, generating trends and goals on issues spanning from the environment and politics to technology and amusement (Sitaram & Huberman, 2010). They are seen as an important way to provide health information to students. But how successfully are colleges and universities using social media in the sense in which it is intended—to be truly social, not just promotional? Students can only benefit from social media if they follow, interact with, and share content (Perrault et al., 2019). Certainly, the Internet has taken on an important role in people's lives. It is hard to imagine that there is a young person who does not visit social media and follow the news at least once a day. Modern life requires us to stay in touch and up to date with the latest news and trends (Talaue et al., 2018). Twitter and Facebook are two of the most popular social media platforms where students spend the majority of their time (Alwagait et al., 2014). According to Ukwishaka and Aghaee (2020), Facebook is rapidly spreading across a variety of industries, including education. According to most research, today's students use Facebook to interact, collaborate, and find answers. What we know today is less important than our ability to learn what we will need tomorrow. Smartphones, social media, and the Internet are part of the daily lives of today's generation. The experience of undergraduate and graduate students in business has undoubtedly improved with the use of social media techniques in learning (Bharucha, 2018). They are seen as an important way to deliver health information to students. But how successfully are colleges and universities using social media in the sense in which it is intended—to be truly social, not just promotional? Students can only benefit from social media if they follow, interact with, and share content (Perrault et al., 2019). To be sure, the Internet has become increasingly essential in people's lives. It's difficult to envision a young person who doesn't look. The idea of social software has developed greatly in recent years, whether for sharing videos like YouTube, photos like Flickr, community building like Facebook, or social bookmarking like Del.icio.us (Al-Khalifa, 2008). Zhao (2021) found that social media use has a minor effect on students' mental wellbeing. Using social media for enjoyment is more likely to lead to addiction than it is to improve psychological well-being. The Internet's popularity and application in higher education have altered the worldwide environment. Recent advancements in its powers have opened up new channels of contact for the exchange of knowledge and experience. Innovative applications have produced new chances for internationally known experts to share their academic experiences and study methodologies. It appears to be changing the norms and influencing encounters. The Internet has facilitated virtual interaction for sharing search results. The term "social media" refers to such enhanced online connections for communication. It is an Internet-based tool that promotes social interaction among users. Studying differences in social media usage by students' demographics is important because social media has become an 16 increasingly important part of students' lives and is often used to facilitate communication, learning, and socialization. Understanding how different demographic groups use social media can provide valuable insights into how these platforms shape and are shaped by broader social and cultural trends. For example, studies have shown that students from lower-income backgrounds are more likely to use social media as a source of news and information than students from higher-income backgrounds, who are more likely to use traditional news sources such as newspapers and television (Pew Research Center, 2018). Six hypotheses have been proposed based on the examined literature: H1: Students' use of social media varies by field of study. H2: Students' use of social media depends on the level of study. H3: Students' use of social media depends on the year of study. H4: Students' use of social media varies by gender. H5: Students' use of social media varies by age. H6: Student use of social media varies by income. 3. Methodology Participants The research included 204 candidates of the bachelor, master and doctoral levels. Data collection was done online and only those who had access to the shared link participated in the research. Instruments The Social Media Behavior Meter, developed by Özlü and Kalyoncuolu (2017), which includes 37 questions, was used to assess the review of activities (statements) performed on social media platforms. From (1) strongly disagree to (5) strongly agree on a Likert measure. The survey was translated into Albanian and the SPSS application was used to analyze the data obtained. 