Description

This phase of the research focused on posts written by actors on their Facebook pages, analyzing the lexicon chosen by each of them when they talk about migrants on their pages. More specifically we wanted to find out which terms are particularly used by the actors and their followers in reference to migrants and which are the most frequent attributes. The visualization shows the connections between the keywords: “Immigrati”, ”Migranti”, ”Profughi”, ”Clandestini”, ”Rifugiati” and the most frequent attributes they are linked with in posts. The result is a network where the words which generate more connections have the role of seeds. In this way it is possible to discover other central topics connected with the keywords; for example we can notice that in Angelino Alfano’s page the word migration is as important as the five keywords, and so it have the role of seed. The representation can be seen as a sort of neural network mirroring the imagery of migrants that actors are communicating. The seeds can be seen as Somas, connected to other words by synapses-like bridges. From another point of view these ten imagery networks can give an idea of the evocative power of the words used to define migrants. For each actor is possible to notice interesting patterns; particularly the pages of Salvini, Casapound and Lega Nord (quite linked in the in the chapter 3 network) seem to share a similar lexicon usage. Indeed their pages are the only ones in which the keyword clandestini, which connote an implicit negative significance, is a seed of the network. Particularly in Lega Nord page this word generates a huge number of links compared with the other keywords. Another interesting insight is the connection of the keyword clandestini with the word albergo or hotel, probably connected with the common thought about illegal migrants living in hotels while Italians can’t afford homes. On the Facebook pages of Lega Nord and Matteo Salvini, the most connected from the point of view of the like-network, is possible to notice another interesting common trend, they often use the world Italiani in connection with all the keywords which indicate migrants, this might be a communication strategy adopted to divide in two groups: Italians and strangers, pushing to a we-against-us vision. Those are not the only similarities between Lega Nord and Matteo Salvini, they both use terms like mantenere, invasione. This is not surprising though Matteo Salvini is actually the Lega Nord party secretary; so, it can be more interesting to notice the differences between the two communication strategies: if as already said Lega Nord’s most linked seed is the term clandestini we can notice that in the case of its secretary the main seed is “immigrati”, and is connected with strongly negative terms like “violentatori”, “terrorismo”, “sessuali” and “spaccio”. On the other side Casapound does not seem to have a preferential seed, but the first interesting element which is possible to notice is that the word “Casapound” is a seed itself, this indicate a strong self-referentiality which can be connected with tribal communication. For what concern the use of terms is interesting to point out that Casapound’s negative terms are more likely “criminali” and “delinquenti” or slogan such as “stopimmigrazione” and “Difendereroma”. Moreover in this particular case the keywords are often associated with the word “rom”. In conclusion the three digital tribes just mentioned are recognisable as the most hostile against migrants and never mention “bambini” or words related to human rights. On the contrary Matteo Renzi, UNHCR and Amnesty International show a strong positive vision about migrants. First of all their three imagery maps record the slogan “withrefugees”, and generally other words recalling human rights. Secondly two of them mention the term “war” and there are not negative terms suggesting or stimulating hate, or fear against migrants. It is also relevant the similarity between Matteo Renzi’s and UNHCR’s networks, they both have “rifugiati” as main seed and uses a large range of similar words, for example referring to the nationalities of the refugees, another shared tendency is the strong link with “migranti” which is not considered a seed due to its few links. Another interesting observation is that Amnesty and Lega Nord are the two pages that link the most “migranti” with words as “richiedenti” and “asilo”, showing a strongly different approach to the migration phenomenon. Even if there are just 9 posts on migrants on Papa Francesco’s page, the terms used such as “anziani”, “fanciulli”, “poveri” and “affollati” stimulate empathy. Alfano instead uses more juridical words remarking, for example, laws infringements and seems to give an objective, unimpassioned view.

Protocol

In this step we wanted to understand which words were more connected with our five queries (“immigrati”, “migranti”, “profughi”, “clandestini” and “rifugiati”). The tool that allowed us to understand that through a text analysis has been Voyant. In Voyant we imported all the Facebook posts per each actor, then we selected Document terms> Collocation. Typing into the box our five initial queries (migranti, immigrati, richiedenti, clandestini, profughi) we got as output a list made of two columns: the A column with the queries and the B column with the linked words to our terms. We downloaded them and created an Excel sheet. These two columns became the edges and nodes for our Gephi file. As result this dataset has been used to create the different networks of words for each actors using first Gephi and then Adobe Illustrator.

Data

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

Data source: Voyant

This dataset was downloaded by Voyant tool. Each sheet of the document belongs to one actor’s data. Each sheet is composed by three columns: the five queries (“immigrati”, “migranti”, “profughi”, “clandestini” and “rifugiati”), the attributes linked to the queries, and how many times they appear together.