TY - GEN
T1 - Modeling Organizational Culture with Workplace Experiences Shared on Glassdoor
AU - Das Swain, Vedant
AU - Saha, Koustuv
AU - Reddy, Manikanta D.
AU - Rajvanshy, Hemang
AU - Abowd, Gregory D.
AU - De Choudhury, Munmun
N1 - Funding Information:
This research is supported in part by the Office of the Director of National Intelligence (ODNI), Intelligence Advanced Research Projects Activity (IARPA), via IARPA Contract No. 2017-17042800007. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies, either expressed or implied, of ODNI, IARPA, or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for governmental purposes notwithstanding any copyright annotation therein. We thank the Tesserae team for their contributions in realizing the goals of this project, and thank Shrija Mishra, Daejin Choi, Sindhu Ernala, Sandeep Soni, Asra Yousuf, and Dong Whi Yoo for their help and feedback.
Publisher Copyright:
© 2020 ACM.
PY - 2020/4/21
Y1 - 2020/4/21
N2 - Organizational culture (OC) encompasses the underlying beliefs, values, and practices that are unique to an organization. However, OC is inherently subjective and a coarse construct, and therefore challenging to quantify. Alternatively, self-initiated workplace reviews on online platforms like Glassdoor provide the opportunity to leverage the richness of language to understand OC. In as much, first, we use multiple job descriptors to operationalize OC as a word vector representation. We validate this construct with language used in 650k different Glassdoor reviews. Next, we propose a methodology to apply our construct on Glassdoor reviews to quantify the OC of employees by sector. We validate our measure of OC on a dataset of 341 employees by providing empirical evidence that it helps explain job performance. We discuss the implications of our work in guiding tailored interventions and designing tools for improving employee functioning.
AB - Organizational culture (OC) encompasses the underlying beliefs, values, and practices that are unique to an organization. However, OC is inherently subjective and a coarse construct, and therefore challenging to quantify. Alternatively, self-initiated workplace reviews on online platforms like Glassdoor provide the opportunity to leverage the richness of language to understand OC. In as much, first, we use multiple job descriptors to operationalize OC as a word vector representation. We validate this construct with language used in 650k different Glassdoor reviews. Next, we propose a methodology to apply our construct on Glassdoor reviews to quantify the OC of employees by sector. We validate our measure of OC on a dataset of 341 employees by providing empirical evidence that it helps explain job performance. We discuss the implications of our work in guiding tailored interventions and designing tools for improving employee functioning.
KW - glassdoor
KW - organizational culture
KW - social media
KW - wordvector
UR - http://www.scopus.com/inward/record.url?scp=85091272533&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85091272533&partnerID=8YFLogxK
U2 - 10.1145/3313831.3376793
DO - 10.1145/3313831.3376793
M3 - Conference contribution
AN - SCOPUS:85091272533
T3 - Conference on Human Factors in Computing Systems - Proceedings
BT - CHI 2020 - Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems
PB - Association for Computing Machinery
T2 - 2020 ACM CHI Conference on Human Factors in Computing Systems, CHI 2020
Y2 - 25 April 2020 through 30 April 2020
ER -