Networked partisanship and framing: A socio-semantic network analysis of the Italian debate on migration

Abstract

The huge amount of data made available by the massive usage of social media has opened up the unprecedented possibility to carry out a data-driven study of political processes. While particular attention has been paid to phenomena like elite and mass polarization during online debates and echo-chambers formation, the interplay between online partisanship and framing practices, jointly sustaining adversarial dynamics, still remains overlooked. With the present paper, we carry out a socio-semantic analysis of the debate about migration policies observed on the Italian Twittersphere, across the period May-November 2019. As regards the social analysis, our methodology allows us to extract relevant information about the political orientation of the communities of users—hereby called partisan communities—without resorting upon any external information. Remarkably, our community detection technique is sensitive enough to clearly highlight the dynamics characterizing the relationship among different political forces. As regards the semantic analysis, our networks of hashtags display a mesoscale structure organized in a core-periphery fashion, across the entire observation period. Taken altogether, our results point at different, yet overlapping, trajectories of conflict played out using migration issues as a backdrop. A first line opposes communities discussing substantively of migration to communities approaching this issue just to fuel hostility against political opponents; within the second line, a mechanism of distancing between partisan communities reflects shifting political alliances within the governmental coalition. Ultimately, our results contribute to shed light on the complexity of the Italian political context characterized by multiple poles of partisan alignment.

Bow-tie structures of twitter discursive communities

“…As highlighted in other works 21 , 26 , 29 , 30 , 32 – 34 , the presence of well-defined discursive communities is the signal that users on Online Social Networks (OSNs) are strongly polarized, i.e., they tend to tend to split into groups, which one with same opinions and political orientation.…”

“…Nevertheless, as mentioned above, verified users tend more to create new contents (i.e tweet) than to share it with her followers (retweet)). The main idea is to anchor the definition of discursive communities on verified users since they usually introduce new content and posts: as observed in many other studies 21 , 26 , 29 , 32 – 34 , 47 , verified users are, on average, much more retweeted than common users. Such a procedure obtains great performances, since it can be observed that the various discursive communities are coherent in terms of verified users belonging to the same political front; in a further analysis we are comparing this procedure with annotated datasets, better quantifying our performances 28 .…”

“…We identified the discursive communities in the retweet networks and we investigated the presence of bow-tie structures in such communities. In previous works, discursive communities were shown to mirror the political orientation of users 21 – 24 , 26 , 29 , 30 , 32 – 34 , thus the analysis of their structure is of utmost importance to infer the way opinions create and circulate.…”

“…The recent literature has extensively analysed online debate and discourse communities, focusing, from time to time, on coordinated activities in discursive communities 26 , 29 , 30 , on the semantic network associated to the various discursive communities 21 , 31 , 32 , on their exposure to disinformation campaigns 33 , 34 , and on their dynamical evolution 35 – 39 .…”

Bridging Echo Chambers? Understanding Political Partisanship through Semantic Network Analysis

“…Kwon et al (2016) studied rumors propagated by Twitter users during a time of conflict between South Korea and North Korea (what the authors refer to as Korean saber rattling ) where the authors found that discussions of rumors were a gauge of public opinion during a time of uncertainty. Radicioni et al (2021) analyzed Italian discourse on migration during a time of tension in 2019, finding five distinct partisan groups who primarily amplified the views of their members via retweeting while using mentions to interface with the opinions of other partisan groups indirectly. Extending this stream of research, we apply semantic network analysis to examine echo chambers in political discussions.…”