Ms Natalie De Vries
Adjunct Associate Lecturer
School of Information and Physical Sciences
- Email:natalie.devries@newcastle.edu.au
- Phone:(02) 40420489
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 ExpertiseNatalie 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)
Publications
For publications that are currently unpublished or in-press, details are shown in italics.
Book (1 outputs)
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2019 |
Moscato P, de Vries NJ, Business and Consumer Analytics: New Ideas (2019) This two-volume handbook presents a collection of novel methodologies with applications and illustrative examples in the areas of data-driven computational social sciences. Throug... [more] This two-volume handbook presents a collection of novel methodologies with applications and illustrative examples in the areas of data-driven computational social sciences. Throughout this handbook, the focus is kept specifically on business and consumer-oriented applications with interesting sections ranging from clustering and network analysis, meta-analytics, memetic algorithms, machine learning, recommender systems methodologies, parallel pattern mining and data mining to specific applications in market segmentation, travel, fashion or entertainment analytics. A must-read for anyone in data-analytics, marketing, behavior modelling and computational social science, interested in the latest applications of new computer science methodologies. The chapters are contributed by leading experts in the associated fields.The chapters cover technical aspects at different levels, some of which are introductory and could be used for teaching. Some chapters aim at building a common understanding of the methodologies and recent application areas including the introduction of new theoretical results in the complexity of core problems. Business and marketing professionals may use the book to familiarize themselves with some important foundations of data science. The work is a good starting point to establish an open dialogue of communication between professionals and researchers from different fields. Together, the two volumes present a number of different new directions in Business and Customer Analytics with an emphasis in personalization of services, the development of new mathematical models and new algorithms, heuristics and metaheuristics applied to the challenging problems in the field. Sections of the book have introductory material to more specific and advanced themes in some of the chapters, allowing the volumes to be used as an advanced textbook. Clustering, Proximity Graphs, Pattern Mining, Frequent Itemset Mining, Feature Engineering, Network and Community Detection, Network-based Recommending Systems and Visualization, are some of the topics in the first volume. Techniques on Memetic Algorithms and their applications to Business Analytics and Data Science are surveyed in the second volume; applications in Team Orienteering, Competitive Facility-location, and Visualization of Products and Consumers are also discussed. The second volume also includes an introduction to Meta-Analytics, and to the application areas of Fashion and Travel Analytics. Overall, the two-volume set helps to describe some fundamentals, acts as a bridge between different disciplines, and presents important results in a rapidly moving field combining powerful optimization techniques allied to new mathematical models critical for personalization of services. Academics and professionals working in the area of business anyalytics, data science, operations research and marketing will find this handbook valuable as a reference. Students studying these fields will find this handbook useful and helpful as a secondary textbook.
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Chapter (19 outputs)
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2019 |
De Vries NJ, Moscato P, 'Datasets for Business and Consumer Analytics', Business and Consumer Analytics: New Ideas, Springer, Cham, Switzerland 965-987 (2019) [B1]
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2019 |
De Vries NJ, Olech LP, Moscato P, 'Introducing Clustering with a Focus in Marketing and Consumer Analysis', Business and Consumer Analytics: New Ideas, Springer, Cham, Switzerland 165-212 (2019) [B1]
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2019 |
Moscato P, De Vries NJ, 'Marketing Meets Data Science: Bridging the Gap', Business and Consumer Analytics: New Ideas, Springer Nature, Cham, Switzerland 3-117 (2019) [B1]
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2019 |
Mathieson L, De Vries NJ, Moscato P, 'Using Network Alignment to Identify Conserved Consumer Behaviour Modelling Constructs', Business and Consumer Analytics: New Ideas, Springer, Cham, Switzerland 513-541 (2019) [B1]
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2019 |
De Vries NJ, Moscato P, 'Consumer Behaviour and Marketing Fundamentals for Business Data Analytics', Business and Consumer Analytics: New Ideas, Springer, Cham, Switzerland 119-162 (2019) [B1]
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2019 |
Lobos CS, De Vries NJ, Inostroza-Ponta M, Berretta R, Moscato P, 'Visualizing Products and Consumers: A Gestalt Theory Inspired Method', Business and Consumer Analytics: New Ideas, Springer, Cham, Switzerland 661-689 (2019) [B1]
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2019 |
Carlson J, De Vries N, Moscato P, 'Clustering Consumers and Cluster-Specific Behavioural Models', Business and Consumer Analytics: New Ideas, Springer, Switzerland 235-267 (2019) [B1]
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2019 |
Haque MN, de Vries NJ, Moscato P, 'A Multi-objective Meta-Analytic Method for Customer Churn Prediction', Business and Consumer Analytics: New Ideas, Springer, Switzerland 781-813 (2019) [B1]
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2019 |
De Vries NJ, Moscato P, 'Datasets for Business and Consumer Analytics', Business and Consumer Analytics: New Ideas, Springer, Cham, Switzerland 965-987 (2019) [B1]
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2019 |
