The young professionals career success based on LinkedIn as the professional social network site Authors: Jakub Kania and Kamila Wegrzyn
AGENDA 1.Aim of the research 2.Hyphotesis 3.Data collection process 4.Collected data 5.Methods 6.Conclusion
AGENDA 1.Aim of the research 2.Hyphotesis 3.Data collection process 4.Collected data 5.Methods 6.Conclusion
AIM OF THE RESEARCH: To verify if there are connections between each piece of information included in the LinkedIn profile of an individual user.
AGENDA 1.Aim of the research 2.Hypothesis 3.Data collection process 4.Collected data 5.Methods 6.Conclusion
H1: Creating a network of professional contacts has a positive impact on the career development. We would like consider a relationship between career development - understood as a level of the position (e.g., entry level, mid-senior level) - and the network of professional contacts - described by a number of contacts in social network – together with a number of recommendations. We would like to prove that the increasing number of professional contacts together with the growing number of recommendations has a positive impact on the growth of the job position.
H2: The number of recommendations has a positive effect on the network of professional contacts. We would like to establish if the network of professional contacts, represented by the number of them, depends on the number of recommendations.
H3: The number of listed skills has a positive effect on the network of professional contacts. We would like to consider if the increasing number of skills in the profile is closely related with the network of professional LinkedIn contacts. We would like to examine whether the dimensions increase interdependently.
AGENDA 1.Aim of the research 2.Hypothesis 3.Data collection process 4.Collected data 5.Methods 6.Conclusion
1.The special function of Google browser. 2.The first scrape bot – collected, copying links from Google results. 3.The second scrape bot – scanned, found all defined elements from each profile.
AGENDA 1.Aim of the research 2.Hypothesis 3.Data collection process 4.Collected data 5.Methods 6.Conclusion
Data included: profiles of people working in the IT industry on the Wroclaw labour market. used publicly available information from LinkedIn categorizing each profile by gender, number of skills, number of recommendations, number of spoken languages, type of university degree (technical or not) etc.
AGENDA 1.Aim of the research 2.Hypothesis 3.Data collection process 4.Collected data 5.Methods 6.Conclusion
1.Pearson’s correlation statistics - variables measure the strength of the linear association between two quantities. 2.Spearman’s correlation - other types of variables. 3.Principal Component Analysis – numerical variables.
AGENDA 1.Aim of the research 2.Hypothesis 3.Data collection process 4.Collected data 5.Methods 6.Conclusion
People looking for a jobs in new way. Build the network of contacts Improve skills Fill up all information in a profile