Table 1.
M5S | CDX | CSX | |
---|---|---|---|
100% | dimaio, lega, renzi, berlusconi, m5s, pd, italia | salvini, m5s, centrodestra, pd, lega | renzi, salvini, dimaio, m5s, pd |
98% | forzaitalia, salvini | berlusconi, italia, renzi | |
96% | roma, ottoemezzo | forzaitalia | berlusconi, italia, lega |
94% | centrodestra, ricercapubblica | russia | |
92% | boschi, politica | dimaio | europa, politica, roma |
90% | fi, governo | fi, governo | |
88% | casapound | roma | |
86% | meloni | ||
84% | fakenews, lavoro, liberieuguali | casapound, politica | forzaitalia, lavoro, usa |
82% | 8800precari, gentiloni, migranti, senato, voto | governo, lombardia | centrodestra, leu, liberieuguali |
80% | bonino, campagnaelettorale, casini, leu, rosatellum | cdx, flattax, sinistra | milano, partitodemocratico, ue |
78% | avanti, iovotom5s, movimento5stelle, precari, sinistra | lavoro, ue | campagnaelettorale, fakenews, governo |
The first column shows the percentage of days each hashtag is present in the set of tweets of each community. Notice that the hashtags that are always present are those carrying the name of political parties and political leaders, while other relevant themes for the political debate are absent from (at least) some of the discursive communities. These findings suggest that the online political debate is largely focused on single personalities/political entities (as particularly evident upon inspecting the CSX hashtags) and only to a much smaller extent on themes of public interest.