You Are What You Surf: Characterizing Preference and Decision-making Styles With Digital Footprints
Project's Details
Title: You Are What You Surf: Characterizing Preference and Decision-making Styles With Digital Footprints
Funded by: Ministry of Education Social Science Research Thematic Grant
Amount: S$877,800
PI: Associate Professor Liang Zhenkai, Department of Computer Science, School of Computing, NUS
Co-PI: Dr. Ng See-Kiong, Department of Computer Science, School of Computing, NUS
Collaborators: Associate Professor Rongjun Yu, Department of Management, School of Business, Hong Kong Baptist University; and Sai Li, Department of Psychology, University of Cambridge
Project duration: 03 September 2018 to 02 December 2021
Abstract
The rapid growth in the use of digital media in almost every sphere of human life gives rise to a huge amount of recorded and retrievable digital data, which are footprints of the intricate interactions between humans and their surroundings. How the analysis of such “big data” may provide meaningful inferences about people’s preferences and decision-making styles – which can then be used to create better tools, services, and public goods – underscores the importance of more research on the topic. Given that Singaporeans rank third in global social media usage, it would be a promising strategy to use insightful information derived from digital footprints to better inform government policies, consumer business and even promote social cohesion and stability. Investing in the profiling of people’s preferences and decision-making styles through digital footprints will provide timely, more accessible, cost-effective, relevant, and actionable information to business and governments – which can increase productivity, reduce costs and enhance the quality of life. In the context of a global digital age and the rising digitization of personal and public life interactions, a major challenge in Singapore is how to monitor and adapt to the dynamic decision-making styles and preferences of the new generations as influenced by global events. In particular, how do we efficiently adapt and enhance policies and tools pertinent to social, business and health domains by capitalizing on the “big data” generated by everyday digital interactions of citizens?
We propose to study how analysing big data in Singapore retrieved from social-media (Facebook/Twitter/Instagram) users can be used to predict and generate meaningful inferences about both individual and society-level decision-making styles. By using these methods we aim to lay the foundation for a Singaporean society where big data generated from widespread digital media use is used to effectively and adaptively create tools, services and public goods for the benefit of commerce and society. The main research questions are how big data in the form of Facebook “likes”, Twitter “status updates”, Instagram profile picture characteristics etc. can be used to predict decision-making styles of individuals and groups in Singapore and what other key demographic variables such as age, race, education etc. may interact with social media data to give a better prediction model in this regard.
Our research addresses policy concerns pertaining to how the digital revolution could substantively alter the inter-relationships linking people, businesses and governments in both positive and negative ways. Advances in big data and data science bring along challenges but also offer new insights, and our research will shed light on how methods of big data analytics will provide more robust evidence-based approaches to better understand Singapore society and usher long-term positive implications for Singapore’s productivity, innovation, social inclusion and integration. The use of this new wave of big data derived from various types of digital media to understand complex societal issues and inform policy making is still at its initial stages around the world, and it is best started in Singapore as early as possible. The use of big data to predict citizen characteristics such as decision-making style will keep Singapore at the forefront of a digital age society which uses efficient, reliable and evidence-based practices to improve governance, commerce and ultimately the lives of people.
Project's Team
![Lzk_1 Lzk_1](https://fass.nus.edu.sg/cfpr/wp-content/uploads/sites/17/2020/11/Lzk_1-1-150x150.jpg)
Principal Investigator
Associate Professor LIANG Zhenkai
Department of Computer Science School of Computing
National University of Singapore
![Ng See-Kiong Ng See-Kiong](https://fass.nus.edu.sg/cfpr/wp-content/uploads/sites/17/2020/11/Ng-See-Kiong-150x150.jpg)
Co-Principal Investigator
Dr NG See-Kiong
Department of Computer Science, School of Computing
National University of Singapore
![Dr.-Yu-Rongjun-ru77ro Dr.-Yu-Rongjun-ru77ro](https://fass.nus.edu.sg/cfpr/wp-content/uploads/sites/17/2020/11/Dr.-Yu-Rongjun-ru77ro-1-150x150.jpg)
Collaborator
Associate Professor Rongjun YU
Department of Management School of Business
Hong Kong Baptist University
![Sai_Li Sai_Li](https://fass.nus.edu.sg/cfpr/wp-content/uploads/sites/17/2020/11/Sai_Li-1-150x150.jpg)
Collaborator
Dr Sai LI
Department of Psychology
University of Cambridge
Postdoctoral Fellows
![dav dav](https://fass.nus.edu.sg/cfpr/wp-content/uploads/sites/17/2021/01/IMG_20201231_142933c-2-150x150.jpg)
AU Zher Wen
![serenella_tolomeo-240x300 serenella_tolomeo-240x300](https://fass.nus.edu.sg/cfpr/wp-content/uploads/sites/17/2020/12/serenella_tolomeo-240x300-1-150x150.jpg)
Serenella TOMELLO
Research Assistants
![Shuyi Wu Shuyi Wu](https://fass.nus.edu.sg/cfpr/wp-content/uploads/sites/17/2021/02/Shuyi-Wu-1-150x150.jpg)
WU Shuyi
Contact Us
Principal Investigator: Associate Professor Liang Zhenkai
Email: liangzk@comp.nus.edu.sg OR liangzk@nus.edu.sg
Collaborator: Associate Professor Rongjun Yu
Email: rongjunyu@hkbu.edu.hk
Address:
Centre for Family and Population Research
Faculty of Arts and Social Sciences
National University of Singapore
The Shaw Foundation Building
Block AS7, Level 3, 5 Arts Link
Singapore 117570