Hogeschool van Amsterdam

Centre for Economic Transformation | CET

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  R.E. Loke (Rob)

Assistant Professor Data Science
Telefoon:
0621155541
Bij geen gehoor:
0621157306
Email:
r.e.loke@hva.nl
Werkadres:
Wibauthuis, Wibautstraat 3b, 1091 GH Amsterdam
Postadres:
Postbus 526,1000 AM Amsterdam
Kamernummer:
06A42
Expertise:
Online data mining | Pattern recognition | Computer graphics and visualization | Engineering
Social media:
Website:
cmihva.nl
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Rob Loke is assistant professor data science at the Centre for Market Insights of the HvA. He holds a MSc degree in computer science as well as a PhD degree, both from Delft University of Technology. He also holds a MA degree in psychology from Leiden University.

Rob was previously stationed and employed in Spain, Portugal, Italy and The Netherlands where he was consultant, researcher, lecturer and ad interim in the public and private sector. He designed, prototyped/built, tested and finetuned a large number of software systems architectures in nationally and European-Union funded projects, individually, but also jointly in teams. Rob authored/coauthored about 40 scientific papers in books, journals and conference proceedings. For his PhD-work on the visualisation of sparse datasets from the seabottom he was invited four times to IEEE/OCEANS conferences in the USA—Seattle, Providence, Honolulu and Biloxi. Based on his machine learning system for diatom recognition that he engineered as ad interim data scientist in only three weeks, four new species were identified by taxonomy experts from Royal Botanic Garden Edinburgh.

Rob applies his knowledge/expertise to projects in the CMIHvA with regard to online data mining, big data, natural language processing and machine learning.

  • Decision Support System for corporate reputation based social media listening using a cross-source sentiment analysis engine
    Loke-, R., & Pathak, S. (2023). Decision Support System for corporate reputation based social media listening using a cross-source sentiment analysis engine. In Proceedings of the 12th International Conference on Data Science, Technology and Applications DATA (Vol. 1, pp. 559-567) https://doi.org/10.5220/0012136400003541
  • Exploring Corporate Reputation based on Sentiment Polarities That Are Related to Opinions in Dutch Online Reviews
    Loke, R. E., & Vergeer, J. (2023). Exploring Corporate Reputation based on Sentiment Polarities That Are Related to Opinions in Dutch Online Reviews. In A. Cuzzocrea, O. Gusikhin, W. van der Aalst, & S. Hammoudi (Eds.), Proceedings of the 11th International Conference on Data Science, Technology and Applications (Vol. 1, pp. 423-431). Curran Associates, Inc.. https://doi.org/10.5220/0011285500003269
  • Corporate Reputation of Companies on Twitter Seen from a Sustainability Perspective
    Loke, R. E., & Zerouk, I. (2022). Corporate Reputation of Companies on Twitter Seen from a Sustainability Perspective. In J. Luís Reis, M. K. Peter, R. Cayolla, & Z. Bogdanović (Eds.), Marketing and Smart Technologies : Proceedings of ICMarkTech 2021 (Vol. 2, pp. 515-533). (Smart Innovation, Systems and Technologies; Vol. 280). Springer. https://doi.org/10.1007/978-981-16-9272-7_42
  • Design Options and Learning Analytic Pathways in Doing Agile Scrum Team Work in Education
    Loke-, R. E. (2022). Design Options and Learning Analytic Pathways in Doing Agile Scrum Team Work in Education. https://papers.iafor.org/submission61932/
  • The Role of Fake Review Detection in Managing Online Corporate Reputation
    Loke-, R. E., & Kisoen, Z. (2022). The Role of Fake Review Detection in Managing Online Corporate Reputation. 245-256.
  • Online verkoopstrategieën voor retailers
    Hagen, D., Hopman, M., van Geffen-Wenink, L., Weltevreden, J., van Merriënboer, S., Risselada, A., Loke, R., & Leyh, W. (2021). Online verkoopstrategieën voor retailers: De toegevoegde waarde van onlinestrategieën voor retailers met een fysieke winkel . Platform De Nieuwe Winkelstraat. https://www.platformdenieuwewinkelstraat.nl/dnws-onderzoek/
  • Automatic Measurement of Corporate Reputation for Retail Companies from Online Public Data on the Web
    Sitorus, M., & Loke, R. (2021). Automatic Measurement of Corporate Reputation for Retail Companies from Online Public Data on the Web. 34-35. Abstract from 10th International Conference on Data Science, Technology and Applications, Online .
  • Aspect Based Sentiment Analysis on Online Review Data to Predict Corporate Reputation
    Loke-, R. E., & Reitter, W. (2021). Aspect Based Sentiment Analysis on Online Review Data to Predict Corporate Reputation. 343-352. https://doi.org/10.5220/0010607203430352
  • A company’s corporate reputation through the eyes of employees measured with sentiment analysis of online reviews
    Loke, R. E., & Lam-Lion, R. (2021). A company’s corporate reputation through the eyes of employees measured with sentiment analysis of online reviews. 378-385. Paper presented at 10th International Conference on Data Science, Technology and Applications, Online . https://doi.org/10.5220/0010620603780385
  • Assessing corporate reputation from online employee reviews
    Loke-, R. E., & Steentjes, IJ. A. A. (Accepted/In press). Assessing corporate reputation from online employee reviews. In The 2021 International Conference on Marketing and Technologies: Proceedings by Springer (pp. 243). (Smart Innovation, Systems and Technologies; Vol. 279).
  • A new Standard for Doing Agile Scrum Team Work in Education
    Loke, R. (2020). A new Standard for Doing Agile Scrum Team Work in Education. Abstract from 8th European Conference on Education 2020. https://papers.iafor.org/submission57991/
  • Sentiment polarity classification of corporate review data with a bidirectional Long-Short Term Memory (biLSTM) neural network architecture
    Loke, R. E., & Kachaniuk, O. (2020). Sentiment polarity classification of corporate review data with a bidirectional Long-Short Term Memory (biLSTM) neural network architecture. In S. Hammoudi, C. Quix, & J. Bernardino (Eds.), Proceedings of the 9th International Conference on Data Science, Technology and Applications - Volume 1: DATA, 310-317, 2020 (pp. 310-317). (DATA 2020 - Proceedings of the 9th International Conference on Data Science, Technology and Applications). https://doi.org/10.5220/0009892303100317
  • Empowered by Innovation: Unravelling Determinants of Idea Implementation in Open Innovation Platforms
    Situmeang, F., Loke, R., de Boer, N., & de Boer, D. (2019). Empowered by Innovation: Unravelling Determinants of Idea Implementation in Open Innovation Platforms. In S. Hammoudi, C. Quix, & J. Bernardino (Eds.), DATA 2019 - Proceedings of the 8th International Conference on Data Science, Technology and Applications (Vol. 1, pp. 289-295). (DATA 2019 - Proceedings of the 8th International Conference on Data Science, Technology and Applications). SCITEPRESS Digital Library. https://doi.org/10.5220/0007948602890295
  • The Sellaphora pupula species complex (Bacillariophyceae): morphometric analysis, ultrastructure and mating data provide evidence for five new species
    Mann, D. G., McDonald, S. M., Bayer, M. M., Droop, S. J. M., Chepurnov, V. A., Loke, R. E., Ciobanu, A., & Du Buf, J. M. H. (2004). The Sellaphora pupula species complex (Bacillariophyceae): morphometric analysis, ultrastructure and mating data provide evidence for five new species. Phycologia, 43(4), 459-482. https://doi.org/10.2216/i0031-8884-43-4-459.1
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