Journal of Management Information and Decision Sciences (Print ISSN: 1524-7252; Online ISSN: 1532-5806)

Research Article: 2021 Vol: 24 Issue: 2S

The impact of social media on students??? social interaction

Joshua Ebere Chukwuere, North-West University

Citation Information: Chukwuere, J. E. (2021). The impact of social media on students’ social interaction. Journal of management Information and Decision Sciences, 24(7), 1-15.

Abstract

This study aimed to discover the impact of social media platforms on students’ social interaction. Students’ interaction with other people allows them to analyse their thoughts, reflect on their experiences, and find solutions. Social interaction advances students’ learning ability and adaptation in society. It helps to shape their knowledge and social participation. At the same time, social media platforms allow students to connect, network, and communicate. This study applied quantitative research methodology using a questionnaire to determine the impact of social media platforms in facilitating students’ social interaction in their daily lives. The study findings empower students to understand that social media platforms promote social interaction, but it encourages physical distance among friends in a meeting or an event.

Keywords

Students; Social interaction; Social media platforms; Social media.

Introduction

The conventional lecture-oriented teaching and learning model is gradually becoming unfashionable for students (Hurst et al., 2013). Social interactive learning is gradually becoming a norm for students to reflect on their classroom learning experience and daily activities. Social media platforms’ function presents the channel for social interaction among students in the community and learning process. The adoption of social media platforms across the different aspects of students’ lives keeps evolving continuously. Hurst et al. (2013) suggest that students’ social media platforms are as essential as water to fish. Through social media platforms, social interaction and engagement are built among students to connect, share, transform ideologies, and get informed (Abbas et al., 2019). The platforms improve students’ communication, engagement, networking, and social interaction with peers and lecturers. This study seeks to determine the impact of social media platforms in facilitating students’ social interaction in their daily activities.

Literature Review

Student Social Interaction

Learning institutions operate in a multicultural society with a clear mandate to provide social changes and solutions. According to Alhassan (2015), the change in a learning institution is the change in society. Students constitute a larger part of society where changes are required. The changes demanded in society are becoming the function of social interaction. Social interaction among students is noticeable in strengthening their daily reflection and finding solutions in gaps (Okita, 2012). Social interaction plays an essential role in the student learning process and off-learning environment. According to Hurst et al. (2013), social interaction enhances students’ literacy, knowledge, critical thinking, problem-solving skills, and ability to communicate and network. It allows students to fit in with society in contributing effectively and meaningfully. In the learning environment, students benefit more when they are allowed to read, write, participate, listen, and speak in the learning process via social interaction. Socially, students can participate well when they are allowed to contribute, share ideas, and get involved in the social discourse. According to Okita (2012), students’ ability to develop cognitive reasoning lies in their social interaction, culture, values, and history.

In today’s world, social media platforms such as WhatsApp, Facebook, Twitter, LinkedIn, and others have opened the new social interaction among students to communicate and engage with others (Abbas et al., 2019). WhatsApp has remained the most used social media platform by the students (Aluh et al., 2019; Dahdal, 2020) to engage in social interaction; it allows students to be social actors in bringing necessary changes to social issues and concerns. Abbas et al. (2019) further believed that social media platforms make students’ social interaction and communication more advanced in providing opportunities and image branding.

