Kasper Christensen presented his PhD at April 26th.
Title of the thesis is “Detecting ideas in online communities: Utilizing machine learning and text mining for finding ideas in online communities”. The given topic for the trial lecture was ” What is the future of Big Data in Food, Beverage and Personal Products? – A critical perspective.”
In his thesis, Kasper has explored the possibilities of automatic detection of ideas from online communities.by using text mining and machine learning. He also showed that PLS regression in combination with variable selection can be used to identify the words and phrases that define an idea. He used cases from Lego and beer brewing in his work.
- Professor Knut Kvaal, Faculty of Science and Technology, Norwegian University of Life Sciences, Ås, Norway
- Dr. Argic Einar Risvik, Senior Research Scientist, Department of Sensory, Consumer and Innovation, Nofima, Ås, Norway
- Professor Tormod Næs, Senior Research Scientist, Nofima, Ås, Norway and Department of Food Science, Quality and Technology, Faculty of Life Sciences, University of Copenhagen, Copenhagen, Denmark
- Dr. Torulf Mollestad, Principal consultant, Altran, Norway, Oslo
- Dr. Hal Macfie, Visiting Professor, Universities of Reading, Nottingham, United Kingdom
- Professor Per B. Brockhoff, Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kgs. Lyngby, Denmark
- Associate Professor, Jorge M. Marchetti, Faculty of Science and Technology, Norwegian University of Life Sciences, Ås, Norway
Alessandra Biancolillo defended her PhD thesis at the University of Copenhagen on November 18th. Alessandra has been associated with Nofima’s strategic program “Multiblock Methods for prediction and interpretation”, developing methodology for analyzing and interpreting several blocks of data sequentially (so-called SO-PLS). The thesis is titled “Method development in the area of multi-block analysis focused on food analysis”. Supervisors have been Tormod Næs (Nofima), Ingrid Måge (Nofima) and Rasmus Bro (University of Copenhagen).
Alessandra did a very good job at the defense. Opponents Thomas Skov (University of Copenhagen), El Mostafa Qannari (Oniris, Nantes) and Lars Nørgaard (Roskilde University) were well prepared and contributed to an interesting and fruitful discussion.
The paper entitled “Modeling target group heterogeneity in experimental consumer studies” coauthored by J. Jansen, E. Menichelli and T. Næs was recently published in Food Quality and Preference. The paper presents the method Indvidual Differences (InD) to deal with heterogeneity in consumer groups.
Jansen, J. J., Menichelli, E., & Næs, T. (2015). Modeling target group heterogeneity in experimental consumer studies. Food Quality and Preference, 45(0), 50-57.
Consumer group heterogeneity, Consumer segmentation ,Individual Differences (InD) method, ANOVA residuals
Acceptance of a product by a consumer may result from a convoluted interplay between product attributes and individual characteristics of that consumer. Different methods that systematically combine product properties with consumer groups segmented on such characteristics have provided unprecedented insight, but ignore heterogeneity in acceptance within each consumer group. Although such knowledge is invaluable for targeted marketing, dedicated methods for consumer group heterogeneity are lacking. The authors aim to fill this gap by the Individual Differences (InD) method, which models differences between consumers within the same target group. The method scores the ‘diffusion’ within each group, shows how much each consumer contributes to that, and relates this information to product properties. Thereby also novel groups may be discovered, with attributes not covered in the consumer segmentation. The illustrative consumer study on apple juice reveals how young women differ in their price-consciousness and their acceptance on specific preparation technologies more than older women. Although men exhibit heterogeneity on the same product attributes, their mutual variability is considerably lower and they thereby form more homogeneous target groups.
Paula Varela has been coauthoring the paper “Understanding consumers’ perception of the concept and sensory experience of a functional food” to be published in LWT-Food Science and Technology. In this paper the authors used Flash Profile to generate attributes to further use in a CATA study with consumers. Sensory and non-sensory parameters related to food choice were explored. The full reference of the paper with link to ScienceDirect is
Hernández-Carrión, M., Varela, P., Hernando, I., Fiszman, S. M., & Quiles, A. Persimmon milkshakes with enhanced functionality: Understanding consumers’ perception of the concept and sensory experience of a functional food. LWT – Food Science and Technology.
Highlights from paper
Consumers perceived persimmon milkshakes as a functional beverage.
Milkshakes with pressurised persimmon were highly accepted by consumers.
Milkshakes with pasteurised persimmon were scored with the lowest overall liking.
Pressurisation allowed formulating persimmon milkshakes despite their seasonality.