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If you want to understand how behavior occurs, one of the best ways to gain information is to simply observe the behavior in its natural context. However, people might change their behavior in unexpected ways if they know they are being observed. How do researchers obtain accurate information when people tend to hide their natural behavior? As an example, imagine that your professor asks everyone in your class to raise their hand if they always wash their hands after using the restroom. Chances...

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Related Experiment Video

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Radio Frequency Identification and Motion-sensitive Video Efficiently Automate Recording of Unrewarded Choice Behavior by Bumblebees

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Research Dilemmas with Behavioral Big Data.

Galit Shmueli¹

¹Institute of Service Science, National Tsing Hua University , Hsinchu, Taiwan .

|June 21, 2017

Summary

This summary is machine-generated.

Behavioral big data (BBD) presents new challenges for researchers. This study explores the ethical and methodological dilemmas of using BBD for causal behavioral research.

Keywords:

academic research behavioral big data data acquisition data analysis ethics social science

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Area of Science:

Social Sciences
Management Science
Behavioral Economics

Background:

Behavioral big data (BBD) offers unprecedented insights into human and social behaviors.
The increasing availability of BBD necessitates new analytical approaches in research.
Traditional research paradigms face significant shifts in the context of BBD.

Purpose of the Study:

To identify and discuss the unique challenges and ethical dilemmas associated with BBD acquisition and analysis.
To explore the trade-offs researchers face when conducting causal behavioral research using BBD.
To provide a framework for navigating the complexities of BBD in scientific discovery.

Main Methods:

Literature review of existing research on BBD.
Conceptual analysis of the researcher-data-subject relationship in BBD studies.
Discussion of methodological and ethical considerations specific to BBD.

Main Results:

BBD introduces distinct methodological and technical hurdles compared to traditional data.
Ethical considerations, including privacy and consent, are amplified with BBD.
Trade-offs exist between data richness, analytical feasibility, and ethical responsibilities.

Conclusions:

Researchers must address novel methodological and ethical challenges to effectively utilize BBD.
Careful consideration of the evolving research landscape is crucial for valid causal inference.
Navigating BBD requires a balanced approach to maximize scientific discovery while upholding ethical standards.