Jian Liu.pdf (2.02 MB)
Download file

Natural Language Processing (NLP) in stakeholder and consumer insight research to complement interpretivist research approach

Download (2.02 MB)
posted on 03.03.2022, 01:20 by eRNZ AdmineRNZ Admin, Jian Liu, Jenny Young, Tracey Phelps, Denise Conroy, Ivy Gan

Qualitative research helps researchers to understand the ‘how’ and ‘why’ of stakeholders’ attitudes toward certain subjects although it has been challenged that the research approach is susceptible to individual expertise and small selective sample sizes (Rahman, 2016). Previous applications of Natural Language Processing (NLP) on economic and marketing domains have evident that NLP can standardise analyses, process a large volume of textual data, and identify research gaps within the domain objectively (Cheng & Edwards, 2019; Mody et al., 2021).

In Plant and Food Research, we believe that understandings of stakeholders’ attitudes will help us make informed decisions on research activities. Therefore, stakeholder interview (including Māori) data are collected regarding the new food production system, food in general, food safety, and nutrition. Focus groups (within New Zealand) will be organised to obtain consumer perceptions on the same topic. Both interpretivist and quantitative approaches will be used to obtain insights from the textual data.

This study will focus on applying NLP analyses on obtaining insights to complement those gained from the interpretivist research approach. The proposed method consists of two groups of analyses. The first group includes word co-occurrence, and thematic analysis (Callon et al., 1991; Cobo et al., 2011). The second group use trending techniques including part-of-speech tagging, text summarisation and keyword extraction. A robust workflow will be established to objectively dissect interview and focus group data. The result of this study may save interpretivist researchers time on data preparation and offer alternative angles on interpreting stakeholders’ attitudes.


Jian Liu is a data scientist in Plant & Food Research. He was trained in plant physiology and crop modelling but grow his passion in applying data science to facilitate research decision-making. His main interests are NLP applications in understanding stakeholders’ attitudes and machine learning in facilitating biophysical model development.

Dr Jenny Young is a qualitative researcher in the Stakeholder & Consumer Insight Team. Her research investigates how consumers and other stakeholders obtain meaning about food consumption, including the impact of new technologies.

Dr Denise Conroy is a Consumer Behaviourist specialising in understanding the attitudes, emotions, values and cognitions that motivate people to consume specific products, brands or experiences, or to reject these offerings. She is a skilled interpretivist researcher and methodologist, working largely with qualitative methods and data.

Tracey Phelps is a consumer scientist who contributes to qualitative investigations to understand attitudes, emotions, values and cognitions that motivate stakeholders and consumer behaviour as they relate to this proposed programme of research.

Dr Ivy Gan is a consumer scientist that specialises in conducting interpretivist qualitative research to understand consumers and their experience with food in given social-cultural contexts.


Callon, M., Courtial, J. P., & Laville, F. (1991). Co-word analysis as a tool for describing the network of interactions between basic and technological research: The case of polymer chemistry. Scientometrics, 22(1), 155–205. https://doi.org/10.1007/BF02019280

Cheng, M., & Edwards, D. (2019). A comparative automated content analysis approach on the review of the sharing economy discourse in tourism and hospitality. Current Issues in Tourism, 22(1), 35–49. https://doi.org/10.1080/13683500.2017.1361908

Cobo, M. J., López-Herrera, A. G., Herrera-Viedma, E., & Herrera, F. (2011). An approach for detecting, quantifying, and visualizing the evolution of a research field: A practical application to the Fuzzy Sets Theory field. Journal of Informetrics, 5(1), 146–166. https://doi.org/10.1016/j.joi.2010.10.002

Mody, M. A., Hanks, L., & Cheng, M. (2021). Sharing economy research in hospitality and tourism: a critical review using bibliometric analysis, content analysis and a quantitative systematic literature review. International Journal of Contemporary Hospitality Management, 33(5), 1711–1745. https://doi.org/10.1108/IJCHM-12-2020-1457

Rahman, M. S. (2016). The Advantages and Disadvantages of Using Qualitative and Quantitative Approaches and Methods in Language “Testing and Assessment” Research: A Literature Review. Journal of Education and Learning, 6(1), 102. https://doi.org/10.5539/jel.v6n1p102