Mathieson L, Moscato P, 'An Introduction to Proximity Graphs', Business and Consumer Analytics: New Ideas, Springer, Cham, Switzerland 213-233 (2019) [B1]
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2019 |
De Vries NJ, Olech LP, Moscato P, 'Introducing Clustering with a Focus in Marketing and Consumer Analysis', Business and Consumer Analytics: New Ideas, Springer, Cham, Switzerland 165-212 (2019) [B1]
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2019 |
Moscato P, De Vries NJ, 'Marketing Meets Data Science: Bridging the Gap', Business and Consumer Analytics: New Ideas, Springer Nature, Cham, Switzerland 3-117 (2019) [B1]
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2019 |
Moscato P, 'Business Network Analytics: From Graphs to Supernetworks', Business and Consumer Analytics: New Ideas, Springer, Cham, Switzerland 307-400 (2019) [B1]
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2019 |
Gabardo A, Berretta R, Moscato P, 'Overlapping Communities in Co-purchasing and Social Interaction Graphs: A Memetic Approach', Business and Consumer Analytics: New Ideas, Springer, Cham, Switzerland 435-466 (2019) [B1]
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2019 |
De Vries NJ, Moscato P, 'Consumer Behaviour and Marketing Fundamentals for Business Data Analytics', Business and Consumer Analytics: New Ideas, Springer, Cham, Switzerland 119-162 (2019) [B1]
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Nova | |||||||||
2019 |
Lobos CS, De Vries NJ, Inostroza-Ponta M, Berretta R, Moscato P, 'Visualizing Products and Consumers: A Gestalt Theory Inspired Method', Business and Consumer Analytics: New Ideas, Springer, Cham, Switzerland 661-689 (2019) [B1]
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2019 |
Moscato P, Mathieson L, 'Memetic Algorithms for Business Analytics and Data Science: A Brief Survey', Business and Consumer Analytics: New Ideas, Springer, Cham, Switzerland 545-608 (2019) [B1]
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2018 |
Inostroza-Ponta M, de Vries NJ, Moscato P, 'World's best universities and personalized rankings', Handbook of Heuristics, Springer, Cham, Switzerland 1335-1371 (2018) [B1]
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2017 |
Inostroza-Ponta M, De Vries NJ, Moscato P, 'World s Best Universities and Personalized Rankings', Handbook of Heuristics, Springer International Publishing, Cham, Switzerland 1-37 (2017) [B1]
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Show 16 more chapters |
Journal article (5 outputs)
Year | Citation | Altmetrics | Link | ||||||||
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2018 |
Carlson J, Rahman M, Voola R, De Vries N, 'Customer engagement behaviours in social media: capturing innovation opportunities', Journal of Services Marketing, 32 83-94 (2018) [C1]
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2017 |
Carlson J, De Vries NJ, Rahman MM, Taylor A, 'Go with the flow: Engineering flow experiences for customer engagement value creation in branded social media environments', Journal of Brand Management, 24 334-348 (2017) [C1] A vital objective for brand managers is to engineer compelling branded social media consumption experiences for consumers that create value and innovation opportunities for brand-... [more] A vital objective for brand managers is to engineer compelling branded social media consumption experiences for consumers that create value and innovation opportunities for brand-building advantage. This multidisciplinary study, anchored in flow theory, investigates for the first time the role of flow, configured as a hierarchical model in a branded social media environment, as having a direct influence on customer engagement value (CEV) creation. Using a survey of 371 consumers, a theoretical framework was empirically tested using structural equation modelling. The results validate flow modelled as a higher-order construct, which unlocks and positively influences perceptions of CEV in branded social media environments. Curvilinear quadratic effects of flow are also investigated which provide novel insights on how optimising salient components of flow act as key customer experience mechanisms for maximising CEV creation in social media.
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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 [C1]
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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]
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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]
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Show 2 more journal articles |
Conference (5 outputs)
Year | Citation | Altmetrics | Link | ||||||||
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2017 |
Gabardo AC, Berretta R, De Vries NJ, Moscato P, 'Where Does My Brand End? An Overlapping Community Approach', Intelligent and Evolutionary Systems. The 20th Asia Pacific Symposium, IES 2016, Canberra (2017) [E1]
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2016 |
de Vries NJ, Arefin AS, Mathieson L, Lucas B, Moscato P, 'Relative neighborhood graphs uncover the dynamics of social media engagement', Advanced Data Mining and Applications. 12th International Conference, ADMA 2016, Gold Coast, QLD (2016) [E1]
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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, Sydney (2014) [E1]
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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]
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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]
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Show 2 more conferences |
Ms Natalie De Vries
Position
Adjunct Associate Lecturer
CIBM
School of Information and Physical Sciences
College of Engineering, Science and Environment
Contact Details
natalie.devries@newcastle.edu.au | |
Phone | (02) 40420489 |
Office
Room | L3.Pod |
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Building | HMRI Building. |
Location | Hunter Medical Research Institute (New Lambton Heights) , |