Development of A New Conceptual Framework for Better Understanding of the Food Consumer: An Interdisciplinary Big Data Approach

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3A8IQFU7Y5" target="_blank" >RIV/00216208:11320/25:8IQFU7Y5 - isvavai.cz</a>

Result on the web

<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85189198182&doi=10.22364%2fbjmc.2024.12.1.04&partnerID=40&md5=70f60c00a0674f678d35b17081eb4fa0" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85189198182&doi=10.22364%2fbjmc.2024.12.1.04&partnerID=40&md5=70f60c00a0674f678d35b17081eb4fa0</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.22364/bjmc.2024.12.1.04" target="_blank" >10.22364/bjmc.2024.12.1.04</a>

Result language

angličtina

Original language name

Development of A New Conceptual Framework for Better Understanding of the Food Consumer: An Interdisciplinary Big Data Approach

Original language description

The author’s motivation for this study is to create a new application of big data to food. While the amount of food data increases, many important topics have been studied within separate fields or too narrow disciplines, due to the interdisciplinary nature of this type of data. The author is of the opinion that these drawbacks can be eliminated by analysing food big data using computing methods and by taking interdisciplinary approach to develop research questions. The fact that computer science has a significant role in the analysis of food consumption data is evidenced by the development of a new field of science—food computing, which is the framework of this study. Since there are still many unresolved tasks in the collection and analysis of food-related data, the use of social media and other type of big data is an important introduction. The author, by combining the methodological frameworks of cognitive, social and computer sciences, has developed several methods for using big data, based on the natural language processing and by applying the following methodologies: a) sentiment analysis of affective reactions about food and multi-sensory eating experience; b) comparative analysis of different national cuisines, by applying the topic modelling methodology; and c) bigram analysis to trace ways how food consumers talk about healthy food. Results have been summarised in a new conceptual framework by illustrating its application in practice; in the course of application, several researches, have been conducted using various computer science methodologies. As a combination of theories and methodologies of social, cognitive, and computer sciences, the new conceptual framework offers methods and a direction for studying food consumers. By using computer science methods in the analysis of big data and thus improving the understanding of food consumption, the author hopes to improve the efficiency of public health policies resulting in better public health and higher quality of life. © 2024 University of Latvia. All rights reserved.

Czech name

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Czech description

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Type

J_SC - Article in a specialist periodical, which is included in the SCOPUS database

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

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Continuities

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Publication year

2024

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Baltic Journal of Modern Computing

ISSN

2255-8942

e-ISSN

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Volume of the periodical

12

Issue of the periodical within the volume

1

Country of publishing house

US - UNITED STATES

Number of pages

32

Pages from-to

50-81

UT code for WoS article

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EID of the result in the Scopus database

2-s2.0-85189198182