The e-ROSA project seeks to build a shared vision of a future sustainable e-infrastructure for research and education in agriculture in order to promote Open Science in this field and as such contribute to addressing related societal challenges. In order to achieve this goal, e-ROSA’s first objective is to bring together the relevant scientific communities and stakeholders and engage them in the process of coelaboration of an ambitious, practical roadmap that provides the basis for the design and implementation of such an e-infrastructure in the years to come.
This website highlights the results of a bibliometric analysis conducted at a global scale in order to identify key scientists and associated research performing organisations (e.g. public research institutes, universities, Research & Development departments of private companies) that work in the field of agricultural data sources and services. If you have any comment or feedback on the bibliometric study, please use the online form.
You can access and play with the graphs:
- Evolution of the number of publications between 2005 and 2015
- Map of most publishing countries between 2005 and 2015
- Network of country collaborations
- Network of institutional collaborations (+10 publications)
- Network of keywords relating to data - Link
Farm tourism experiences in travel reviews: A cross-comparison of three alternative methods for data analysis
This paper demonstrates three alternative approaches for mining consumer sentiment from large amounts of qualitative data found in online travel reviews. Manual content coding, corpus-based semantic analysis, and stance-shift analysis represent methods varying greatly in both process and output. For illustration purposes, they are applied in an exploratory study focused on consumers' reaction to farm stays in order to demonstrate how large volumes of qualitative data can be analyzed quantitatively in a relatively efficient and reliable way. A total of 800 narratives describing farm stay experiences and representing four national settings (Australia, Italy, UK, and USA) was collected. The results reveal that each method provides unique insights of what a farm stay vacation evokes, helpful to farm entrepreneurs wishing to develop a tourism business. The findings indicate universal values as recurrent key drivers of customer satisfaction closely relate to rural experiences. Comparing the national datasets, local differences are evident, highlighting regional variations in terms of service products and consumer preferences. From a methodological viewpoint, all three methods produce reliable results by evidence of the similarities across all three analyses. The current study shows manual content coding, corpus-based semantic method, and stance-shift analysis can capture the peculiarities of rural experiences in different national settings. (C) 2011 Elsevier Inc. All rights reserved.
- CNR_Natl_Res_Council (IT)
- Univ_N_Carolina_Charlotte (US)
- Coll_Charleston (US)
- Univ_Piemonte_Orientale_Amedeo_Avogadro (IT)
Inappropriate format for Document type, expected simple value but got array, please use list format