The Impact of Social Media in Facilitating Students’ Social Interaction

Social interaction is essential for social building, cohesion, and networking among individuals with shared interests and associations. Social media is impacting and facilitating social interactions. The impact benefits the youth and students (Akram & Kumar, 2017) and changes the social interaction and communication landscape. However, it increases some cyber threats, such as cyberbullying, which could be regarded as a societal concern (Abaido, 2020; Chan et al., 2020). This is a digital age, where ideas, contents, and concepts are shared among interest groups. Currently, social media has changed and continues to redefine social lives. Many, including students, spend hours daily on their smartphones, desktops, and other technological devices in surfing different social media platforms, commenting, tweeting, liking, checking pictures, images, and many more (Akram & Kumar, 2017). The enormous amount of time spent on social media is done on social activities (Tasir et al., 2011) in building social interaction. Social media platforms have improved students’ social interaction with more comprehensive networking and connection with local, national, and international peers. It has also provided students with the platform to socialise with classrooms, campus (university), and society. Students can build virtual interaction and connection, which at some point can lead to physical contact and meeting. However, social media’s long hours lead to private content exposers to the public (Saravanakumar & Deepa, 2016; Blasbalg et al., 2012). At the same time, Gupta and Dhami (2015) suggest that social media platform usage has raised many privacy and security concerns.

According to Akram and Kumar (2017), social media platforms facilitate students’ communication and information sharing quickly for various reasons, using WhatsApp, Facebook, and others. Students can use social media to improve their social engagement and interaction with others. It positively impacts students in providing them with continuous connectivity with peers and lecturers, increasing information exchange, access to learning materials and support, and entertainment (Abbas et al., 2019). Nonetheless, the usage of social media platforms impacts students’ (users’) family time and relationships (Procentese et al., 2019).

Research Methodology

This study used a quantitative research methodology. According to Creswell and Poth (2016) and Alhassan (2019), quantitative methods’ deployment is due to the students’ experience and understanding of the topic. This study used first-year university students from the North-West University. The study collected 449 online questionnaires through Google Forms, and only 325 were considered and used. 124 questionnaires were discarded because they were incomplete as a result of the students not being first-year students. The discarded questionnaires formed part of data validity and cleansing.

The questionnaire was collected using Google Forms. The questionnaire data were exported to a spreadsheet and analysed using Statistical Package for the Social Sciences (SPSS). SPSS was used to extract data, as presented in Table 1.

Table 1 Demographic Information
  Questions Options Frequency Percentage
1 Age group? 17 3 0.9
18 69 21.1
19 93 28.4
20 58 17.7
21 38 11.6
22 24 7.3
23 15 4.6
24 9 2.8
25 5 1.5
26 5 1.5
27 3 0.9
28 2 0.6
31 1 0.3
35 1 0.3
45 1 0.3
2 Gender? Male 155 47.4
Female 172 52.6
3 Race? Black 319 97.6
White 2 0.6
Indian 3 0.9
Coloured 3 0.9
4 Faculty? Economic and Management Sciences (EMS) 214 65.4
Education 63 19.3
Natural and Agricultural Sciences 24 7.3
Humanities 19 5.8
Health Sciences 5 1.5
Theology 2 0.6

Findings and Discussions

The findings on social media platforms’ impact on students’ social interaction are presented and answers to the research questions. The study came up with 13 questions to understand how social media platforms define students’ social interaction. The findings and discussion began with the students’ demographic data.

Demographics Information

Table 1 provides the demographic information of the students (participants). The demographic involves age group, gender, race, and faculty of study. The second question presents different forms of social media platforms used by students daily.

The study found in Table 1 that students’ ages are 19 (28.4%), 18 (21.1%), and many others. The findings indicate that most of the students are tech-generations who can adapt and use social media platforms and other emerging technologies. The table also shows on number 2 that 172 (52.6%) of the participates are females, and 155 (47.4%) are male. It shows that most of the students who participated in the study are female students. On number 3 (Table 1), most of the students are black, because the Mafikeng Campus is located in a black-dominated area of the South African province, the North West Province. Finally, number 4 of the demographic question indicates that 214 (65.4%) of the students are from the EMS Faculty.

Most Used Social Media

This question aimed to determine different forms of social media platforms that students use daily. The findings of the study show the hierarchy of the most used social media platforms for the students. 262 (62.7%) of the students used WhatsApp, 78 (18.7%) Facebook, 38 (9.1%) Instagram, 22 (5.3%) Twitter, 12 (2.9) YouTube, 3 (0.7) TikTok and 3 (0.7) Google. WhatsApp is the most used social platform among the students in the study. Literature studies show that students mostly use WhatsApp (Dahdal, 2020; Aluh et al., 2019).

