FAS.research
Semantic Network Analysis of Terms Related to Food & Agriculture
This is a map showing the network of terms associated with food and agriculture. To create the map, we collected two months worth of tag data from delicious.com in the Fall of 2008. The network was visualized using techniques from the field of social network analysis.
How to read the map:
Each node is a tag. The larger the node, the more the tag showed up in the dataset. Links between tags means they co-occurred as tags for a website. The thicker the line between tags, the more tags co-occurred. The distance between nodes indicates how closely related the terms are in the minds of Delicious.com users (theoretically). Groups of tags were identified using a cluster algorithm. The cluster names were chosen by the research team (for instance, "Food Safety" in the upper right hand corner).
Purpose of the map:
The map was created to help a foundation frame food policy issues for engaging industry and the public. Their program goal is to improve the environmental performance of agriculture. Our recommendation based on the map and other analysis was to frame their food policy agenda as "total security net for agriculture" taking into account farmers' need for financial security, consumers' need for a healthy and reliable food supply, and an overarching, long-term need for environmental sustainability of agriculture. In other words, we recommended that the framing lead with what is closest to farmers' and consumers' immediate personal concern.
Semantic Network Analysis of Terms Related to Food & Agriculture
This is a map showing the network of terms associated with food and agriculture. To create the map, we collected two months worth of tag data from delicious.com in the Fall of 2008. The network was visualized using techniques from the field of social network analysis.
How to read the map:
Each node is a tag. The larger the node, the more the tag showed up in the dataset. Links between tags means they co-occurred as tags for a website. The thicker the line between tags, the more tags co-occurred. The distance between nodes indicates how closely related the terms are in the minds of Delicious.com users (theoretically). Groups of tags were identified using a cluster algorithm. The cluster names were chosen by the research team (for instance, "Food Safety" in the upper right hand corner).
Purpose of the map:
The map was created to help a foundation frame food policy issues for engaging industry and the public. Their program goal is to improve the environmental performance of agriculture. Our recommendation based on the map and other analysis was to frame their food policy agenda as "total security net for agriculture" taking into account farmers' need for financial security, consumers' need for a healthy and reliable food supply, and an overarching, long-term need for environmental sustainability of agriculture. In other words, we recommended that the framing lead with what is closest to farmers' and consumers' immediate personal concern.