Methods for finding web-sites
To start finding relevant degrowth website all group members used google.
By using the links on the first relevant websites other websites regarding degrowth was found. The steps of finding relevant websites by using known websites were performed twice and by the use of navicrawler. All relevant websites, called IN-sites, were categorized and tagged according to the categories.
The Categories were simple life, de-growth, infrastructure, sustainability, economy, political and social. The synonyms were found after the team members subjective understanding. The reading of the subject have mostly been in in French and English, and hence most synonyms were found in these languages. Because there exist synonyms for each them an excel sheet were made. All the keywords for each category was run through the list of IN-sites using google scraper. The scraper found out how many time the keywords was mentioned on each web-site.
Tagging in Navicrawler:
The nationality of a site was found by using a domain-search. (The sites most difficult to find nationality on were those with “domain by proxy” address.) All sites were either categorized as academic (academia, including think-tanks), non-governmental-organization (org2), commercial-enterprise (company), sites for one individual (blog (single author)),sites with journalistic content (magazine), sites with debate and participation of several individuals (blog (several authors)) and governmental sites (gov).
After finished tagging the IN-sites were imported into the program called Gephi. Errors in the tagging were corrected and all IN-sites without connection to the rest of the network were deleted. After this phase there were a little over 200 sites.
To find the most relevant sites for a future reader all IN-sites that weighed-indegree, weighed-degree, and weighed-out-degree were found. All site with a low degree were deleted.
All the sites can be found under Nations, while the reduce list is under links. The gephi-maps have been used for analyses under intro
Method for timeline 1970-2012
Data for the timeline has been found using the IN-site's, found by from navicrawler, Wikipedia and Google search on degrowth and decroissance. The time line has been manually entered in Dipity
Method for timeline 2008-2012
Fifty relevant blogs from each has been found using google blog and harvester, blogs from each year has been placed an manually sorted. Relevant words are labeled in Gephi.
Method for making the blog network maps in History
Google Blog Search:
50 URL’s from each year from 2008 to 2012, found via google blogs The text in the search field were: De-Growth OR "Down shifting" OR "nongrowth" OR "zero growth" OR "Down scaling" OR "Right seizing" OR "decrescita" OR "decroissance" OR "Nemnövekedés" OR "decrecimiento" bike-auto-car
This were used to clean the URL’s found in google so they could be used in other programs.
Manual review of URLS for relevance:
The 250 sites are, one by one, evaluated for whether they are indeed relevant to the topic and the dateline.
API & Gephi:
Then, the 5 * 50 sites placed into Gephi via API. Then edited in Gephi Data Laboratory, irrelevant and generic labels are deleted, while others are merged into the main categories.Then they are finished Gephi graphs saved as GDF files. The overall 5 GDF files open in "new project" and is now seen as a comprehensive timeline.
The result can be found under the history page
Method for identifying and representing Degrowth participants at the actor site
All participants have to be identified manually. First step was to write all names down in a list as we came across them, step two was sorting sites with navicrawler.
DMI’s Issue Discovery Tool: After having the defined list of IN-site’s we used the Issue discovery tool from DMI to get all the most used words within our IN-site’s. Then names were identified and added to the previous name list.
Ranking the persons involved using Google Scraper. All our IN-sites were put in the URL box and all our identified persons in the search box. Google Scrape was run. Output from Google Scrape was a ranking cloud and a csv file.
Mapping the network of communication between the degrowth persons has been done by importing the csv file into Lippmanian device tool, that converted a csv file to a Gephi output. Gephi has been used to draw the network map. The map can be seen at the degrowth actors page.
Methods for making word timeline and word-clouds
The timeline for the words degrowht and decroissance were done by using www.google.com/insights
The word-clouds were made first by finding word-heavy documents or pages on the most popular degrowth-sites, within each nation. In many circumstances the site’s manifest was uses. The documents were uploaded to manyeyes for the creation of the wordclouds.