Social Media And Social Interaction

Table 2 presents 13 different questions that seek to understand social media platforms’ influence on students’ social interactions. Table 2’s analyses are combined, such as strongly agree plus agree equals ‘agree’ = Total A; while disagree and strongly disagree are combined to form ‘disagree’ = Total D; while undecided remained untouched.

Table 2 Question Construct
Construct Strongly agree Agree Total (agree) Undecided Disagree Strongly disagree Total (disagree)
1 My usage of social media
improves my social interaction
102 (31.4%) 141 (43.4%) 243
(74.8%)
30
(9.2%)
43 (13.2%) 9
(2.8%)
52
(16%)
2 The use of social media improves my communication
and sharing of information with friends and peers
115 (35.4%) 149 (45.8%) 264 (81.2%) 20 (6%) 30 (9.2%) 11 (6.2%) 41 (12,6%)
3 The use of social media
promotes physical distance
among friends
143 (44.0%) 148 (45.5%) 291
(89.5%)
19 (5.8%) 11
(3.4%)
4
(1.2%)
15
(4.6%)
4 The use of social media
encourages students to spend
hours (time) online
140 (43.1%) 137 (42.2%) 277 (85,3%) 29 (8.9%) 12 (3.7%) 7 (2.2%) 19 (5.9%)
5 Usage of social media promotes data privacy issues
and exposure of personal
information.
101
(31.1%)
113
(34.8%)
245
(83%)
85
(26.2%)
19
(5.8%)
7
(2.2%)
24
(8%)
6 The use of social media is a
useful tool in meeting friends
101
(31.1%)
139
(42.8%)
240
(73.9%)
48
(14.8%)
25
(7.7%)
12
(3.7%)
37
(11.4%)
7 Social media promotes
cyberbullying and infringement of privacy
86 (26.5%) 109 (33.5%) 195 (60%) 88 (27.1%) 28 (8.6%) 14 (4.3%) 42 (12.9%)
8 I believe that social media
usage enhances your social
life and interaction
82
(25.2%)
143
(44.0%)
225
(69.2%)
64
(19.7%)
26
(8.0%)
10
(3.1%)
36
(11.1%)
9 Indeed, social media is terrible for social interaction 38
(11.7%)
62
(19.1%)
100
(30.8%)
125
(38.5%)
63
(19.4%)
37
(11.4%)
100
(30.8%)
10 Social media platforms are not favourable for interacting with friends always 43 (13.2%) 93 (28.6%) 136 (41.8%) 80 (24.6%) 82 (25.2%) 27 (8.3%) 109 (33.5%)
11 In all, social media is harmful to social interaction 41 (12.6%) 62 (19.1%) 103 (31.7%) 120 (36.9%) 68 (20.9%) 34 (10.5%) 102 (31.4%)
12 In all, social media is negatively influencing students’ social interaction with others 45 (13.8%) 90 (27.7%) 135 (41,5%) 95 (29.2%) 60 (18.5%) 35 (10.8%) 95 (29.3%)
13 The use of social media limits time with family, friends and loved ones 119 (36.6%) 107 (32.9%) 226 (69.5%) 48 (14.8%) 34 (10.5%) 17 (5.2%) 51 (15.7%)

Question 1 seeks to determine whether using social media platforms assists students to improve their social interaction. The study found that 243 (74.8%) of the students agree that social media platforms improve social interaction. It implies that the social interaction of the student is the function of social media platforms. The finding was backed by Abbas et al. (2019), who found that different social platforms such as WhatsApp, Facebook, Twitter, LinkedIn, and others have opened the new social interaction among students to communicate and engage with peers.

