Social networking sites and employment status: an investigation based on Understanding Society data

Social networking sites and employment status: an investigation based on

Understanding Society dataBy John Mowbray

Co authors: Professor Robert RaesideProfessor Hazel HallDr Peter Robertson

2nd International Data and Information Management Conference 12 th & 13th January 2016

Twitter: @jmowb_napier

Structure of presentation• Understanding society: The UK household longitudinal study

• Background themes from the literature– The significance of social networks to job search– Social networking sites and job search

• Hypotheses• Sample and method• Results• Discussion• Future research directions

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• Innovative study about 21st century life in the UK

• Longitudinal perspective on how UK life is changing

• Derives information about peoples’:– Social and economic circumstances– Attitude– Behaviour – Health

Source: University of Essex. Institute for Social and Economic Research and National Centre for Social Research/TNS BMRB, Understanding Society: Innovation

Panel, Waves 1-7, 2008-2014 [computer file]. Colchester, Essex: UK Data Archive [distributor], July 2015. SN: 6849

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Variables analysed for paper:

• Membership of SNS• Frequency of SNS use• Number of close friends• Employment status• Age• Sex

Source: University of Essex. Institute for Social and Economic Research and National Centre for Social Research/TNS BMRB, Understanding Society: Innovation

Panel, Waves 1-7, 2008-2014 [computer file]. Colchester, Essex: UK Data Archive [distributor], July 2015. SN: 6849

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Background themes from the literature

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The significance of social networks to job search

• Crucial job information can be attained from network contacts

• Network structure is key– E.g. strong & weak ties

• Access to social capital is also important

• “Networking” a concept in job search theory

3D Social Networking © Photo by: Potter, C. (2012) Web: www.stockmonkeys.com Licence: https://creativecommons.org/licenses/by-sa/2.0/legalcode

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http://www.stockmonkeys.com/

Social networking sites and job search

Social Media apps © Photo by: Howie, J. (2013) Web: https://goo.gl/kynW66 Licence: https://creativecommons.org/licenses/by-sa/2.0/legalcode

• The use of digital technologies during job search is an area which is under researched

• Social media afford unprecedented information gathering capacities

• SNS associated with higher levels of social capital

• SNSs facilitate online networks which proffer– sharing and networking– Channels for strong/weak ties

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https://goo.gl/kynW66

https://goo.gl/kynW66

Hypotheses

H1o: Employment status is not associated with membership of SNSs.

H2o: Employment status is not associated with frequency of SNS use.

H3o: Employment status is not associated with number of close friends.

H4o: Age is not associated with membership of SNSs.

H5o: Sex is not associated with the use of SNSs.

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Sample and method• Sample of 3,616 16-21 year olds

– 24% employed, 11% unemployed, 65% students

• Hypotheses tested using Chi square analysis and independent t-tests

• Binary logistic regression model fitted to understand multivariate effects– Controlling for sex and age– To determine the relationship between SNS membership, close friends,

and employment status– n=1,266 (students removed)

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Results

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Hypotheses a / r Analysis

H1o: Employment status is not associated with membership of SNSs

r 92% of employed were members. 83.2% unemployed were members (p<0.001)


r Evidence of association, although not a linear one.


a 6.05 mean friends amongst employed, 5.88 amongst unemployed (p=0.674)

H4o: Age is not associated with membership of SNSs. r 18.34 mean age of members, 18.68 mean age of non-members (p=0.001).

H5o: Sex is not associated with the use of SNSs. r Females higher users of SNSs (90.1% to 88.1%) (p=0.001). Also, females more frequent users (33% > 3 hours per day to 28%) (p<0.001).

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r 92% employed, and 83.2% unemployed were members (p<0.001).






r 18.34 mean age of members, 18.68 mean age of non-members (p=001).


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Frequency of SNS use (n=3616)

Hours per day spent interacting with friends through SNSs

Economic Status noneunder an

hour 1-3 hours 4-6 hours7 or more

hours

Employed 4.5% 30.3% 36.9% 16.1% 12.3%

Unemployed 6.3% 21.2% 33.9% 20.6% 18.0%

Student 3.4% 26.5% 40.1% 17.0% 12.9%

All respondents 4.0% 26.9% 38.7% 17.2% 13.3%

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r 18.34 mean age of members, 18.68 mean age of non-members (p=0.001).