4. Data Analysis Descriptive statistics The SPSS 26 software was used to evaluate the data. Statistical tests were carried out using reliability, factor analysis, ANOVA, and the T-test. Table 1. Descriptive sample statistics (n = 204) Variables Frequency Percent Study department Economics 72 35.3% Education 58 28.4% Medicine 16 7.8% Law 12 5.9% Philology 9 4.4% Computer Science 9 4.4% Mathematics and Natural Sciences 6 2.9% Architecture 4 2.0% Other 18 8.8% Studying level Bachelor 138 67.6% Master 54 26.5% Doctorate 12 5.9% Year of studying First year 75 36.8% The second year 59 28.9% Third year 46 22.5% Fourth year 15 7.4% Sixth year 7 3.4% Fifth year 2 1.0% Gender Women 147 72.1% Men 57 27.9% Age 21-29 years old 106 52.0% Under 20 years old 74 36.3% 30-39 years old 17 8.3% 40-49 years old 5 2.5% 50-59 years old 2 1.0% Income 0-300 € 121 59.3% 301–600 € 45 22.1% 601-900 € 24 11.8% 901-1200 € 8 3.9% Over 1,200 € 6 2.9% Descriptive statistics for the sample are shown in Table 1. Department of Study: the largest number of participants who responded to the survey were from the economics direction major with 72, followed by students from the Education direction major with 58 individuals. Level of Studies: This poll had the most participants at the Bachelor's degree 67.6%, followed by the Master's level 26.5%, and finally the PhD level 5.9%. Year of study: first-year students accounted for the largest proportion 36.8 percent, followed by second-year students with 59 people. Gender: In terms of participants by gender, women were 72.1 percent, while men were 27.9 percent. Age: the most frequently repeated age category of respondents is 21-29 with 52 percent, followed by under 20 36.3 percent, and then other groups. Income: 121 people from the respondents have an income of 0- 300 euros and only 6 people have an income of over 1200 euros. 17 4.1. Validity Analysis Validity and reliability of instruments The findings of the preliminary factor analysis are shown in Table 2. Using the varimax approach, a total of eight factors were formed from 33 statements. Our measure consisted of 37 statements; however, due to the low weights (below 0.50), four statements were dropped from the factor analysis (ISM10, ISM20, ISM32, ISM37) and the factor analysis was repeated. The first factor is composed of eight statements. "I generally write comments on videos, photos, and other multimedia content on various social media platforms." "I generally comment on content (photos, videos, texts) on other users' social media profiles." "I generally tag various messages or pages on social media platforms." "I generally tag news or pages on social media platforms." "I generally tag images or websites." "I often share my comments and views on various social media platforms, such as question and answer pages and dictionary pages." Based on this information, this aspect is called "commenting and tagging behavior". The second factor is composed of five statements. "I regularly publish posts on my website." "I regularly publish posts on my blog." "I frequently update/edit my profile on social networking sites such as Facebook, Instagram, LinkedIn, MySpace, and so on." "I clearly share my reviews for various goods and services on social media platforms (electronic shopping sites)." and "I mostly share my posts on my profile on a social network (Facebook, Instagram, LinkedIn, Myspace, etc.)." Based on these statements, this component can be referred to as "posting behavior." The third factor consists of four statements. These are the statements: "I usually play various single-player games in the virtual world (Farmville, Mafia Wars, Angry Birds, Candy Crush, etc.);" "I usually play multiplayer games in the virtual world (Warcraft, Second Life, League of Legends, etc.);" and "I usually listen to music/podcasts on social media platforms such as Fizzy, Grooveshark, and Ttnetmusic." and "I usually perform tagging on websites such as Delicious and Pinterest." According to these words, this component can be referred to as "fun behavior." The fourth factor is composed of four assertions. These assertions are, "I usually post audio/music files that I have created on social media platforms," "I frequently upload videos that I have created on video sharing sites such as YouTube, Dailymotion, Vimeo, etc." "I regularly post my latest posts/updates on my personal Twitter account," and "I post essays/articles/stories that I have written online on various social media platforms." According to these statements, this component can be referred to as "music/script uploading behavior." The fifth factor is composed of four statements. "I generally read different news on social media platforms." "I