Human judgments in hiring decisions based on online social network profiles. Bachrach, Y. In 2015 IEEE International Conference on Data Science and Advanced Analytics (DSAA), pages 1–10, October, 2015.
doi  abstract   bibtex   
Online social networks have changed the ways in which people communicate and interact, and have also impacted the business landscape. One recent trend is firms using online social networks as a part of the job hiring process. Firms scrutinize potential employees using their social network profiles, sometimes even seeking access to restricted parts of the profile, for example by demanding applicants to hand over their passwords. We explore the key criteria and profile components that affect perceptions about a user. Our results are based on datasets consisting of reports of participants who actually took part in a task of evaluating candidates. Participants volunteered their Facebook profiles and CVs, to be examined by other participants who provided a detailed report about their job-suitability. We find that in screening based on social network profiles, a profile owner's education and demographic traits correlate with their job-suitability rating. Many profile components, including textual posts, pictures, likes, and even the friend list, relate to an applicant's perceived job-suitability. Further, diverse criteria play a role in forming job-suitability perceptions, including education and skills, personality, offensive content, physical appearance, interests and age, gender, family status or other demographic traits. Thus screening based on social networking websites is very different from CV based screening, where we find that the dominant criterion is education and skills, with personality being a remote second.
@inproceedings{bachrach_human_2015,
	title = {Human judgments in hiring decisions based on online social network profiles},
	doi = {10.1109/DSAA.2015.7344842},
	abstract = {Online social networks have changed the ways in which people communicate and interact, and have also impacted the business landscape. One recent trend is firms using online social networks as a part of the job hiring process. Firms scrutinize potential employees using their social network profiles, sometimes even seeking access to restricted parts of the profile, for example by demanding applicants to hand over their passwords. We explore the key criteria and profile components that affect perceptions about a user. Our results are based on datasets consisting of reports of participants who actually took part in a task of evaluating candidates. Participants volunteered their Facebook profiles and CVs, to be examined by other participants who provided a detailed report about their job-suitability. We find that in screening based on social network profiles, a profile owner's education and demographic traits correlate with their job-suitability rating. Many profile components, including textual posts, pictures, likes, and even the friend list, relate to an applicant's perceived job-suitability. Further, diverse criteria play a role in forming job-suitability perceptions, including education and skills, personality, offensive content, physical appearance, interests and age, gender, family status or other demographic traits. Thus screening based on social networking websites is very different from CV based screening, where we find that the dominant criterion is education and skills, with personality being a remote second.},
	booktitle = {2015 {IEEE} {International} {Conference} on {Data} {Science} and {Advanced} {Analytics} ({DSAA})},
	author = {Bachrach, Y.},
	month = oct,
	year = {2015},
	keywords = {Atmospheric measurements, CVs, Data mining, Education, Facebook, Facebook profiles, Particle measurements, Predictive models, applicant perceived job-suitability, demographic traits, demography, education, human judgments, job hiring process, job-suitability perceptions, job-suitability rating, online social network profiles, profile components, profile owner education, recruitment, social networking (online), social networking Web sites},
	pages = {1--10}
}

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