Akram and Kumar (2017) put it that social media platforms facilitate students’ communication and information sharing. The second question (number 2) indicates that 264 (81.2%) of the students suggest that social media platforms enable them to socially interact in communicating and sharing information and ideas with peers and friends. This shows that social media platforms allow students to socially interact with peers and friends in communicating and sharing information.

The third question (question 3) proves that 291 (89.5%) of the participants (students) have the view that social media platforms promote physical distance from friends. The finding implies that social media platforms promote physical distance among friends. This distance is not because friends are far from each other, but they rather spend hours checking social media platforms than engaging and discussing with friends while sitting around. In accordance with Akram and Kumar (2017), many students spend hours daily on their smartphones, laptops, desktops, and other technological devices in surfing different social media platforms, commenting, tweeting, liking, checking pictures, images, and many more

According to question 4, 277 (85.3%) of the students believed that social media platforms promote spending hours on the platforms with engaging effectively on social interaction. It is concluded that students rather spend hours on social media platforms than engaging with each other socially. In support of the finding, social media users spend an enormous amount of time on the platform/s engaging in social activities (Tasir et al., 2011).

When students are social actors on social media platforms, it exposes them to different cyber threats. According to Saravanakumar and Deepa (2016), Gupta and Dhami (2015), and Blasbalg et al. (2012), content sharing on social media platforms exposes users’ (students’) private content to the public. Question 5 shows that 245 (83%) of the students are convinced that social media interaction exposes them to data privacy issues regarding personal information. The finding indicates that social media platforms promote data privacy concerns and personal information. 240 (73.9%) of respondents, in question 6, prove that students use social media platforms to meet and connect with friends and engage in social interaction. The finding shows that social media platforms are a perfect tool for students to socialise.

According to the finding from question 7, it was found that 195 (60%) of the students chose the option that social media platforms encourage cyberbullying and infringement of privacy among the students. It implies that social media use in promoting social interaction negatively impacts students because it can encourage cyberbullying and piracy infringement. Abaido (2020) and Chan, Cheung and Lee (2020) found increased social media cyberbullying usage by students. A question was asked to determine whether social media usage enhances student social life and interaction. The figure on question 8 (Table 2) suggests that 225 (69.2%) of the students feel that social media platform usage increases students’ social life and interaction with others (peers and lecturers). The finding means that social media platforms enhance students’ social life and interactions.

The study found from question 9 that students are indifferent or undecided towards social media platforms’ terrible effect on students’ social interaction. This means that students are not sure whether social media platforms are terrible for their social interaction. Question 10 aimed to understand whether social media platforms do not favour students’ social interaction with peers. It was found that 136 (41.8%) of the students agree that social media platforms are not favourable to students’ social interaction. Following was question 11, which recorded that 120 (36.9%) of the students were undecided or indifferent about whether social media harms students’ social interaction with others. The study found that social media platforms are not harmful to students’ social interaction.

According to Akram and Kumar (2017), students spend hours on social media platforms without engaging with peers and friends who are physically present. The finding is aligned with question 12, which indicates that 135 (41.5%) of students suggest that social media platforms continuously influence students’ social interaction. The finding indicates that social media platforms negatively impact students’ social interaction with each other (peers). Students’ continuous adoption and usage of social media platforms limit time spent with students’ family, friends, and loved ones. The finding from question 13 indicates that 226 (69.5%) of the students in the study believe that social media platforms hinder students’ family time and that of friends and loved ones. The finding is aligned with Procentese et al., (2019), who found that social media impacts family time and relationships.

Chi-square

As an inferential statistic, chi-square works to establish and test the relationship between variables (Ugoni & Walker, 1995; Rana & Singhal, 2015). The testing is categorised in two ways: testing the null hypothesis among two or more variables (theory of no relationship) and goodness-of-fit testing (testing the likelihood of a variable fitting within a more significant dataset) (Rana & Walker, 2015). To this study, the Chi-square test is applied to understand the relationship between two independent variables. The study carried eight (8) chi-square tests. Testing the hypothesis can be done in two ways, either accept or reject the hypothesis.

