INTRODUCTION:

Social media has made a vital impact on different aspects of society over the past few years especially in the way people communicate and share information. Through video sharing sites, wikis, forums, etc., social networking sites (SNS) provide an active, free and open platform for grabbing knowledge and connecting socially to any interested user regardless of their socio-demographic characteristics such as age or gender Huang, Hood, and Yoo, Osatuyi, (2013). Furthermore, this platform provides the perfect medium for personalized informal learning in the domains that the user is interested in, and increases the motivation to continue the learning process (Bull et al., 2008). For ease of understanding the influence of social media landscape, the total time spent on it has been calculated and further it is projected in comparison to many other regular activities.

(http://www.businessinsider.com/how-much-time-do-people-spend-on-facebook-per-day-2016-4) Kalpana Chauhan and Anandan Pillai (2011) initiated an attempt to simplify the role of content strategy followed by leading higher education institutes who have created brand community on social media in India to make people aware about the same.

Social media usage has increased in areas such as: health, shopping, education, social networking, marketing etc. Demographic factors like age, income, gender, occupation etc have a huge impact on the usage pattern of social media. show that the teenagers usually use the Internet for social networking and communication. In this context, analyzing the purposes of Internet usage of the high school students, the relationship between these purposes and the demographic variables, and determining important factors affecting the purposes of social media usage are the objectives of this research. The main objective of research answering the following research question: “What are the demographic factors affecting social media usage?” (https://www.researchgate.net/publication/320556687_Factors_affecting_the_use_of_social_media_in_the_learning_process) Ruchi Sachdev (2015) discusses the role of social media in today’s society in terms of it play more of a positive or a negative role for the masses. Reynol Junco (2017) has studied the relationship between multiple indices of facebook usage and its relationship with academic performance of students in the United States.Ruth N. Bolton, A. Parasuraman, Ankie Hoefnagels and co-authors (Jan 2013) have studied the generation Y and how they use the social media. Wexlr Lisa, Aline Gubrim, Megan gifin and Gloria Diflvo (2015) have studied the role of digital world for promoting positive youth development and showing the reasons for living in northwest Alaska.

The role of the Internet and smartphone has been increasing in the daily life of many people around the globe and the studies on the Internet widely use individuals’ demographic characteristics in explaining the nature of usage. For example, in an earlier study, Taylor, Zhu, Dekkers and Marshall (2003) claimed that Internet usage pattern may have different dispersions for different gender groups out of total population who uses smartphones. Kalmus, Realo and Siibak (2011) age, income level, education level are the significant predictors of adoption and usage patterns of social media. On the other hand, the nature of Internet has changed drastically with the increasing popularity of social media especially during the last few yearsThis scenario has attracted the attention of higher education institutions. More specifically, Calisir, Atahan and Saracoglu (2013) pointed that differences may be significantly explained by the demographic characteristics for the adoption and usage pattrens of Social Network Sites (SNS), which means demographic characteristics should be taken into consideration, as the nature and consequences of SNS usage could be potentially different for different demographic groups.

RESEARCH METHODOLOGY:

Objectives of the study:

The core objective of the study is to understand the difference among demographic factors with respect to social media influence in Ahmedabad city. To identify the factors of demographic that have an impact on usage pattern of social media.

Data collection:

Secondary Data collection:

In this research, the researcher has used many resources of secondary data collection. Recent newspapers, research journals, media websites, books, magazines, published research papers in the national and international journals have been referred for the secondary data. Recent cases involving use of social media have been taken from various English and Gujarati newspapers and online papers. Even some articles from the supplements of a newspaper have been discussed. Websites of media channels like Times of India, NDTV and Mint have been cited where n when content has been taken and various online dictionaries like Oxford and Cambridge have been referred to, to get the theoretical content and various definitions for many terms.

Primary data collection:

For collection of primary data, researcher has used structured questionnaire which consist of the parameters of social media influence on youngsters.

Sample frame:

With reference to collect the data, researcher has considered any male or female, falling in the age group of 15 to 35, resident of Ahmedabad city and using social media for the last 6 months.

Sample size:

1133 samples have been taken from various areas of Ahmedabad city.

Data Analysis:

Age * Influence of social media:

H₀: There is no significant difference amongst various age group regarding the positive influence of social media

H₁: There is significant difference amongst various age group regarding the positive influence of social media

Table 1. 1 Descriptive Statistics

Dependent Variable: SUMMATED_COMBINPOSITIVE
Age Group	Mean	Std. Deviation	N
15-20	42.0000	10.11691	234
21-25	39.8509	10.56275	523
26-30	39.8062	11.35577	227
31-35	35.6081	12.14069	148
Total	39.7314	10.99105	1132

This table 1.1 shows the descriptive statistics of overall changes in positive manners because of social media. Mean stands for the average value while standard deviation shows the fluctuations. Our objective is to check whether there is any significant difference amongst the various age values. The researcher has also evaluated whether the variance is homogeneous or not through the Levence’s Test.

