IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Social Science Data Analysis: The Ethical Imperative

Social Science Data Analysis: The Ethical Imperative
View Sample PDF
Author(s): Anthony Scime (State University of New York, USA) and Gregg R. Murray (Texas Tech University, USA)
Copyright: 2013
Pages: 17
Source title: Ethical Data Mining Applications for Socio-Economic Development
Source Author(s)/Editor(s): Hakikur Rahman (University of Minho, Portugal) and Isabel Ramos (University of Minho, Portugal)
DOI: 10.4018/978-1-4666-4078-8.ch007

Purchase

View Social Science Data Analysis: The Ethical Imperative on the publisher's website for pricing and purchasing information.

Abstract

Social scientists address some of the most pressing issues of society such as health and wellness, government processes and citizen reactions, individual and collective knowledge, working conditions and socio-economic processes, and societal peace and violence. In an effort to understand these and many other consequential issues, social scientists invest substantial resources to collect large quantities of data, much of which are not fully explored. This chapter proffers the argument that privacy protection and responsible use are not the only ethical considerations related to data mining social data. Given (1) the substantial resources allocated and (2) the leverage these “big data” give on such weighty issues, this chapter suggests social scientists are ethically obligated to conduct comprehensive analysis of their data. Data mining techniques provide pertinent tools that are valuable for identifying attributes in large data sets that may be useful for addressing important issues in the social sciences. By using these comprehensive analytical processes, a researcher may discover a set of attributes that is useful for making behavioral predictions, validating social science theories, and creating rules for understanding behavior in social domains. Taken together, these attributes and values often present previously unknown knowledge that may have important applied and theoretical consequences for a domain, social scientific or otherwise. This chapter concludes with examples of important social problems studied using various data mining methodologies including ethical concerns.

Related Content

Fundamentals of Opinion Mining
Ashish Seth, Kirti Seth. © 2019. 19 pages.
View Details View Details PDF Full Text View Sample PDF
Feature Based Opinion Mining
Mridula Batra, Vishaw Jyoti. © 2019. 20 pages.
View Details View Details PDF Full Text View Sample PDF
Deep Learning for Opinion Mining
Iman Raeesi Vanani, Morteza Amirhosseini. © 2019. 26 pages.
View Details View Details PDF Full Text View Sample PDF
Opinion Mining: Using Machine Learning Techniques
Vijender Kumar Solanki, Nguyen Ha Huy Cuong, Zonghyu (Joan) Lu. © 2019. 17 pages.
View Details View Details PDF Full Text View Sample PDF
Ontology-Based Opinion Mining
Chitra Jalota, Rashmi Agrawal. © 2019. 20 pages.
View Details View Details PDF Full Text View Sample PDF
Ontologies, Repository, and Information Mining in Component-Based Software Engineering Environment
Rajesh Kumar Bawa, Iqbaldeep Kaur. © 2019. 19 pages.
View Details View Details PDF Full Text View Sample PDF
Ontology-Based Opinion Mining for Online Product Reviews
Farheen Siddiqui, Parul Agarwal. © 2019. 26 pages.
View Details View Details PDF Full Text View Sample PDF
Body Bottom