The final step in this first section is about how online newspapers talk about, in relation to sharing economy. So we chose the top 15 free online newspapers in world, written in English language. We used Alexa to get the top 15 once. In this protocol we tried for the first time to use the words count as text analysis method.
By Google Advanced Search we retrieved the top 10 articles (in order of relevance) for each journal per query: for each journal we used all our four definition queries, downloading 40 total articles. The final amount of articles was 600.
In order to gain the text of these articles we used Moz first, to get the URLs of the articles and then, trough Text ripper (a Digital Methods initiative) we downloaded the plain texts.
The next step was the count the top 10 words occurring in each journal: we did it with an R script. Finally, Gephi was used to visualize: in the spreadsheet, top 10 words of all journals fulfill the column “target”, while newspaper fulfill the column “source”. We achieved a regular and ordered form by using Circular layout, a plugin for Gephi.
The visualization offers two different comprehension levels. The first one is the graph in itself without interaction: in this form it shows at one glance which are the most frequent words written and by which newspapers. Edges thickness represents how many times a world is repeated by the source journal’s articles. The second one allows getting deeper insights about each specific journal or word. It activates passing over the element you want to focus on.
What we achieved by this visualization are two main considerations: first of all, we can distinguish between newspapers more voted to entertainment (the use often the same words, maybe because of their appealing on readers) and journals which use a lot of different words (they try offer a more complete point of view on sharing economy). Secondly, we noticed that the second top word used is the name of a company: Uber. This means that Uber, in December 2015, influences so much news articles topics, until becoming the second word most used by journalists.