join various groups (Facebook groups, brand communities, etc.) on social media platforms." I read posts from other users on social media (Facebook, LinkedIn, Myspace, Google+, etc.) daily and I like the brand's social media pages. Based on these statements, this component can be referred to as "social media reading behavior." Table 2. Results of exploratory factor analysis Factor 1 2 3 4 5 6 7 8 ISM24 .712 ISM23 .639 ISM9 .613 ISM28 .597 ISM36 .596 ISM14 .580 ISM22 .523 ISM21 .465 ISM1 .827 ISM2 .788 ISM6 .693 ISM8 .555 ISM27 .552 ISM34 .785 ISM35 .694 ISM16 .654 ISM33 .505 ISM5 .757 ISM4 .695 ISM7 .536 ISM3 .505 ISM30 .789 ISM29 .745 ISM31 .565 ISM26 .544 ISM18 .789 ISM17 .650 ISM15 .462 ISM12 .724 ISM13 .536 ISM11 .514 ISM25 .733 ISM19 .623 KMO .875 Barlett test .000 Total Explained Variance 63.054 18 The sixth factor is composed of three statements. "I generally read forum posts" and "I watch videos posted by other users on social media platforms." "I regularly read and follow other users' blogs." Based on these statements, this component can be referred to as "following behavior." The seventh factor is composed of four statements. These statements are, "I frequently follow news content, etc., of which I want to be notified of updates using news aggregators such as RSS, Atom, and GoogleReaders." "I generally vote/rate various websites" and "I generally write/contribute to wikis (Wikipedia, etc.)." Based on these comments, we can call this factor "voting/contributing behavior." The eighth factor is composed of four statements. These are the statements, "I generally use social media platforms to learn about companies' products (goods and services)" and "I participate in numerous social media networks (Facebook groups, brand communities, etc.)." Based on these statements, this factor can be referred to as "information gathering behavior." 4.2. Reliability Analysis Table 3. Results of exploratory factor analysis Factors Alpha reliability coefficient Number of statements Commenting and tagging behavior .866 8 Posting behavior .822 5 Fun behavior .739 4 Uploading music/writing behavior .762 4 Reading behavior .710 4 Following behavior .593 3 Voting/contributing behavior .547 3 Information gathering behavior .493 2 The factor "Commenting and tagging behavior" has a reliability of 86.6%, “Posting behavior” has a reliability of 82.2%, “Fun behavior” has a reliability of 73.9%, “Uploading music/writing behavior” has a reliability of 76.2%, “Reading behavior” has a reliability of 71.0%, “Following behavior” has a reliability of 59.3%, “Voting/contributing behavior”” has a reliability of 54.7%, “Information gathering behavior” ” has a reliability of 49.3%. The analysis was performed with the first 5 factors: "commenting and labeling behavior," "posting behavior," "fun behavior," "music/writing upload behavior," and "social media reading behavior," because they have high values and show that the measurement tool used is very reliable. While the last 3 factors ("following behavior", "voting/contributing behavior" and "information gathering behavior") are not included in the analysis because their reliability coefficient is low (alpha reliability coefficient below 0.700). 4.3. Hypothesis Testing H1: Students' use of social media varies by field of study. Table 4 summarizes the results of the ANOVA analysis regarding the difference in social media use according to the direction of the study. The F and Sig values show that there is no significant difference in the factors CTB, FB, UB and RB (F = 1.781, p > 0.05; F = 1.273, p > 0.05; F = 1.077, p > 0.05; F = 1.335, p > 0.05, respectively). However, there is a significant difference in the second factor, PB based on the values (F = 2.685, p = .008 < 0.05). To see these differences, the multiple comparison table was used using Tukey's test. Table 4. Results of the ANOVA analysis regarding differences in social media use according to the direction of the study. Sum of Squares df Mean Square F Sig. CTB Between Groups 10.028 8 1.254 1.781 .083 Within Groups 137.221 195 .704 Total 147.249 203 PB Between Groups 16.791 8 2.099 2.685 .008 Within Groups 152.416 195 .782 19 Total 169.207 203 FB Between Groups 8.645 8 1.081 1.273 .259 Within Groups 165.498 195 .849 Total 174.143 203 UB Between Groups 6.729 8 .841 1.077 .381 Within Groups 152.266 195 .781 Total 158.995 203 RB Between Groups 5.992 8 .749 1.335 .228 Within Groups 109.394 195 .561 Total 115.386 203 CTB - Commenting and tagging behavior, PB - Posting behavior, FB - Fun behavior, UB - Uploading music/writing behavior, RB - Reading behavior. Table 5. Results of the Multiple Comparisons Regarding the Difference in Social Media Use According to the Direction of the Studies Using Tukey's