Ms Natalie De Vries

Ms Natalie De Vries

Research Academic

School of Elect Engineering and Computer Science

Career Summary

Biography

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 at the University's Priority Research Centre for Bioinformatics, Biomarker Discovery and Information-Based medicine (CIBM), which is now re-branded as the group of Life and Economy Applications of Data Science (LEADS). Here she conducts interdisciplinary research with 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.

Research Expertise
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. 



Qualifications

  • Bachelor of Business, University of Newcastle
  • Bachelor of Commerce, University of Newcastle

Keywords

  • Behaviour Modeling
  • Computational Social Science
  • Consumer Behaviour
  • Data-Driven
  • Social Media Analysis

Languages

  • Dutch (Fluent)
  • French (Working)
  • English (Fluent)

Fields of Research

Code Description Percentage
010399 Numerical and Computational Mathematics not elsewhere classified 30
150502 Marketing Communications 30
150599 Marketing not elsewhere classified 40

Professional Experience

UON Appointment

Title Organisation / Department
Research Academic University of Newcastle
School of Elect Engineering and Computer Science
Australia
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Publications

For publications that are currently unpublished or in-press, details are shown in italics.


Journal article (3 outputs)

Year Citation Altmetrics Link
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) [C1]
DOI 10.1371/journal.pone.0122133
Citations Scopus - 2Web of Science - 1
Co-authors Pablo Moscato
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]
DOI 10.1057/bm.2014.18
Co-authors Jamie Carlson
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]
DOI 10.1371/journal.pone.0102768
Citations Scopus - 4Web of Science - 5
Co-authors Jamie Carlson, Pablo Moscato

Conference (5 outputs)

Year Citation Altmetrics Link
2016 de Vries NJ, Arefin AS, Mathieson L, Lucas B, Moscato P, 'Relative neighborhood graphs uncover the dynamics of social media engagement', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2016)

© Springer International Publishing AG 2016.In this paper, we examine if the Relative Neighborhood Graph (RNG) can reveal related dynamics of page-level social media metrics. A s... [more]

© Springer International Publishing AG 2016.In this paper, we examine if the Relative Neighborhood Graph (RNG) can reveal related dynamics of page-level social media metrics. A statistical analysis is also provided to illustrate the application of the method in two other datasets (the Indo-European Language dataset and the Shakespearean Era Text dataset). Using social media metrics on the world¿s ¿top check-in locations¿ Facebook pages dataset, the statistical analysis reveals coherent dynamical patterns. In the largest cluster, the categories ¿Gym¿, ¿Fitness Center¿, and ¿Sports and Recreation¿ appear closely linked together in the RNG. Taken together, our study validates our expectation that RNGs can provide a ¿parameterfree¿ mathematical formalization of proximity. Our approach gives useful insights on user behaviour in social media page-level metrics as well as other applications.

DOI 10.1007/978-3-319-49586-6_19
Co-authors Luke Mathieson, Pablo Moscato
2016 Gabardo AC, Berretta R, De Vries NJ, Moscato P, 'Where Does My Brand End? An Overlapping Community Approach', Where Does My Brand End? An Overlapping Community Approach (2016)
DOI 10.1007/978-3-319-49049-6_10
Co-authors Pablo Moscato
2014 Moslemi Naeni L, de Vries N, 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', Proceedings IEEE Fourth International Conference on Big Data and Cloud Computing (BdCloud) 2014 (2014) [E1]
DOI 10.1109/BDCloud.2014.83
Citations Scopus - 2
Co-authors Regina Berretta, Pablo Moscato
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 (2014) [E1]
DOI 10.1109/BDCloud.2014.56
Co-authors Regina Berretta, Jamie Carlson, Pablo Moscato
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) (2014) [E1]
DOI 10.1109/BDCloud.2014.23
Co-authors Pablo Moscato
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Ms Natalie De Vries

Position

Research Academic
CIBM
School of Elect Engineering and Computer Science
Faculty of Engineering and Built Environment

Contact Details

Email natalie.devries@newcastle.edu.au
Phone (02) 40420489

Office

Room L3 Pod
Building HMRI Building
Location Hunter Medical Research Institute (New Lambton Heights)

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