• alternative), accept Accept = greater than 0.05 (reject alternate hypothesis

• Reject = less than 0.05 (accept alternative), reject the null hypothesis

Usage of social media improves students’ social interaction vs. social media promotes cyberbullying and infringement of privacy (Table 3).

Table 3 Chi-Square Tests
  Value Df Asymp. sig. (2-sided)
Pearson chi-square 35.583a 16 .003
Likelihood ratio 34.261 16 .005
N of valid cases 325    
a. 10 cells (40.0%) have expected count less than 5. The minimum expected count is .39.

H0: There is a relationship between social media usage improving students’ social interaction and social media promoting cyberbullying and infringement of privacy (null hypothesis).

H1: There is no relationship between social media usage improving students’ social interaction and social media promoting cyberbullying and infringement of privacy (alternate hypothesis).

The Pearson’s chi-square value is 35.583 (Table 3) at a degree of freedom of 22. 0.003 is the alpha level of significance, which is less than the set level of 0.05. If the p-value is less than 0.05, then reject the null hypothesis.

Accept the alternate. There is no relationship between social media usage improving students’ social interaction and social media promoting cyberbullying and infringement of privacy (alternate hypothesis).

Social media usage improves students’ social interaction vs. the belief that social media usage enhances students’ social life and interaction (Table 4).

Table 4 Chi-Square Tests
  Value Df Asymp. sig. (2-sided)
Pearson chi-square 226.059a 16 .000
Likelihood ratio 155.477 16 .000
N of valid cases 325    
a. 11 cells (44.0%) have expected count less than 5. The minimum expected count is .28.

H0: There is a relationship between social media usage improving students’ social interaction vs. the belief that social media usage enhances students’ social life and interaction (null hypothesis).

H1: There is no relationship between social media usage improving students’ social interaction vs. the belief that social media usage enhances students’ social life and interaction (alternate hypothesis).

The Pearson’s chi-square value is 226.059 (Table 4) at a degree of freedom (df) of 16. 0.000 is the alpha level of significance, which is less than the set level of 0.05. If the p-value is less than 0.05, then reject the null hypothesis.

Accept the alternate. There is no relationship between social media usage and improving students’ social interaction vs. the belief that social media usage enhances students’ social life and interaction (alternate hypothesis).

The usage of social media improves students’ social interaction against social media is terrible for students’ social interaction (Table 5).

Table 5 Chi-Square Tests
  Value Df Asymp. sig. (2-sided)
Pearson chi-square 49.684a 16 .000
Likelihood ratio 49.008 16 .000
N of valid cases 325    
a. 8 cells (32.0%) have expected count less than 5. The minimum expected count is 1.02.

H0: There is a relationship between social media usage and improving students’ social interaction vs. social media is terrible for students’ social interaction (null hypothesis).

H1: There is no relationship between social media usage and improving students’ social interaction vs. social media is terrible for students’ social interaction (alternate hypothesis).

The Pearson’s chi-square value is 49.684 (Table 5) at a degree of freedom (df) of 16. 0.00 is the alpha level of significance, which is less than the set level of 0.05. If the p-value is less than 0.05, then reject the null hypothesis.

Accept the alternate. There is no relationship between social media usage improving students’ social interaction vs. social media is terrible for students’ social interaction (alternate hypothesis).

Social media usage improves students’ social interaction vs. social media is harmful to social interaction (Table 6).

Table 6 Chi-Square Tests
  Value Df Asymp. sig. (2-sided)
Pearson chi-square 58.049a 16 .000
Likelihood ratio 57.265 16 .000
N of valid cases 325    
a. 8 cells (32.0%) have expected count less than 5. The minimum expected count is .94.

H0: There is a relationship between social media usage improving students’ social interaction vs. social media is harmful to social interaction (null hypothesis).