Table 1.2 Levene's Test of Equality of Error Variances^a

Dependent Variable: SUMMATED_COMBINEDPOSITIVE
F	df1	df2	Sig.
9.106	3	1130	.000

Tests the null Hypothesis that the error variance of the dependent variable is equal across groups.

a. Design: Intercept + Q0.1

The Levene’s Test table indicated that F ratio between and within the sample is 9.106 it means variations between the samples is 9 times more than the variations within the samples. While significant value of the test is 0.00 which is less than 0.05, it indicates that there is a significant difference amongst the value of variance in different groups.

Table 1.3 ANOVA

Source	Type III Sum of Squares	df	Mean Square	F	Sig.
Corrected Model	3729.252^a	3	1243.084	10.551	.000
Intercept	1425691.887	1	1425691.887	12100.762	0.000
Questions	3729.252	3	1243.084	10.551	.000
Error	132899.109	1128	117.818
Total	1923590.000	1132
Corrected Total	136628.360	1131

Table 1.4 Multiple Comparisons

Dependent Variable: SUMMATED_COMBINEDNEGATIVE Tukey HSD
(I) Age Group		Mean Difference (I-J)	Std. Error	Sig.	95% Confidence Interval
(I) Age Group		Mean Difference (I-J)	Std. Error	Sig.	Lower Bound	Upper Bound
15-20	21-25	2.1491	.85368	.058	-.0473	4.3455
	26-30	2.1938	1.01120	.132	-.4078	4.7955
	31-35	6.3919^*	1.13999	.000	3.4589	9.3249
21-25	15-20	-2.1491	.85368	.058	-4.3455	.0473
	26-30	.0447	.86273	1.000	-2.1750	2.2644
	31-35	4.2428^*	1.01062	.000	1.6426	6.8429
26-30	15-20	-2.1938	1.01120	.132	-4.7955	.4078
	21-25	-.0447	.86273	1.000	-2.2644	2.1750
	31-35	4.1981^*	1.14678	.001	1.2476	7.1486
31-35	15-20	-6.3919^*	1.13999	.000	-9.3249	-3.4589
	21-25	-4.2428^*	1.01062	.000	-6.8429	-1.6426
	26-30	-4.1981^*	1.14678	.001	-7.1486	-1.2476

Based on observed means.

The error term is Mean Square(Error) = 117.818.

*. The mean difference is significant at the .05 level.

By analyzing the Tukey multiple comparisons, We can find the mean difference of 21 to 25 is 2.14 and significant value is 0.058 similarly for 26 to 30, it is 2.19 and significant value is 0.132, which is more than 0.05, it indicates that these two categories are not significantly different in terms of average value for overall positive changes occurring because of the social media. While analyzing the Tukey multiple comparison for the various age groups of 21 to 25, the mean difference of 15 to 20 is -2.14 and significant value is 0.58, similarly for 26 to 30, the mean difference is 0.0447 and the significant difference is 1.00; with the age group 31-35, the mean difference is 4.24 and the significant difference is 0.0.By analyzing the Tukey multiple comparisons, the mean difference of 15 to 20 is -2.19 and significant value is 0.132, similarly for 21 to 25, it is -0.044 and significant value is 1.00, which is quite more than 0.05, indicating that these two categories are similar in terms of average value for overall positive changes occurring because of the social media. 31 to 35: Considering the mean differences and the significant values of the age groups of 15 to 29, 21 to 25 and 26 to 30 in the Tukey multiple comparisons the mean differences -6.39, -4.24 and -4.19 and the significant differences 0.0, 0.0 and 0.001, all of these are less than 0.05, indicating that all of these categories are similar in terms of influences of social media.

Income * Influence of social media:

H₀: There is no significant difference amongst various income groups regarding social positive influence of social media.

H₁: There is significant difference amongst various income groups regarding social positive influence of social media.

Table 1.5 Descriptive Statistics

Dependent Variable: SUMMATED_SOCIALPOSITIVE
Family Income	Mean	Std. Deviation	N
Less than 2 lac	29.4045	4.99485	267
Between 2.1 lac- 5 lac	30.4609	4.61404	447
5.1 lac – 10 lac	30.8157	4.56837	293
10 lac p.a – to 20 lac	30.4896	5.08040	96
More than 20 lac	31.1034	6.96596	30
Total	30.3224	4.82783	1133

This table shows the descriptive statistics of Social influences of social media with reference to various young social media users across various family incomes. Mean stands for the average value while standard deviation shows the fluctuations. Our objective is to check whether there is any significant difference amongst the various values of annual family income. The researcher also evaluated whether the variance is homogeneous or not through the Levence’s Test.