Results. (I) Direction in which you are studying? (J) Direction in which you are studying? The average difference (I- J) Mistake Std. Sig. Economics Education .53199* .15599 .022 Table 5 shows the results of numerous comparisons based on the direction of the studies in terms of differences in social media use. There is a significant difference between students at the Economic Faculty and students at the Education Faculty. The average difference is 0.53199. This difference shows that students in the Faculty of Economics utilize social media more than education faculty students to publish and post on social media. Based on these results, Hypothesis H1: Students' use of social media changes according to their field of study has been successfully accepted. H2: Students' use of social media depends on the level of study. Table 6 summarizes the results of the ANOVA analysis regarding differences in social media use by study level. The F and Sig values show that there is no significant difference in the factors CTB, PB, FB, UB and RB (F = 2.619, p > 0.05; F = 1.968, p > 0.05; F =.714, p > 0.05; F = 1.322, p > 0.05; F =.748, p > 0.05, respectively). Table 6. Results of ANOVA analysis regarding differences in social media use by study level. Sum of Squares df Mean Square F Sig. CTB Between Groups 3.739 2 1.870 2.619 .075 Within Groups 143.510 201 .714 Total 147.249 203 PB Between Groups 3.250 2 1.625 1.968 .142 Within Groups 165.957 201 .826 Total 169.207 203 FT Between Groups 1.228 2 .614 .714 .491 Within Groups 172.916 201 .860 Total 174.143 203 UB Between Groups 2.065 2 1.032 1.322 .269 Within Groups 156.930 201 .781 Total 158.995 203 RB Between Groups .853 2 .426 .748 .475 Within Groups 114.534 201 .570 20 Total 115.386 203 CTB - Commenting and tagging behavior, PB - Posting behavior, FB - Fun behavior, UB - Uploading music/writing behavior, RB - Reading behavior. Based on these results, the H2 hypothesis that students' use of social media varies by level of study is not accepted. H3: Students' use of social media depends on the year of study. Table 7 summarizes the results of the ANOVA analysis on differences in social media use by year of study. Results F and Sig show that there is no significant difference in factors CTB, PB, UB, and RB (F = 1.022, p > 0.05; F =.857, p > 0.05; F = 2.249, p > 0.05; and F = 1.872, p > 0.05). Based on the data, (F = 2.279, p =.048 0.05), there is a significant difference in the third component, FT. Table 7. Results of ANOVA analysis regarding differences in social media use by year of study. Sum of Squares df Mean Square F Sig. CTB Between Groups 3.705 5 .741 1.022 .406 Within Groups 143.544 198 .725 Total 147.249 203 PB Between Groups 3.583 5 .717 .857 .511 Within Groups 165.624 198 .836 Total 169.207 203 FT Between Groups 9.478 5 1.896 2.279 .048 Within Groups 164.666 198 .832 Total 174.143 203 UB Between Groups 8.545 5 1.709 2.249 .051 Within Groups 150.450 198 .760 Total 158.995 203 RB Between Groups 5.210 5 1.042 1.872 .101 Within Groups 110.176 198 .556 Total 115.386 203 CTB - Commenting and tagging behavior, PB - Posting behavior, FB - Fun behavior, UB - Uploading music/writing behavior, RB - Reading behavior. Based on these findings, hypothesis H3: Student social media use varies by academic year was accepted. H4: Students' use of social media varies by gender. Table 8. T-test results regarding the difference in social media use by gender Gender? N Mean Std. Deviation t Sig CTB Male 57 2.6952 .78952 1.143 .254 Female 147 2.5434 .87349 PB Male 57 2.9018 1.02408 .867 .387 Female 147 2.7782 .86741 FT Male 57 2.3465 .94698 -.132 .895 Female 147 2.3656 .92124 UB Male 57 2.2807 .95088 1.097 .274 Female 147 2.1293 .85776 RB Male 57 3.4693 .75307 .2.204 .029 Female 147 3.7262 .74446 21 CTB - Commenting and tagging behavior, PB - Posting behavior, FB - Fun behavior, UB - Uploading music/writing behavior, RB - Reading behavior. Table 8 summarizes the results of the T-test related to the difference in social media use by year of study. The F and Sig values show that there is no significant difference in the factors CTB, PB, FT, and UB (F = 1.143, p > 0.05; F =.867, p > 0.05; F = -.132, p > 0.05; F = 1.097, p > 0.05, respectively). However, based on the values (F = 2.204, p =.029 0.05), there is a significant difference in the fifth factor, RB. Based on these results, Hypothesis H4: Student use of social media varies by gender, was successfully accepted. H5: Students' use of social media varies by age. Table 9 summarizes the results of the ANOVA analysis regarding differences in social media use by year of study. The F and Sig values show that there is no significant difference in the factors CTB, FT, UB, and RB (F = 1.205, p > 0.05; F =.053, p > 0.05; F = -2.099, p > 