H1: There is no relationship between social media usage and improving students’ social interaction vs. social media is harmful to social interaction (alternate hypothesis).

The Pearson’s chi-square value is 58.049 (Table 6) at a degree of freedom (df) of 16. 0.00 is the alpha level of significance, which is less than the set level of 0.05. If the p-value is less than 0.05, then reject the null hypothesis.

Accept the alternate. There is no relationship between social media usage improving students’ social interaction vs. social media is harmful to social interaction (alternate hypothesis).

The usage of social media improves students’ social interaction vs. social media is negatively influencing students’ social interaction with others (Table 7)

Table 7 Chi-Square Tests
  Value Df Asymp. sig. (2-sided)
Pearson chi-square 57.587a 16 .000
Likelihood ratio 58.234 16 .000
N of valid cases 325    
a. 8 cells (32.0%) have expected count less than 5. The minimum expected count is .97.

H0: There is a relationship between social media usage and improving students’ social interaction vs. social media negatively influencing students’ social interaction with others (null hypothesis).

H1: There is no relationship between social media usage and improving students’ social interaction vs. social media negatively influencing students’ social interaction with others (alternate hypothesis).

The Pearson’s chi-square value is 57.587 (Table 7) at a degree of freedom (df) of 16. 0.00 is the alpha level of significance, which is less than the set level of 0.05. If the p-value is less than 0.05, then reject the null hypothesis.

Accept the alternate. There is no relationship between social media usage and improving students’ social interaction vs. social media negatively influencing students’ social interaction with others (alternate hypothesis).

The usage of social media improves students’ social interaction vs. the use of social media limits time with family, friends and loved ones (Table 8).

Table 8 Chi-Square Tests
  Value Df Asymp. sig. (2-sided)
Pearson chi-square 28.600a 16 .027
Likelihood ratio 29.055 16 .024
N of valid cases 325    
a. 10 cells (40.0%) have expected count less than 5. The minimum expected count is .47.

H0: There is a relationship between social media usage improves students’ social interaction vs. the use of social media limits time with family, friends and loved ones (null hypothesis).

H1: There is no relationship between social media usage improves students’ social interaction vs. the use of social media limits time with family, friends and loved ones (alternate hypothesis).

The Pearson’s chi-square value is 28.600 (Table 8) at a degree of freedom (df) of 16. 0.027 is the alpha level of significance, which is greater than the set level of 0.05. If the p-value is greater than 0.05, then reject the alternate hypothesis.

Accept the null hypothesis. There is a relationship between social media usage improves students’ social interaction vs. the use of social media limits time with family, friends and loved ones (null hypothesis).

Social media use improves students’ communication and sharing of information with friends and peers vs. the belief that social media usage enhances students’ social life and interaction (Table 9).

Table 9 Chi-Square Tests
  Value Df Asymp. sig. (2-sided)
Pearson chi-square 168.057a 16 .000
Likelihood ratio 130.946 16 .000
N of valid cases 325    
a. 12 cells (48.0%) have expected count less than 5. The minimum expected count is .34.

H0: There is a relationship between social media use improves students’ communication and sharing of information with friends and peers vs. the belief that social media usage enhances students’ social life and interaction (null hypothesis).

H1: There is no relationship between using social media to improve students’ communication and sharing of information with friends and peers vs. the belief that social media usage enhances students’ social life and interaction (alternate hypothesis).

The Pearson’s chi-square value is 168.057 (Table 9) at a degree of freedom (df) of 16. 0.000 is the alpha level of significance, which is less than the set level of 0.05. If the p-value is less than 0.05, then reject the null hypothesis.

Accept the alternate. There is no relationship between social media use improves students’ communication and sharing of information with friends and peers vs. the belief that social media usage enhances students’ social life and interaction (alternate hypothesis).

The use of social media promotes physical distance among friends vs. the belief that social media usage enhances students’ social life and interaction (Table 10).

