Description

The first approach to the research had been a screening to better understand how Google renders migration. At first we needed to individuate the main discussed themes in the online debate, so we started a qualitative snowball research on a 70 sites sample, listing keywords and main issues for each of them. This step had been fundamental to hypothesize the presence of relatively isolated groups which shared the same opinion about the migration phenomenon. The interesting thing we noticed was that each group focused on different small aspects of the phenomenon to describe it in toto.

Firstly we isolated the terms which were the most used to refer to migrants. Then we ranked them with Google Trends in order to understand which one was the most popular between the researches on the browser. The top five ranked terms were: “immigrati”, “migranti”, “profughi”, “clandestini” and “rifugiati”. At this point a further and additional selection was necessary. Comparing these words on Google Trend (first visualization above) we obtained the first three preeminent terms typed on Google most frequently in 2016: “immigrati”, “migranti” and” profughi”. So we googled these three queries to obtain the most indexed websites. As shown by the second visualization the research outcome firstly indexed a huge majority of newspaper websites (73% in a sample of ten results per query) and a small amount of other fragmental sources (Wikipedia pages, organizations websites and a blog). Due to the majority of online newspapers and since newspapers are still highly important in public opinion shaping; we decided to focus on this path in order to list the most influential actors of the debate. To do this we searched for the most quoted forenames, and politicians-political party’s names. The result is displayed by the third visualization.

Protocol

Our research has started with a qualitative analysis. Firstly we googled some arbitrary queries such as "migration", "migrants", "refugees" etc. Through the indexed online newspapers websites we got a more general idea about the phenomenon and we wrote down a list of keywords. Than, using Google Trends, we see which words are more used than others. By selecting on this tool Italy/ last 12 months/ all categories/ Google Search, we obtained the first five preeminent terms typed on Google most frequently in 2016: "immigrati", "migranti", "profughi", "clandestini" and "rifugiati". At this point we googled the first three queries in order to analyse how Google answers. Basically the outcome firstly indexed a huge preeminence of newspaper websites (73%) and a small amount of other fragmental sources (geopolitical magazine, a Wikipedia page, a broadcasting station website).

In order to understand who were the main actors of our controversy, we analyzed the list of 15 online newspaper using one of the digital methods tool: Google Scraper. From this tool it has been extracted 100 article’s links for each queries (“immigrati”, “migranti” and “profughi”), for a total of 4.500 articles’ links. Then we set the tool selecting Google local version.it/ Italian language/ Italy/ in the body of the articles. Secondly all these links has been analyzed by an add-on for Google Sheet called Aylien to extract the title and the body of all the articles. At this point, we had a database of articles to explore and find out the name of the actors. The database of articles has been put in Issue Discover to understand which words were the most repeated. The output was a long list of words with the number of time the word was used. Scraping this dataset with Excel we could have seen the most repeated names in online newspapers articles: our top ten actor’s name.

Data

Timestamp: 05/12/2016 - 12/12/2016

Data source: Google Trends

Download data (Google Search)

The first dataset file is composed of three sheets, one for each query (“immigrati”, “migranti” and “profughi”). The first column shows the name of the Google results, the second one the index page and the third one the url of websites.

The second one, instead, has two sheets; the first one reports the most frequent and repeated words in the online newspaper articles. The second sheet shows the name of politics, political party and organizations: our actors.