Table 1.6 Levene's Test of Equality of Error Variances^a

Dependent Variable: SUMMATED_SOCIALPOSITIVE
F	df1	df2	Sig.
4.394	4	1127	.002

Tests the null Hypothesis that the error variance of the dependent variable is equal across groups.

a. Design: Intercept + Q0.11

The Levene’s Test table indicated that F ratio between and within the sample is 4.394 it means variations between the samples is four times more than the variations within the samples. While significant value of the test is 0.002 which is less than 0.05, it indicates that there is significant difference amongst the value of variance in different groups. By analyzing the descriptive statistics, the highest fluctuations is 6.96 in the group no 5 for the income group of more than 5 lacs while the smallest variations is 4.56 in the range of 5.1 to 10.

Table 1.7 ANOVA

Source	Type III Sum of Squares	df	Mean Square	F	Sig.
Corrected Model	325.204^a	4	81.301	3.519	.007
Intercept	427064.342	1	427064.342	18485.925	0.000
Question	325.204	4	81.301	3.519	.007
Error	26036.107	1127	23.102
Total	1067179.000	1132
Corrected Total	26361.310	1131

Table 1.8

	Independent Samples Test
		Levene's Test for Equality of Variances		t-test for Equality of Means
		F	Sig.	t	df	Sig. (2-tailed)	Mean Difference	Std. Error Difference	95% Confidence Interval of the Difference
									Lower	Upper
Summated_Combinedpositive	Equal variances assumed	17.990	.000	1.815	1129	.070	1.52718	.84152	-.12393	3.17830
	Equal variances not assumed			1.901	1077.582	.058	1.52718	.80318	-.04879	3.10316

Considering the independent sample test table, the value F suggest 17.99 with significant value is 0.00, it indicates that Levance Test significant value which is less than 0.05, it indicates that there is no similarity in the variance between male and female. Considering the T value is 1.815, and significant two tailed value is 0.07, which is less than 0.05, so we reject null Hypothesis. It indicates that there is significant difference between male and female regarding the overall Negative influence Combined factors with respect to social media. The mean difference between the male and female is 1.52 for the sample size and it should lie between -0.12 and 3.17 for the entire population of the Ahmedabad city.

Educational Level * Influence of social media:

H₀: There is no significant difference amongst various education levels regarding influence of social media.

H₁: There is a significant difference amongst various education levels regarding influence of social media.

Table 1. 9 Descriptive Statistics

Dependent Variable: Overall_Influence_Combinepositive_Negative
Student	Mean	Std. Deviation	N
School Going	122.4341	18.32853	129
Under Graduate	116.4505	17.92803	404
Post Graduate	116.4928	18.91993	489
Higher Degree	117.1651	21.63267	109
Total	117.2202	18.85581	1131

This table shows the descriptive statistics of overall influences of social media with reference to various educational levels. Mean stands for the average value while standard deviation shows the fluctuations. Our objective is to check whether there is any significant difference amongst the various values of annual family income.

Table 1.10 Tests of Between-Subjects Effects

Dependent Variable: Overall_Influence_Combinepositive_Negative
Source	Type III Sum of Squares	df	Mean Square	F	Sig.
Corrected Model	4005.228^a	3	1335.076	3.783	.010
Intercept	10411798.037	1	10411798.037	29500.669	0.000
Q0.4Edu	4005.228	3	1335.076	3.783	.010
Error	397756.952	1127	352.934
Total	15942342.000	1131
Corrected Total	401762.180	1130

a. R Squared = .010 (Adjusted R Squared = .007)

b. Computed using alpha = .05

Table 1. 11 Multiple Comparisons

Dependent Variable: Overall_Influence_Combinepositive_Negative Scheffe
(I) Student		Mean Difference (I-J)	Std. Error	Sig.	95% Confidence Interval
(I) Student		Mean Difference (I-J)	Std. Error	Sig.	Lower Bound	Upper Bound
School Going	Under Graduate	5.9836^*	1.89987	.020	.6645	11.3027
	Post Graduate	5.9413^*	1.85948	.017	.7352	11.1473
	Higher Degree	5.2690	2.44415	.200	-1.5739	12.1119
Under Graduate	School Going	-5.9836^*	1.89987	.020	-11.3027	-.6645
	Post Graduate	-.0423	1.26307	1.000	-3.5786	3.4939
	Higher Degree	-.7146	2.02769	.989	-6.3916	4.9623
Post Graduate	School Going	-5.9413^*	1.85948	.017	-11.1473	-.7352
	Under Graduate	.0423	1.26307	1.000	-3.4939	3.5786
	Higher Degree	-.6723	1.98989	.990	-6.2434	4.8988
Higher Degree	School Going	-5.2690	2.44415	.200	-12.1119	1.5739
	Under Graduate	.7146	2.02769	.989	-4.9623	6.3916
	Post Graduate	.6723	1.98989	.990	-4.8988	6.2434

Based on observed means. The error term is Mean Square (Error) = 352.934.

