Iannelli, L., & Giglietto, F. (2015). Hybrid spaces of politics: the 2013 general elections in Italy, between talk shows and Twitter. Information, Communication & Society. https://doi.org/10.1080/1369118x.2015.1006658
Summary
This article investigates the hybrid entanglement of television and Twitter during Italy’s 2013 general election campaign, treating second-screen tweeting around political talk shows as a site where broadcast logic and networked publics meet. Combining a firehose collection of nearly 2.5 million hashtagged tweets across 11 talk shows and 1,076 episodes with a scene-anchored content analysis of 8,031 tweets sampled around 23 conversation peaks tied to the PD, PDL, and M5S, Iannelli and Giglietto map who participates and how. They argue that the democratic promise of second-screen practices is largely unrealized in Italy: participation is narrow, politicians and broadcasters barely engage, and tweeting mostly amplifies rather than reshapes the televised agenda.
Key Contributions
- One of the first large-scale empirical mappings of TV–Twitter hybrid practices in an Italian national election context.
- Operationalizes Carpentier, Dahlgren, and Pasquali’s distinction between participation in and through the media for second-screen Twitter, adapting Wohn and Na’s typology.
- Develops a mixed-method workflow linking firehose-level Twitter capture, peak detection, stratified sampling, and content analysis of tweets paired with their corresponding on-air scene.
- Releases an open dataset of episodes and per-minute engagement metrics on figshare for replication.
- Contributes to hybrid-media-systems theory by showing empirically how TV logic continues to structure networked political talk.
Methods
The study takes a practice-based, hybrid-media approach. Tweets containing official/dominant hashtags of 11 Italian political talk shows were collected via DiscoverText/GNIP (Aug 2012–Jun 2013), filtered to airtime windows (1,889,281 tweets), and per-minute metrics (replies, retweets, unique contributors, reach, originals) were computed following Bruns and Stieglitz. Keyword matching attributed tweets to the PD, PDL, and M5S, and the Marcus et al. peak-detection algorithm identified 530 conversation peaks, from which 23 (one per party per political period) were sampled, yielding 15,737 tweets (8,031 original). These were double-coded against the corresponding TV scene using a code-set for orientation (politics/media), form (opinion, information/streaming, request for interaction, introduction of new issues, plus emotion/irony/violence), and content (Krippendorff’s α up to .81).
Findings
- Only 187,031 unique users tweeted during airtime — a small fraction of Italy’s ~4M Twitter users — signaling narrow access to the practice.
- Just 3 of 11 talk shows displayed tweets on screen; party/leader official accounts produced only 969 tweets, and Grillo/M5S were almost absent from these conversations.
- Tweet volumes across the three parties were roughly comparable (PDL 11%, PD 10%, M5S 8%) and tracked the broadcast and political event calendar.
- 77.3% of tweets were politics-oriented; opinions/comments (79.8%) and requests for interaction (28.6%) dominated, while introducing new issues/angles/sources was residual (2.4%).
- Party profiles diverged: PDL tweets skewed to media-oriented opinions (notably around Berlusconi on Servizio Pubblico), PD tweets to politics-oriented streaming, M5S tweets to requests for interaction.
- Requests for interaction were disproportionately marked by irony (35% vs. 27% average) and violent/vulgar language (11% vs. 8%).
Connections
This paper sits within hybrid-media-systems and social-TV scholarship, offering an early empirical anchor for later work on how broadcast agendas shape platform conversation and vice versa. Its concern with the narrowness and reactive character of second-screen publics resonates with broader debates on polarization and asymmetric participation across hybrid media, though the connections to the other listed papers are largely thematic rather than direct methodological lineages.