Natalie de Vries graduated with a B.Com in Economics, a B.Bus in International Business and Marketing and a first-class Honours thesis in Marketing in 2013 at the University of Newcastle. She joined the University of Newcastle as a staff member first as a research assistant in marketing and in August 2013, she started working part-time at the University's Priority Research Centre for Bioinformatics, Biomarker Discovery and Information-Based medicine (CIBM). Here she conducts interdisciplinary research with CIBM's computer science researchers in the field of computational social science as well as being in charge of the centre's outgoing communications to the general and online community and engage with private donors of the centre.
Natalie's research encompasses computational social science, marketing, online consumer behaviour, social media and related areas. Through her collaborative work with other members of the centre, Natalie conducts studies analysing large datasets through clustering, community detection, ranking, proximity graph analysis and behavioural model building amongst other methodologies.
- Bachelor of Business, University of Newcastle, 10/12/2012
- Bachelor of Commerce, University of Newcastle, 10/12/2012
- Behaviour Modeling
- Computational Social Science
- Consumer Behaviour
- Social Media Analysis
Natalie de Vries' main area of research is consumer behaviour using computational social science techniques. Combining interdisciplinary fields to investigate online consumer behaviour, social media metrics and behaviour using predictive modeling, community detection and clustering among other methods.
Fields of Research
|150599||Marketing Not Elsewhere Classified||40|
|010399||Numerical And Computational Mathematics Not Elsewhere Classified||30|
For publications that are currently unpublished or in-press, details are shown in italics.
Click on a category title below to expand the list of citations for that specific category.
Journal article (3 outputs)
|2015||de Vries NJ, Reis R, Moscato P, 'Clustering Consumers Based on Trust, Confidence and Giving Behaviour: Data-Driven Model Building for Charitable Involvement in the Australian Not-For-Profit Sector', PLOS ONE, 10 e0122133-e0122133 (2015)|
|2014||De Vries N, Carlson JL, 'Examining the drivers and brand performance implications of customer engagement with brands in the social media environment', Journal of Brand Management, 21 495-515 (2014) [C1]|
|2014||de Vries NJ, Carlson J, Moscato P, 'A Data-Driven Approach to Reverse Engineering Customer Engagement Models: Towards Functional Constructs', PLoS One, 9 (2014) [C1]|
Conference (3 outputs)
|2014||de Vries NJ, Arefin AS, Moscato P, 'Gauging Heterogeneity in Online Consumer Behaviour Data: A Proximity Graph Approach', Proceedings the Fourth IEEE International Conference on Big Data and Cloud Computing (BdCloud), Sydney, NSW (2014) [E1]|
|2014||Lucas B, Arefin AS, de Vries NJD, Berretta R, Carlson J, Moscato P, 'Engagement in Motion: Exploring Short Term Dynamics in Page-Level Social Media Metrics', Proceedings of the 2014 IEEE Fourth International Conference on Big Data and Cloud Computing, Sydney (2014) [E1]|
|2014||Naeni LM, Vries NJD, Reis R, Arefin AS, Berretta R, Moscato P, 'Identifying Communities of Trust and Confidence in the Charity and Not-for-Profit Sector: A Memetic Algorithm Approach', Big Data and Cloud Computing (BdCloud), 2014 IEEE Fourth International Conference on (2014)|
Grants and Funding
|Number of current supervisions||0|
Ms Natalie De Vries
|Work Phone||(02) 40420489|
School of Elect Engineering and Computer Science
Faculty of Engineering and Built Environment
The University of Newcastle, Australia
Hunter Medical Research Institute (New Lambton Heights)