The aim of this paper is to explore the phenomenon of urbanization and its consequences on food consumptions in Lebanon. It describes the general patterns of social dynamics and integrates them in order to identify the social processes that influence changes in food culture. An empirical application is presented to portray a system of structural processes which influence food culture changes. The analysis of food consumption and practices of eating has involved the interplay of constructing and deconstructing models to provide multiple perspectives. Results from in-depth interviews on food consumer’s behaviour have been discussed. Given the linguistic and qualitative information in our database, a recently developed pattern recognition method for categorised information is deployed. A machine learning approach based on decision tree induction will be used to identify critical success factors in consumers behaviour’s with a view to construct a model of food consumption in Lebanon. Based on qualitative answers during our interview fieldwork, a multidimensional qualitative data table for 216 interviews has been created. We have derived a tree-like form hierarchical classification model, which uncovers hidden structure of our database. Finally, from this classification a set of rules will be extracted aimed at describing the most relevant features of the database by means of explanatory statement. The ability of the system as a classifier will be tested using the classification accuracy criterion and the so-called confusion matrix.

Food consumption patterns in urban and rurale environment: interdipendence and interfaces. A case study in Lebanon

PERI, IURI;VINDIGNI G.
2008-01-01

Abstract

The aim of this paper is to explore the phenomenon of urbanization and its consequences on food consumptions in Lebanon. It describes the general patterns of social dynamics and integrates them in order to identify the social processes that influence changes in food culture. An empirical application is presented to portray a system of structural processes which influence food culture changes. The analysis of food consumption and practices of eating has involved the interplay of constructing and deconstructing models to provide multiple perspectives. Results from in-depth interviews on food consumer’s behaviour have been discussed. Given the linguistic and qualitative information in our database, a recently developed pattern recognition method for categorised information is deployed. A machine learning approach based on decision tree induction will be used to identify critical success factors in consumers behaviour’s with a view to construct a model of food consumption in Lebanon. Based on qualitative answers during our interview fieldwork, a multidimensional qualitative data table for 216 interviews has been created. We have derived a tree-like form hierarchical classification model, which uncovers hidden structure of our database. Finally, from this classification a set of rules will be extracted aimed at describing the most relevant features of the database by means of explanatory statement. The ability of the system as a classifier will be tested using the classification accuracy criterion and the so-called confusion matrix.
2008
food consumption; decision tree method; consumer’s behaviour
File in questo prodotto:
File Dimensione Formato  
2779-3163-1-PB.pdf

solo gestori archivio

Tipologia: Versione Editoriale (PDF)
Licenza: Non specificato
Dimensione 350.2 kB
Formato Adobe PDF
350.2 kB Adobe PDF   Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/26165
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact