Evidence map›Paper›PMID 39353995›Full record

ArticleScientific reports2024

Fluctuations and extreme events in the public attention on Italian legislative elections.

Andrea Auconi, Lorenzo Federico, Gianni Riotta, Guido Caldarelli

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Andrea AuconiDepartment of Molecular Sciences and Nanosystems, Ca' Foscari University of Venice, 30172, Venice, Italy.
Lorenzo FedericoLUISS Data Lab, Viale Pola 12, 00198, Rome, Italy. lfederico@luiss.it.
Gianni RiottaLUISS Data Lab, Viale Pola 12, 00198, Rome, Italy.
Guido CaldarelliDepartment of Molecular Sciences and Nanosystems, Ca' Foscari University of Venice, 30172, Venice, Italy.

Funding

European Commission CNECT/2022/5162608European Commission INEA/CEF/ICT/A2020/2394428
6 · The paper itself

Abstract

The share of social media attention to political candidates was shown to be a good predictor of election outcomes in several studies. This attention to individual candidates fluctuates due to incoming daily news and sometimes reflects long-term trends. By analyzing Twitter data in the 2013 and 2022 election campaign we observe that, on short timescales, the dynamics can be effectively characterized by a mean-reverting diffusion process on a logarithmic scale. This implies that the response to news and the exchange of opinions on Twitter lead to attention fluctuations spanning orders of magnitudes. However, these fluctuations remain centered around certain average levels of popularity, which change slowly in contrast to the rapid daily and hourly variations driven by Twitter trends and news. In particular, on our 2013 data we are able to estimate the dominant timescale of fluctuations at around three hours. Finally, by considering the extreme data points in the tail of the attention variation distribution, we could identify critical events in the electoral campaign period and extract useful information from the flow of data.

Indexed as

PoliticsSocial MediaAttentionHumansItalyPublic Opinion

Identifiers

PMID39353995
PMCPMC11445506

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.