Fig 1.
Monopartite projection on the layer of verified users.
The network is obtained from the tweeting and retweeting activity of verified and non-verified users across the entire observation period (May-November 2019). The five final communities pivot around verified accounts of the main Italian political parties/coalitions and politicians (i.e. far-right parties as Brothers of Italy and the League, in green; center-left parties as the Democratic Party and Italy Alive, in red; the Five Stars Movement, in yellow; Go Italy in blue) as well as around accounts of media, intergovernmental and non-governmental organizations.
Table 1.
Structural characteristics of the five partisan communities.
Partisan communities show distinct structural characteristics—e.g. the number of users Nu, number of edges Ne, mean degree 〈k〉 and normalized mean degree 〈k〉N—but exhibit a rather similar communicative behavior in terms of the polarization index ρα and the self-reference indexes for retweeting (μr) and mentioning (μm).
Fig 2.
Evolution of the number of tweets and users within partisan communities across the entire observation period.
In general, the trend of tweets (on the left) is characterized by weekly oscillations where peaks, coinciding with relevant political or issue-related events (e.g. the 2019 European elections, the ‘Sea-Watch 3’ crisis, the Italian government crisis) appear. The community producing the highest number of tweets is the DX one, followed by the CSX and the M5S ones. In correspondence of July 2019, a peak characterizing the trend of the number of users (on the right) within each partisan community is clearly visible due to the ‘Sea-Watch 3’ controversy, which also induces a single community of ‘governmental supporters’.
Table 2.
Five most retweeted and mentioned verified accounts for each partisan community.
While retweets are assumed to represent a broadcast action, mentions are indicative of an interactive relationship [7]. Account names with an asterisk are intended as external to the partisan community.
Fig 3.
Evolution of the partisan communities at a monthly time scale from July to October.
In October 2019, politicians of the main center-left party (united in the red cluster in September) split into two sub-communities, the orange one being induced by the Twitter activity of the members of a new political formation (i.e. the Italy Alive party).
Table 3.
Ranking of the ten most central hashtags (according to their values of betweenness centrality) within the DX and the CSX partisan communities.
While some of the DX community hashtags as #portichiusi (‘closed ports’) denotes the clear anti-migration position of such a community, the CSX community is characterised by slogans as #portiaperti (‘open ports’) openly promoting pro-migration positions. The normalized betweenness of each hashtag, multiplied by a factor equal to 108, is reported in parentheses.
Table 4.
Ranking of the ten most central hashtags (according to their values of betweenness centrality) within the M5S and the MINGOs partisan communities.
The M5S community presents a peculiar mix of hashtags characterizing both the CSX, as #facciamorete (‘let’s act as a network’), and the DX community, as #bibbiano, along with original hashtags referring to the governmental crisis in August 2019 and the formation of a new government in September 2019, as #governoconte2 (‘government Conte 2’) and #salvinitraditore (‘Salvini traitor’); on the other hand, the MINGOs community is characterized by an evident support towards specific pro-migration topics and slogans, as hashtags like #ioaccolgo (‘I host’) prove The normalized betweenness of each hashtag, multiplied by a factor equal to 108, is reported in parentheses.
Fig 4.
K-core decomposition of the July 2019 semantic networks for the DX (top left) and the CSX (bottom left) partisan communities.
The k-core decomposition reveals the bulk of the discussion about immigration developed by these two partisan communities: while the innermost core of the DX-induced semantic network (top right figure) is composed by hashtags like #salvininonmollare (‘Salvini don’t give up’), #arrestatecarolarackete (‘arrest Carola Rackete’), #iostoconsalvini (‘I stand with Salvini’), that of the CSX-induced semantic network (bottom right figure) is composed by hashtags like #salvinidimettiti (‘Salvini resign’), #fateliscendere (‘let them get off’), #carolaracketelibera (‘free Carola Rackete’).
Fig 5.
K-core decomposition of the July 2019 semantic networks for the M5S (top left) and the MINGOs (bottom left) partisan communities.
The k-core decomposition reveals the bulk of the discussion about immigration developed by these two partisan communities: while the M5S community displays a mixed behavior towards immigration policies, as shown by the hashtags #freecarola and #bibbiano, the MINGOs innermost k-shell uncovers a strong support towards pro-migration positions, as proven by the hashtags #ioaccolgo (‘I host’), #iostoconcarola (‘I stand with Carola’) and #facciamorete (‘let us act as a network’).