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H1o Employment status is not associated with membership of SNSs

r 92% employed, and 83.2% unemployed were members (p<001).







H5o: Sex is not associated with the use of SNSs.

r Females higher users of SNSs (90.1% to 88.1%) (p=0.001). Also, females more frequent users (33% > 3 hours per day to 28%) (p<0.001).

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r Logistic regression model confirmed the association, and predicted 68.8% of respondents correctly





H4o: Age is not associated with membership of SNSs. r 18.34 mean age of members, 18.68 mean age of non-members (p=001).


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Discussion• Direction of causality?

• What is the nature of SNS use?

• Functional and/or social?

• What is the role of “weak ties” in information sharing?

Society Gates © Photo by: Lleberwirth, R. (2014) Web: https://goo.gl/jhzbWR Licence: https://creativecommons.org/licenses/by-sa/2.0/legalcode

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https://goo.gl/jhzbWR

https://goo.gl/jhzbWR

Future research directions

• To determine the information needs of young jobseekers

• To determine how young jobseekers engage in networking behaviours during job search– Who are they asking (i.e. people and or/organisations)?– What social media tools are they using?– What is the online/offline divide?

• To determine the barriers and enablers young jobseekers face to networking

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References• Bell, D., & Blanchflower, D. G. (2010). Young people and recession: A lost generation?. In Fifty-Second

Panel Meeting on Economic Policy, Einaudi Institute for Economics and Finance, October, 22-23.

• Beaudoin, C. E., & Tao, C. C. (2007). Benefiting from social capital in online support groups: An empirical study of cancer patients. CyberPsychology & Behavior, 10(4), 587-590.

• Ellison, N. B., Steinfield, C., & Lampe, C. (2007). The benefits of Facebook “friends”: social capital and college students’ use of online social network sites. Journal of Computer‐Mediated Communication, 12(4), 1143-1168.

• Finlay, I., Sheridan, M., McKay, J., & Nudzor, H. (2010). Young people on the margins: in need of more choices and more chances in twenty‐first century Scotland. British Educational Research Journal, 36(5), 851–867.

• Gibson, C., H. Hardy III, J., & Ronald Buckley, M. (2014). Understanding the role of networking in organizations. Career Development International, 19(2), 146-161.

• Granovetter, M. S. (1973). The strength of weak ties. American journal of sociology, 1360-1380.

• Granovetter, M. (1974). Getting a job. Cambridge, MA: Harvard University Press.

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References (2)• Kietzmann, J. H., Hermkens, K., McCarthy, I. P., & Silvestre, B. S. (2011). Social media? Get serious!

Understanding the functional building blocks of social media. Business horizons, 54(3), 241-251.

• Ofcom (2014). Adults’ Media Use and Attitudes Report. [Online]. Available at: http://stakeholders.ofcom.org.uk/binaries/research/media-literacy/adults-2014/2014_Adults_report.pdf [Accessed 20th February 2015].

• Smith, S. S. (2005). Don’t put my name on it: social capital activation and job‐finding assistance among the black urban poor. American Journal of Sociology, 111(1), 1-57.

• Valenzuela, S., Park, N., & Kee, K. F. (2009). Is there social capital in a social network site?: Facebook use and college students' life satisfaction, trust, and participation. Journal of Computer‐Mediated Communication, 14(4), 875-901.

• Verhaeghe, P.-P., Van der Bracht, K., & Van de Putte, B. (2015). Inequalities in social capital and their longitudinal effects on the labour market entry. Social Networks, 40, 174–184.

• Wanberg, C. R., Kanfer, R., & Banas, J. T. (2000). Predictors and outcomes of networking intensity among unemployed job seekers. Journal of Applied Psychology, 85(4), 491.

• Wolff, H. G., & Kim, S. (2012). The relationship between networking behaviors and the Big Five personality dimensions. Career Development International, 17(1), 43-66.

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http://stakeholders.ofcom.org.uk/binaries/research/media-literacy/adults-2014/2014_Adults_report.pdf

Any Questions?

Blog site:www.johnmowbray.org

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Social networking sites and employment status: an investigation based on Understanding Society data

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