Exploring Consumer Attitudes Towards Social Media Data Minimization
Open Access
- Author:
- Burke, Michael
- Area of Honors:
- Management Information Systems
- Degree:
- Bachelor of Science
- Document Type:
- Thesis
- Thesis Supervisors:
- Robert Alexander Novack, Thesis Supervisor
John C Spychalski, Honors Advisor - Keywords:
- data minimization
social media
consumer trust
data privacy - Abstract:
- Social media businesses, among many others, take an aggressive approach to collecting personal data from their users. This data fuels machine learning and other advanced analytic algorithms that improve the user experience and allow advertisers to target consumers. Collecting and storing personal data creates inherent privacy and data breach risks. To combat this issue and protect consumers, data minimization principles have been a hot topic in legislative, academic, and corporate discussion. This research thesis investigates consumer attitudes towards social media data minimization. Using Amazon Mechanical Turk, consumers participated in an experimental survey that presented social media data policies with and without data minimization techniques. Consumer attitudes were measured using a Likert Scale for responsibility, risk, comfortability, trust, and preference in the social media companies. The results of the survey determined that data minimization in a social media data policy increased positive sentiment for each of the tested categories. Additionally, researchers observed that a lower proportion of older participants trusted either social media company compared to younger participants. Overall, the study underlines that consumers respond positively to data minimization. Companies need to understand data minimization as a value to the consumer and a possible competitive advantage in the future.