0.05; F = 0.507, p > 0.05, respectively). There is a significant difference in the second factor, PB, based on the values (F = 3.065, p =.018, 0.05). Based on these results, hypothesis H5 is stated: Student use of social media varies by age and was successfully accepted. Table 9. Results of ANOVA analysis regarding differences in social media use by age. Sum of Squares df Mean Square F Sig. CTB Between Groups 3.483 4 .871 1.205 .310 Within Groups 143.766 199 .722 Total 147.249 203 PB Between Groups 9.820 4 2.455 3.065 .018 Within Groups 159.386 199 .801 Total 169.207 203 FT Between Groups .186 4 .047 .053 .995 Within Groups 173.957 199 .874 Total 174.143 203 UB Between Groups 6.436 4 1.609 2.099 .082 Within Groups 152.559 199 .767 Total 158.995 203 RB Between Groups 1.164 4 .291 .507 .731 Within Groups 114.222 199 .574 Total 115.386 203 CTB - Commenting and tagging behavior, PB - Posting behavior, FB - Fun behavior, UB - Uploading music/writing behavior, RB - Reading behavior. H6: Student use of social media varies by income. Table 10. Results of ANOVA analysis regarding differences in social media use by income. Sum of Squares df Mean Square F Sig. CTB Between Groups 3.851 4 .963 1.336 .258 Within Groups 143.398 199 .721 Total 147.249 203 PB Between Groups 4.094 4 1.024 1.234 .298 Within Groups 165.112 199 .830 Total 169.207 203 FT Between Groups 2.593 4 .648 .752 .558 Within Groups 171.550 199 .862 Total 174.143 203 UB Between Groups 4.177 4 1.044 1.342 .256 22 Within Groups 154.818 199 .778 Total 158.995 203 RB Between Groups 2.158 4 .540 .948 .437 Within Groups 113.228 199 .569 Total 115.386 203 CTB - Commenting and tagging behavior, PB - Posting behavior, FB - Fun behavior, UB - Uploading music/writing behavior, RB - Reading behavior. Table 10 summarizes the results of the ANOVA analysis regarding differences in social media use by study level. The F and Sig values show that there is no significant difference in the factors CTB, PB, FT, UB, and RB (F = 1.336, p > 0.05; F = 1.234, p > 0.05; F =.752, p > 0.05; F = 1.342, p > 0.05; F =.948, p > 0.05). Based on these results, Hypothesis H6: Student use of social media varies by income, is not accepted. 5. Conclusions The purpose of this study was to explore the social media usage habits of students studying in Kosovo and to determine if different groups emerge depending on the actions and goals of the users. As a result of the data obtained using the social media user behavior assessment scale, eight types of user behaviors were identified in this study. Examples of these behaviors include commenting and tagging, posting, fun behavior, uploading music and writing, reading social media, following behaviors, voting and contributing, and gathering information. The last three behaviors were not included in the next study due to their low agreement (less than 70%). From the collected data, we found that there is a substantial difference in the usage of social media between students from the Faculty of Economics and students from the Faculty of Education, and there is a significant difference in the third component. In terms of the difference in students' usage of social media by year of study, there is a substantial difference in the fifth element. Reading Behavior Based on Value p =.029 0.05, women utilize social media for reading more than males, and there is also a significant difference between students of different ages. The following suggestions are made based on the findings: Given that the research group, university students, uses social media to learn about almost everything, it is unavoidable that they will make the best use of the information tools accessible on social media platforms when making buying choices. Considering this situation, it has become essential for businesses that target students to begin their marketing efforts on social media sites. Furthermore, the research suggests that businesses consider the fact that young people use social media for more than just knowledge. Companies must conduct a comprehensive study of social media problems that are of interest to university students in Kosovo, as well as be conscious of the importance of marketing; this information must then be incorporated into their marketing actions. A study by Pew Research Center (2018) found that younger generations tend to use social media platforms more frequently than older generations. This is consistent with the data collected in our study, which also found a difference in social media usage among different age groups. 