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Big Data Visualizations in Organizational Science

Authors :
Abish Malik
Jieqiong Zhao
Vincent Ng
Junghoon Chae
Louis Tay
Jiawei Zhang
Yiqing Ding
David S. Ebert
Margaret L. Kern
Source :
Organizational Research Methods. 21:660-688
Publication Year :
2017
Publisher :
SAGE Publications, 2017.

Abstract

Visualizations in organizational research have primarily been used in the context of traditional survey data, where individual data points (e.g., responses) can typically be plotted, and qualitative (e.g., language data) and quantitative (e.g., frequency data) information are not typically combined. Moreover, visualizations are typically used in a hypothetico-deductive fashion to showcase significant hypothesized results. With the advent of big data, which has been characterized as being particularly high in volume, variety, and velocity of collection, visualizations need to more explicitly and formally consider the issues of (a) identification (isolating or highlighting relevant data pertaining to the phenomena of interest), (b) integration (combining different modes of data to reveal insights about a phenomenon of interest), (c) immediacy (examining real-time data in a time-sensitive manner), and (d) interactivity (inductively uncovering and identifying new patterns). We discuss basic ideas for addressing these issues and provide illustrative examples of visualizations that incorporate and highlight ways of addressing these issues. Examples in our article include visualizing multiple performance criteria for police officers, publication network of organizational researchers, and social media language of Fortune 500 companies.

Details

ISSN :
15527425 and 10944281
Volume :
21
Database :
OpenAIRE
Journal :
Organizational Research Methods
Accession number :
edsair.doi...........c109dd7dc8ea47d842277f95e644f68a
Full Text :
https://doi.org/10.1177/1094428117720014