Evaluating Social Media Data Quality for Employee Hiring Process Proposal

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Justification

Over the past decade, social media has become a powerful instrument to estimate the personalities of potential candidates, post job ads, and recruit talented specialists. However, the application of social media in the hiring process is a relatively new phenomenon that requires further investigation. More precisely, it remains unclear how to estimate the quality of data retrieved from the potential employees social media. The current research paper addresses this issue and tries to close the research gap using analysis of large datasets in an open-source.

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Research question, aims & objectives

The research project aims to develop a method to effectively estimate the quality of social media data.

Research question

How to evaluate social media data quality for employee hiring process?

Objectives

This research aims to analyse large datasets in an open-source and develop practices that would help to escape errors in evaluating the quality of data.

Deliverable

The deliverable of the research project is the set of recommendation on how to avoid errors while estimating social media for the hiring process. The key beneficiaries of the research are human resource managers who use social media to evaluate whether a candidate is suitable for the position.

Literature review

The scholars argue that social media are not always a reliable source of information (Landers & Schmidt, 2016). Sharaburyak et al. (2020) note that the evaluation of candidates via social media could be regarded as an invasion of privacy. From the point of view of Salvatore, Biffignandi, and Bianchi (2020), the problem of examining large datasets is that the retrieved data is not representative. Still, Bohmova and Chudan (2018) claim that social media evaluation helps to perform the MBTI personality test. Another advantage of social media in the requirement process is discussed by Sameen and Cornelius (2015). The literature review outlines the framework for the present research paper.

Research design

The project is based upon mixed research methods, i.e. quantitative and qualitative research methodologies. This research method was chosen because it enables the author to conduct a more complex and multidimensional analysis of the retrieved data. Besides, the qualitative and quantitative parts of the investigation target different aspects of the research questions. Qualitative and quantitative findings complement one and represent a stronger evidentiary basis. The author decides to employ interview with HR managers as a qualitative research method because it could help to better understand finding based on the quantitative analysis of large datasets.

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As a primary quantitative research method, the author will analyse large datasets with mathematical approaches to reveal patterns in the correlation between the content of accounts in social media and outcomes of the recruitment process. The author of the present research paper plans to collect information from the Facebook and LinkedIn accounts of people who were recruited or denied employment over the past three years. The data could be retrieved through special websites and software programs. Then, all the existing information will be divided into several sections such as the number of followers and friends, the number and the content of posts, the number of likes and photos at the page. Afterwards, the author will analyse data to figure out whether there is a correlation between behaviour in social media and recruitment outcomes. If the correlation is established, then social media data could be regarded as of good quality.

Several software apps could be used to retrieve information from social media accounts. Firstly, R programming could be used to extract data and examine it. The strong side of R is that it allows creating a scheme that shows the sociability of a person. The problem with R is that a user who is not familiar with this programming language will fail to do anything in this program. Therefore, the second option to be used is the program called Octoparse. It is a user-friendly app that converts data from the accounts in social media to Excel and other formats.

For a reason discussed above, in the present research Octoparse or its analogues will be used. After data is retrieved via the specialised software, it will be sorted into several subgroups, including the number of followers, the number of posts and reposts. The quality of social media data could not be measured without estimation of the content of posts on the personal page. Since the analysed dataset is large, it is impossible to check posts manually. At this point, R software will be helpful because it enables a user to count the frequency of the words used in tweets and posts on Facebook. The frequently used words are needed to understand what a person usually communicates via his social media. When data is gathered, it will be analysed for its quality.

The second part of the research is the conduction of qualitative research through the interview with HR managers. The manager for the interview will be chosen by simple random sampling and should correspond to two criteria. First of all, they should be employed in big businesses because the employees there are chosen more carefully. Secondly, they should use social media as an instrument for the evaluation of the candidates during the recruitment process. The author will conduct semi-structured in-depth interviews with open-ended questions to know what HR managers think about the quality of social media data and whether they have any suggestions on how to increase the quality of such data.

The questions for the interviews are to be developed later. Nonetheless, they should be aimed at revealing peculiarities of social media usage by the interviewed HR managers. For example, the fundamental question is which social media does HR manager prefer to use. Another question will reveal whether it is right to assume that the choice of social media is to be checked depends on the vacancy for which the candidate applies. In addition, it is necessary to ask the interviewees to estimate the importance of social media checking in comparison to real-life communication. Finally, another critical question that should be asked during the interview is how the quality of social media data for hiring purposes could be improved. Due to the fact that the interview is semi-structured, it is not necessary to create a long list of questions because the conversation will be based upon the responses of the chosen HR managers.

The significant advantage of this research method is that the dialogue could reveal some unexpected breakthrough since every following question is based on a respondents answer. Focus group as a data collection instruments seems to be not that effective because of the organisational issues. It is rather challenging to gather several HR managers because they have different schedules, and it would be more convenient to conduct interviews with them either in person or via Zoom.

Ethics, risks and issues

The author will need to use academic literature, information gathered during the interviews, and data retrieved from social media accounts to complete the project. One could argue that it is unethical to use datasets based on social media data because it violates a person’s privacy. Still, the applications that retrieve information from social media could only process data that is visible to all. Thus, it is impossible to gain access to the private messages of a person. Besides, suppose a person makes all information on his or her page available only for the followers. In that case, the app cannot retrieve any data.

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References

Bohmova, L., & Chudan, D. (2018). Analyzing social media data for recruiting purposes. Acta Informatica Pragensia, 7(1), 4-21.

Landers, R. N., & Schmidt, G. B. (2016). Chapter 1: Social media in employee selection and recruitment: An overview. In R. N. Landers and G. B. Schmidt (Eds.), Social Media in Employee Selection and Recruitment (pp. 3-11). Springer.

Salvatore, C., Biffignandi, S., & Bianchi, A. (2020). Social media and twitter data quality for new social indicators. Social Indicators Research, 1-30.

Sameen, S., & Cornelius, S. (2015). Social networking sites and hiring: How social media profiles influence hiring decisions. Journal of Business Studies Quarterly, 7(1), 27-35.

Sharaburyak, V., Moreira, G., Reis, M., Silva, P., & Au-Yong-Oliveira, M. (2020). The Use of Social Media in the Recruitment Process. In A. Rocha et al. (Eds.), World Conference on Information Systems and Technologies (pp. 165-174). Springer.

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IvyPanda. (2022, August 30). Evaluating Social Media Data Quality for Employee Hiring Process. https://ivypanda.com/essays/evaluating-social-media-data-quality-for-employee-hiring-process/

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"Evaluating Social Media Data Quality for Employee Hiring Process." IvyPanda, 30 Aug. 2022, ivypanda.com/essays/evaluating-social-media-data-quality-for-employee-hiring-process/.

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IvyPanda. (2022) 'Evaluating Social Media Data Quality for Employee Hiring Process'. 30 August.

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IvyPanda. 2022. "Evaluating Social Media Data Quality for Employee Hiring Process." August 30, 2022. https://ivypanda.com/essays/evaluating-social-media-data-quality-for-employee-hiring-process/.

1. IvyPanda. "Evaluating Social Media Data Quality for Employee Hiring Process." August 30, 2022. https://ivypanda.com/essays/evaluating-social-media-data-quality-for-employee-hiring-process/.


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IvyPanda. "Evaluating Social Media Data Quality for Employee Hiring Process." August 30, 2022. https://ivypanda.com/essays/evaluating-social-media-data-quality-for-employee-hiring-process/.

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