Exploring socio-technical future scenarios in the media: the energy transition case in Italian daily newspapers

Neresini, Federico; Giardullo, Paolo; Buccio, Emanuele Di; Cammozzo, Alberto

doi:10.1007/s11135-019-00947-w

Cited by 7 publications

(7 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As postulated by Goodell and further confirmed more recently, the selection of experts in the media tends to become stable [ 1 , 25 , 31 ]. As shown elsewhere [ 12 ], although the number of actors implicated in an issue may increase, still the largest share consists of those actors who came first, thus creating a group of subjects that dominates the issue. In a sense, first-comers occupying a specific issue in media environments tend to become ‘dominant’, further limiting the access of new actors.…”

Section: Resultsmentioning

confidence: 99%

“…Exactly as postulated by Nowotny [ 39 ], those questions are defined by sources external to the scientific community, such as for instance the media agenda [ 69 ], often in close collaboration with the political agenda [ 12 ]. Here again we can observe that becoming a media star depends on being suitable for an additional media criterion, i.e.…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

When scientific experts come to be media stars: An evolutionary model tested by analysing coronavirus media coverage across Italian newspapers

et al. 2023

Self Cite

View full text Add to dashboard Cite

The article aims to understand the process through which scientific experts gain and maintain remarkable media visibility. It has been analysed a corpus of 213,875 articles published by the eight most important Italian newspapers across the Covid-19 pandemic in 2020 and 2021. By exploring this process along the different phases of the management of the emergency in Italy, it was observed that some scientific experts achieve high media visibility—and sometimes notwithstanding their low academic reputation–thus becoming a sort of “media star”. Scientific literature about the relationship between experts and media is considerable, nonetheless we found a lack of theoretical models able to analyse under which conditions experts are able to enter and to remain prominent in the media sphere. A Media Experts Evolutionary Model (MEEM) is proposed in order to analyze the main conditions under which experts can acquire visibility and how they can “survive” in media arena. We proceeded by analysing visibility of experts during SARS-CoV-2 pandemic and considering both their individual credentials previously acquired and the media environment processes of selection; MEEM acts hence as a combination of these two levels. Regarding the credentials, we accounted for i) institutional role/position, ii) previous media visibility, and iii) matches between scientific credentials and media competence. In our analysis, we collected evidence that high visibility in newspapers can be seen as evolutionary in the sense that some profiles—i.e. a particular configuration of credentials—are more adapt to specific media environments.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

When scientific experts come to be media stars: An evolutionary model tested by analysing coronavirus media coverage across Italian newspapers

et al. 2023

Self Cite

View full text Add to dashboard Cite

show abstract

“…The newspaper article harvesting process consists of three main phases: proper article collection, scraping, and de-duplication. Articles had been collected by means of a dedicated media monitoring platform developed within the research initiative “TIPS” (Technoscientific Issues in the Public Sphere, see [ 38 ]). Data acquisition relies on online news such as RSS feeds associated with specific newspaper sections obtained through a collector module.…”

Section: Methodsmentioning

confidence: 99%

“…An initial set of candidate classification algorithms were chosen (a comprehensive overview of the followed approach is provided within the—S3 section in S1 File . See also [ 38 ]): Random Forest, Naïve Bayes, Nearest Neighbor, Multinomial Naïve Bayes (MNB), Linear Stochastic Gradient Descent (LSGD), Dual Coordinate Descent method for Logistic Regression (DCD-LR), and Support Vector Machine (Least Squares Support Vector Machine–LS-SVM, and divide-and-conquer solver for kernel SVMs–DC-SVM). We tested these different machine-learning (ML) techniques in terms of F 1 -score, recall (to minimize the number of false positives), and error rate, through a five-fold hyperparameters cross-validation on a sample of 3,814 articles in Italian that were appropriately labelled.…”

Section: Methodsmentioning

confidence: 99%

Politics overwhelms science in the Covid-19 pandemic: Evidence from the whole coverage of the Italian quality newspapers

et al. 2021

Self Cite

View full text Add to dashboard Cite

The SARS-CoV-2 pandemic has emerged as one of the most dramatic health crises of recent decades. This paper treats mainstream news about the current pandemic as a valuable entry point for analyzing the relationship between science and politics in the public sphere, where the outbreak must be both understood and confronted through appropriate public-health policy decisions. In doing so, the paper aims to examine which actors, institutions, and experts dominate the SARS-CoV-2 media narratives, with particular attention to the roles of political, medical, and scientific actors and institutions within the pandemic crisis. The study relies on a large dataset consisting of all SARS-CoV-2 articles published by eight major Italian national newspapers between January 1, 2020 and June 15, 2020. These articles underwent a quantitative analysis based on a topic modeling technique. The topic modeling outputs were further analyzed by innovatively combining ad-hoc metrics and a classifier based on the stacking ensemble method (combining regularized logistic regression and linear stochastic gradient descent) for quantifying scientific salience. This enabled the identification of relevant topics and the analysis of the roles that different actors and institutions engaged in making sense of the pandemic. The results show how the health emergency has been addressed primarily in terms of political regulation and concerns and only marginally as a scientific matter. Hence, science has been overwhelmed by politics, which, in media narratives, exerts a moral as well as regulatory authority. Media narratives exclude neither scientific issues nor scientific experts; rather, they configure them as a subsidiary body of knowledge and expertise to be mobilized as an ancillary, impersonal institution useful for legitimizing the expansion of political jurisdiction over the governance of the emergency.

show abstract

“…The methodology and the TIPS system were the basis for carrying out other research activities, e.g. on the energy transition case in Italian daily newspapers [ 16 ] and to track biomedicalization in the media [ 15 ]; in the latter work, a comparative study between Italy and UK was performed and the proposed methodology relies both on topic analysis through time and the risk indicator.…”

Section: Final Remarksmentioning

confidence: 99%

Monitoring Technoscientific Issues in the News

Cammozzo

Buccio

Neresini

2020

ECML PKDD 2020 Workshops

Self Cite

View full text Add to dashboard Cite

Research at the intersection between Science and Technology Studies (STS) and Public Communication of Science and Technology (PCST) investigates the role of science in society and how it is publicly perceived. An increasing attention has been paid to coverage of Science and Technology (S&T) issues in newspapers. Because of the availability of a huge amount of digitized news contents, the variety of the issues and their dynamic nature, new opportunities are offered to carry out STS and PCST investigations. The main contribution of this paper is a methodology and a system called TIPS that was co-shaped by sociologists and computer scientists in order to monitor the coverage of S&T issues in the news and to study how they are represented. The methodology relies on machine learning, information retrieval and data analytics approaches which aim at supporting expert users, e.g. sociologists, in the investigation of their research hypotheses.

show abstract

Exploring socio-technical future scenarios in the media: the energy transition case in Italian daily newspapers

Cited by 7 publications

References 38 publications

When scientific experts come to be media stars: An evolutionary model tested by analysing coronavirus media coverage across Italian newspapers

When scientific experts come to be media stars: An evolutionary model tested by analysing coronavirus media coverage across Italian newspapers

Politics overwhelms science in the Covid-19 pandemic: Evidence from the whole coverage of the Italian quality newspapers

Monitoring Technoscientific Issues in the News

Contact Info

Product

Resources

About