Table 10 Chi-Square Tests
  Value Df Asymp. sig. (2-sided)
Pearson chi-square 68.911a 16 0.000
Likelihood ratio 67.667 16 0.000
N of valid cases 325    
a. 16 cells (64.0%) have expected count less than 5. The minimum expected count is .12.

H0: There is a relationship between social media use and physical distance among friends vs. the belief that social media usage enhances students’ social life and interaction (null hypothesis).

H1: There is no relationship between social media use promotes physical distance among friends vs. the belief that social media usage enhances students’ social life and interaction (alternate hypothesis).

The Pearson’s chi-square value is 69.911 (Table 10) at a degree of freedom (df) of 16. 0.000 is the alpha level of significance, which is less than the set level of 0.05. If the p-value is less than 0.05, then reject the null hypothesis.

Accept the alternate. There is no relationship between social media use promotes physical distance among friends vs. the belief that social media usage enhances students’ social life and interaction (alternate hypothesis).

The use of social media promotes physical distance among friends vs. that social media is terrible for social interaction (Table 11).

Table 11 Chi-Square Tests
  Value Df Asymp. sig. (2-sided)
Pearson chi-square 44.122a 16 .000
Likelihood ratio 48.369 16 .000
N of valid cases 325    
a. 14 cells (56.0%) have expected count less than 5. The minimum expected count is .46.

H0: There is a relationship between social media use promotes physical distance among friends vs. social media is terrible for social interaction (null hypothesis).

H1: There is no relationship between social media use and physical distance among friends vs. social media is terrible for social interaction (alternate hypothesis).

The Pearson’s chi-square value is 44.122 (Table 11) at a degree of freedom (df) of 16. 0.000 is the alpha level of significance, which is less than the set level of 0.05. If the p-value is less than 0.05, then reject the null hypothesis.

Accept the alternate. There is no relationship between social media use and physical distance among friends vs. social media is terrible for social interaction (alternate hypothesis).

The use of social media promotes physical distance among friends vs. the use of social media limits time with family, friends and loved ones (Table 12).

Table 12 Chi-Square Tests
  Value Df Asymp. sig. (2-sided)
Pearson chi-square 41.194a 16 .001
Likelihood ratio 39.868 16 .001
N of valid cases 325    
a. 13 cells (52.0%) have expected count less than 5. The minimum expected count is .21.

H0: There is a relationship between using social media to promote physical distance among friends vs. the use of social media limits time with family, friends and loved ones (null hypothesis).

H1: There is no relationship between using social media to promote physical distance among friends vs. the use of social media limits time with family, friends and loved ones (alternate hypothesis).

The Pearson’s chi-square value is 41.194 (Table 12) at a degree of freedom (df) of 16. 0.001 is the alpha level of significance, which is less than the set level of 0.05. If the p-value is less than 0.05, then reject the null hypothesis.

Accept the alternate. There is no relationship between using social media to promote physical distance among friends vs. the use of social media limits time with family, friends and loved ones (alternate hypothesis).

The use of social media encourages students to spend hours (time) online vs. social media is harmful to social interaction (Table 13).

Table 13 Chi-Square Tests
  Value Df Asymp. sig. (2-sided)
Pearson chi-square 46.467a 16 .000
Likelihood ratio 48.279 16 .000
N of valid cases 325    
a. 12 cells (48.0%) have expected count less than 5. The minimum expected count is .73.

H0: There is a relationship between social media’s use encouraging students to spend hours (time) online vs. social media and is harmful to social interaction (null hypothesis).

H1: There is no relationship between social media use encouraging students to spend hours (time) online vs, social media and is harmful to social interaction (alternate hypothesis).

The Pearson’s chi-square value is 48.467 (Table 13) at a degree of freedom (df) of 16. 0.000 is the alpha level of significance, which is less than the set level of 0.05. If the p-value is less than 0.05, then reject the null hypothesis.

Accept the alternate. There is no relationship between using social media encouraging students to spend hours (time) online vs. social media is harmful to social interaction (alternate hypothesis).