*. The mean difference is significant at the .05 level.

If we analyse the Tukey multiple comparisons, the mean difference with under graduates is 5.98 and significant value is 0.09, which is more than 0.05, it indicates that these two categories are not significantly different in terms of average value for overall changes occurring because of the social media. After analyzing the Tukey multiple comparisons, the mean difference with school going students is -5.98 and significant value is 0.020 similarly for the post graduates, the it mean is -.0423, and significant value is 1.00, which is more than 0.05, it indicates that these two categories are not significantly different in terms of average value for overall changes occurring because of the social media. If we analyse the Tukey multiple comparisons, the mean difference with school going students is -5.94 and significant value is 0.017 similarly for the under graduates, the it mean is 0.0423, and significant value is 1.00, which is more than 0.05, it indicates that these two categories are not significantly different in terms of average value for overall changes occurring because of the social media. After analyzing the Tukey multiple comparisons, the mean difference with school going students is -5.26 and significant value is 0.200 similarly for the under graduates, the it mean is 0.71, and significant value is 0.989, which is more than 0.05, it indicates that these two categories are not significantly different in terms of average value for overall changes occurring because of the social media.

FINDING:

According to analysis the positive influence of the combined factors, male and female both genders have found to be having different in terms of influences. There can be multiple factors behind this difference of both the genders. Both the genders are motivated with different things respectively, have different aspirations, have differences in thought process and even there are differences found in brought up of both the genders in the society today. The values, mindsets, ambition, the influences etc usually differ and hence it is reflected in the research.

From analysis it is observed that there is significant difference amongst various age groups regarding overall influence of social media. In terms of being benefitted by using social media, the various age groups have different results on the positive side. The final result is quite evident considering the difference influencing factors like age, educational background, occupation etc differs a lot across the age groups.

There is significant difference amongst various income groups regarding social influence of social media. Individuals among the various income groups have different peer groups and the amount of participant and the amount of activity varies across the various income groups, which can be the reason for this finding.

Post Graduate and Higher Degree have proximate similarities in terms of Overall combined influence of social media. Both the post graduates and the individuals who are pursuing higher degree education have many similar opinions which may be the reason of their close similarity in the behavior with reference to the overall positive as well as influences of social media. Few of the aspects can be life cycle stage, similar age group, and financial independence

REFERENCE:

1. Bolton et.all,(2013), Understanding Generation Y and their use of social media:a review and research agenda, Journal of Service Management, Journal of Service ManagementVol. 24 No. 3, 2013pp. 245-267

2. Chakraborty, (2013), Using Social Networking Services Effectively for a Successful e-Governance in India

3. Cheung et.all,(2010), Online social networks: Why do students use facebook?, Computers in Human Behavior,Computers in Human Behavior 27 (2011) 1337–1343

4. Christy M.K. Cheung, Matthew K.O. Lee, (2009), A theoretical model of intentional social action in online social networks, Decision Support Systems, Decision Support Systems 49 (2010) 24–30

5. communities: a case of higher education institutes in India, Journal of Product and Brand Management, Journal of Product and Brand Management 22/1 (2013) 40–51

6. Denskus and Esser,(2013), Social Media and Global Development Rituals: a content analysis of blogs and tweets on the 2010 mdg Summit, Third World Quarterly, ISSN 0143-6597 print/ISSN 1360-2241 online/13/000405-18

7. Dhume, Pattanshetti, Kamble and others, (2011), Adoption of Social Media by Business Education Students: Application of Technology Acceptance Model (TAM), National Institute of Industrial Engineering, Journal of Advertising Research, 44(4), 333-348.

8. Hughes et.all(2011), A tale of two sites: Twitter vs. Facebook and the personality predictors of social media usage, Computers in Human Behavior,Computers in Human Behavior 28 (2012) 561–569

9. Kalpana Chauhan, Anandan Pillai(2013), Role of content strategy in social media brand

10. Rishika, Kumar, Janakiraman,(2012), The Effect of Customers’ Social Media Participation on Customer Visit Frequency and Profitability:An Empirical Investigation,Information Systems Research, ISSN 1047-7047 (print). ISSN 1526-5536 (online)

11. Saw, Abbott and Donaghey, Carolyn McDonald,(2012), Social media for International students – it’s not all about Facebook, www.emeraldinsight.com/0143-5124.html

Received on 31.10.2018 Modified on 19.01.2019

Res. J. Humanities and Social Sciences. 2019; 10(2): 709-714.

DOI: 10.5958/2321-5828.2019.00117.7