Sensing, Understanding, and Shaping Social Behavior
Name
sensing_understanding_shaping.pdf
Size
1.1 MB
Format
Adobe PDF
Checksum (MD5)
06e396c9ba283dcd1a6b2cc33313dd75
Author(s)
Shmueli, Erez
Singh, Vivek
Lepri, Bruno
Pentland, Alex Paul
Date Issued
June 2014
Journal
IEEE Transactions on Computational Social Systems
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Shmueli, Erez, Vivek K. Singh, Bruno Lepri, and Alex Pentland. “Sensing, Understanding, and Shaping Social Behavior.” IEEE Transactions on Computational Social Systems 1, no. 1 (March 2014): 22–34.
Version
Author's final manuscript
Abstract
The ability to understand social systems through the aid of computational tools is central to the emerging field of computational social systems. Such understanding can answer epistemological questions on human behavior in a data-driven manner, and provide prescriptive guidelines for persuading humans to undertake certain actions in real-world social scenarios. The growing number of works in this subfield has the potential to impact multiple walks of human life including health, wellness, productivity, mobility, transportation, education, shopping, and sustenance. The contribution of this paper is twofold. First, we provide a functional survey of recent advances in sensing, understanding, and shaping human behavior, focusing on real-world behavior of users as measured using passive sensors. Second, we present a case study on how trust, which is an important building block of computational social systems, can be quantified, sensed, and applied to shape human behavior. Our findings suggest that:1) trust can be operationalized and predicted via computational methods (passive sensing and network analysis) and 2) trust has a significant impact on social persuasion; in fact, it was found to be significantly more effective than the closeness of ties in determining the amount of behavior change.
MIT Department
Massachusetts Institute of Technology. Department of Materials Science and Engineering
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/TCSS.2014.2307438