The use of social media encourages students to spend hours (time) online vs. social media usage limits time with family, friends and loved ones (Table 14).

Table 14 Chi-Square Tests
  Value Df Asymp. sig. (2-sided)
Pearson chi-square 107.250a 16 0.000
Likelihood ratio 94.625 16 0.000
N of valid cases 325    
a. 13 cells (52.0%) have expected count less than 5. The minimum expected count is .37.

H0: There is a relationship between using social media encourages students to spend hours (time) online vs. the use of social media limits time with family, friends and loved ones (null hypothesis).

H1: There is no relationship between using social media encourages students to spend hours (time) online vs. the use of social media limits time with family, friends and loved ones (alternate hypothesis).

The Pearson’s chi-square value is 107.250 (Table 14) at a degree of freedom (df) of 16. 0.000 is the alpha level of significance, which is less than the set level of 0.05. If the p-value is less than 0.05, then reject the null hypothesis.

Accept the alternate. There is no relationship between using social media encourages students to spend hours (time) online vs. the use of social media limits time with family, friends and loved ones (alternate hypothesis).

The use of social media is a useful tool in meeting friends vs. the use of social media limits time with family friends, and loved ones (Table 15).

Table 15 Chi-Square Tests
  Value Df Asymp. sig. (2-sided)
Pearson chi-square 64.733a 16 .000
Likelihood ratio 68.051 16 .000
N of valid cases 325    
a. 9 cells (36.0%) have expected count less than 5. The minimum expected count is .63.

H0: There is a relationship between social media use as a useful tool in meeting friends vs. the use of social media limits time with family, friends and loved ones (null hypothesis).

H1: There is no relationship between social media use as a useful tool in meeting friends vs. the use of social media limits time with family, friends and loved ones (alternate hypothesis).

The Pearson’s chi-square value is 64.733 (Table 15) at a degree of freedom (df) of 16. 0.000 is the alpha level of significance, which is less than the set level of 0.05. If the p-value is less than 0.05, then reject the null hypothesis.

Accept the alternate. There is no relationship between social media use as a useful tool in meeting friends vs. the use of social media limits time with family, friends and loved ones (alternate hypothesis).

Contribution to Academic Knowledge

Social interaction is critical for students to express and apply real-life knowledge into the academic world and vice versa. This study provided a comprehensive contribution to the academic field and other professionals in understanding the role that social media platforms play in students’ social interactions. The study highlighted some of these contributions for students and other stakeholders:

1. Social media improves students’ social interaction, such as communication and information sharing with peers and friends.

2. It promotes physical distance among friends because friends rather spend long hours on their social media platforms than interacting with each other.

3. Social media platforms assist university students in organising meetings, promoting cyberbullying, data privacy, and personal information infringement.

4. Students believe that social media platforms can be favourable for friends’ social interaction, but it could be harmful and negatively impacting their quality time with loved ones and friends.

5. There is no relationship between the usage of social media improving students’ social interaction vs. the belief that social media usage enhances students’ social life and interaction.

6. There is a relationship between social media usage improving students’ social interaction vs. the use of social media limits time with family, friends and loved ones.

7. There is no relationship between the use of social media encourages students to spend hours (time) online vs. the use of social media limits time with family, friends and loved ones.

Through this study, students gain a good and comprehensive insight into social media platforms’ ability to positively and negatively harm their social interaction and quality time with friends and loved ones.

Conclusion

Social media platforms continue to impact human social life and interactions. This study determined the impact that social media platforms have on students’ social interaction and activities in the university environment and society in general. The findings highlight the positive and negative impact of social media platforms on students’ social interaction. However, these impacts could be managed and guided so that students can socialize effectively and meaningfully in this digital age. Social media researchers should look into the platforms’ impact on students’ academic performance and progress in the future. Furthermore, researchers could seek to understand the effect of social interaction on adequate learning progress.

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