6. Limitations of the Paper and Recommendations for Future Research Due to time and cost constraints, we used the convenience sampling and not extend the results to the entire population. It would be a good idea for future studies to include other criteria that can be used to compare students. Another suggestion for future studies is to use a larger sample to obtain the most realistic results. References 1. Al-Khalifa, H. S., & Rubart, J. (2008). Automatic document-level semantic metadata annotation using folksonomies and domain ontologies. ACM SIGWEB Newsletter, 2008(Autumn), 1-3. 2. Alwagait, E., Shahzad, B., & Alim, S. (2015). Impact of social media usage on students academic performance in Saudi Arabia. Computers in Human Behavior, 51, 1092-1097. 3. Armstrong, J., & Franklin, T. (2008). A review of current and developing international practice in the use of social networking (Web 2.0) in higher education. 4. Asur, S., & Huberman, B. A. (2010, August). Predicting the future with social media. In 2010 IEEE/WIC/ACM international conference on web intelligence and intelligent agent technology (Vol. 1, pp. 492-499). IEEE. 23 5. Bharucha, J. (2018). Exploring education-related use of social media: business students perspectives in a changing India. Education+ Training. 6. Lau, W. W. (2017). Effects of social media usage and social media multitasking on the academic performance of university students. Computers in human behavior, 68, 286-291. 7. Lutkevich, B. (2021, 09). TechTarget.com. Gjetur në TechTarget.com: https://whatis.techtarget.com/ definition/social-media (Data e qasjes: 18/18/2021) 8. Müge, Ö. Z. L. Ü., & KALYONCUOĞLU, S. (2017). Grouping University Students According to Their Social Media Usage Behaviours. Journal of Internet Applications and Management, 8(2), 5-29. 9. Mushtaq, A. J., & Benraghda, A. (2018). The effects of social media on the undergraduate students’ academic performances. Library Philosophy and Practice, 4(1). 10. Perrault, E. K., Hildenbrand, G. M., McCullock, S. P., Schmitz, K. J., & Dolick, K. N. (2019). Hashtag health: College health on social media and students’ motivations to follow, interact, and share their social media content. Health promotion practice, 20(5), 721-729. 11. Perrin, A. (2019). Share of U.S. adults using social media, including Facebook, is mostly unchanged since 2018. Pew Research Center. Retrieved from https://www.pewresearch.org/fact- tank/2019/04/10/share-of-u-s-adults-using-social- media-including-facebook-is-mostly-unchanged- since-2018/ 12. Pew Research Center. (2015). Social media usage: 2005-2015. Retrieved from: http://www.pewinternet.org/2015/10/08/social- networking-usage-2005-2015/ 13. Pew Research Center. (2018). News use across social media platforms 2018. Retrieved from https://www.journalism.org/2018/09/10/news-use- across-social-media-platforms-2018/ date of access 01/04/2023 14. Reachout: https://schools.au.reachout.com/articles/students-and- social-media , date of access 02/02/2023 15. Rosen, L. D., Whaling, K., Carrier, L. M., Cheever, N. A., & Rokkum, J. (2013). The 16. Media and Technology Usage and Attitudes Scale: An empirical investigation. Computers in Human Behavior, 29(6), 2501-2511. https://doi.org/10.1016/j.chb.2013.06.006 17. Talaue, G. M., AlSaad, A., AlRushaidan, N., AlHugail, A., & AlFahhad, S. (2018). The impact of social media on academic performance of selected college students. International Journal of Advanced Information Technology, 8(4/5), 27-35. 18. Ukwishaka, M. C., & Aghaee, N. (2020). Using social media for peer integration in higher education:Sudents’perception of using facebook to support peer. In 14th IADIS International Conference e-Learning 2020, EL 2020, Part of the 14th Multi Conference on Computer Science and Information Systems, MCCSIS 2020, July 21-23, 2020 (pp. 109- 116). IADIS Press. 19. Zhao, L. (2021). The impact of social media use types and social media addiction on subjective well- being of college students: A comparative analysis of addicted and non-addicted students. Computers in Human Behavior Reports, 4, 100122 https://www.pewresearch.org/fact-tank/2019/04/10/share-of-u-s-adults-using-social-media-including-facebook-is-mostly-unchanged-since-2018/ https://www.pewresearch.org/fact-tank/2019/04/10/share-of-u-s-adults-using-social-media-including-facebook-is-mostly-unchanged-since-2018/ https://www.pewresearch.org/fact-tank/2019/04/10/share-of-u-s-adults-using-social-media-including-facebook-is-mostly-unchanged-since-2018/ https://www.pewresearch.org/fact-tank/2019/04/10/share-of-u-s-adults-using-social-media-including-facebook-is-mostly-unchanged-since-2018/ https://www.journalism.org/2018/09/10/news-use-across-social-media-platforms-2018/ https://www.journalism.org/2018/09/10/news-use-across-social-media-platforms-2018/ https://schools.au.reachout.com/articles/students-and-social-media https://schools.au.reachout.com/articles/students-and-social-media https://doi.org/10.1016/j.chb.2013.06.006