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Large-scale organic data generated from newspapers, social media, television, and radio require an expertise in infrastructure management, data collection, and data processing in order to gain research value from them. We have developed text analytic research portals to help social science researchers who do not have the resources necessary to collect, store, and process these large-scale data sets. Our portals allow researchers to use an intuitive point and click interface to generate variables from large, dynamic data sets using state of the art text mining and learning methods. These timely variables constructed from noisy text can then be used to advance social science research in areas such as political science, economics, public health, and psychology research.
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Validity Concerns in Research Using Organic Data
With the advent of computing technologies, researchers across social science fields are using increasingly complex methods to collect, process, and analyze data in pursuit of scientific evidence. Given the complexity of research methods used, it is important to ensure that the research findings produced by a study are robust instead of being affected significantly by uncertainties associated with the design or implementation of the study. The field of metascience—the use of scientific methodology to study science itself—has examined various aspects of this robustness requirement for research that uses conventional designed studies (e.g., surveys, laboratory experiments) to collect data. Largely missing, however, are efforts to examine the robustness of empirical research using “organic data,” namely, data that are generated without any explicit research design elements and are continuously documented by digital devices (e.g., video captured by ubiquitous sensing devices; content and social interactions extracted from social networking sites, Twitter feeds, and click streams). Given the growing popularity of using organic data in management research, it is essential to understand issues concerning the usage and processing of organic data that may affect the robustness of research findings. This commentary first provides an overview of commonly present issues that threaten the validity of inferences drawn from empirical studies using organic data. This is followed by a discussion on some key considerations and suggestions for making organic data a robust and integral part of future research endeavors in management.
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- PAR ID:
- 10547001
- Publisher / Repository:
- SAGE Publications
- Date Published:
- Journal Name:
- Journal of Management
- Volume:
- 46
- Issue:
- 7
- ISSN:
- 0149-2063
- Format(s):
- Medium: X Size: p. 1257-1274
- Size(s):
- p. 1257-1274
- Sponsoring Org:
- National Science Foundation
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