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"Journalism Methodology."
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La imposibilidad de una metodología científica para el estudio de los textos del periodismo de investigación
En este articulo se niega la posibilidad de encontrar una metodologia cientifica para el analisis de lostextos de investigacion publicados en los medios de comunicacion. Para alcanzar esta conclusión hemos analizado las tecnicas existentes para el estudio de estos textos, asi como algunos ejemplos que dejan constancia de las dificultades para alcanzar un procedimiento cientifico que nos permita afirmar que sin duda nos encontramos ante un articulo de investigacion. .Como podemos afirmar si estamos o no ante un texto investigado cuando los medios tienden a presentar como investigaciones lo que solo son filtraciones realizadas por una fuente interesada?
Journal Article
Core Outcome Set-STAndards for Development: The COS-STAD recommendations
The use of core outcome sets (COS) ensures that researchers measure and report those outcomes that are most likely to be relevant to users of their research. Several hundred COS projects have been systematically identified to date, but there has been no formal quality assessment of these studies. The Core Outcome Set-STAndards for Development (COS-STAD) project aimed to identify minimum standards for the design of a COS study agreed upon by an international group, while other specific guidance exists for the final reporting of COS development studies (Core Outcome Set-STAndards for Reporting [COS-STAR]).
An international group of experienced COS developers, methodologists, journal editors, potential users of COS (clinical trialists, systematic reviewers, and clinical guideline developers), and patient representatives produced the COS-STAD recommendations to help improve the quality of COS development and support the assessment of whether a COS had been developed using a reasonable approach. An open survey of experts generated an initial list of items, which was refined by a 2-round Delphi survey involving nearly 250 participants representing key stakeholder groups. Participants assigned importance ratings for each item using a 1-9 scale. Consensus that an item should be included in the set of minimum standards was defined as at least 70% of the voting participants from each stakeholder group providing a score between 7 and 9. The Delphi survey was followed by a consensus discussion with the study management group representing multiple stakeholder groups. COS-STAD contains 11 minimum standards that are the minimum design recommendations for all COS development projects. The recommendations focus on 3 key domains: the scope, the stakeholders, and the consensus process.
The COS-STAD project has established 11 minimum standards to be followed by COS developers when planning their projects and by users when deciding whether a COS has been developed using reasonable methods.
Journal Article
Analysing How People Orient to and Spread Rumours in Social Media by Looking at Conversational Threads
As breaking news unfolds people increasingly rely on social media to stay abreast of the latest updates. The use of social media in such situations comes with the caveat that new information being released piecemeal may encourage rumours, many of which remain unverified long after their point of release. Little is known, however, about the dynamics of the life cycle of a social media rumour. In this paper we present a methodology that has enabled us to collect, identify and annotate a dataset of 330 rumour threads (4,842 tweets) associated with 9 newsworthy events. We analyse this dataset to understand how users spread, support, or deny rumours that are later proven true or false, by distinguishing two levels of status in a rumour life cycle i.e., before and after its veracity status is resolved. The identification of rumours associated with each event, as well as the tweet that resolved each rumour as true or false, was performed by journalist members of the research team who tracked the events in real time. Our study shows that rumours that are ultimately proven true tend to be resolved faster than those that turn out to be false. Whilst one can readily see users denying rumours once they have been debunked, users appear to be less capable of distinguishing true from false rumours when their veracity remains in question. In fact, we show that the prevalent tendency for users is to support every unverified rumour. We also analyse the role of different types of users, finding that highly reputable users such as news organisations endeavour to post well-grounded statements, which appear to be certain and accompanied by evidence. Nevertheless, these often prove to be unverified pieces of information that give rise to false rumours. Our study reinforces the need for developing robust machine learning techniques that can provide assistance in real time for assessing the veracity of rumours. The findings of our study provide useful insights for achieving this aim.
Journal Article
The application of artificial intelligence to journalism: an analysis of academic production
Journalism has been able to adapt quickly to technological innovation, especially in recent years. The application of algorithms and artificial intelligence (AI) to this discipline is a phenomenon that has developed rapidly in a very short time. This is therefore a research area that, in spite of its short life, deserves special interest. The objective of this review article is to map and analyze the global scientific production on this topic and to identify which countries are most focused on this issue, which areas are studied most and using which methodological approaches, how and where it is evolving, and the gaps present in this research. The review of 358 texts confirms the considerable attention from academia during the last decade, especially between 2015 and 2020, and that the USA is, by far, the country with most publications on this subject. Most of the published works are research articles carried out, above all, using qualitative methodologies. The areas that have attracted the most interest to date are data journalism, robot writing, and news verification. As is to be expected in a developing discipline, others such as the review of the role of the journalist, the personalization of content, or the incorporation of AI into teaching of journalism have not yet been sufficiently explored but surely will be in the near future.
Journal Article
The “so-called” UGC: an updated definition of user-generated content in the age of social media
PurposeWhen a concept is diffusely defined or, as this article argues, “taken for granted”, it becomes very difficult to track such concept on the literature and have some continuity as researchers build on top of previous results. This article proposes a definition for user-generated content, a term that though has lost some saliency, stands in the center or the social media phenomenon, so it should not be disregarded as an object of study.Design/methodology/approachCelebrating 20 years of the concept, this research performs a multidisciplinary literature review of 61 academic articles on UGC. Through deconstruction of the acronym UGC, it builds on the present converging, conflicting and diverging definitions and/or approaches to UGC on an attempt to consolidate a broader definition that encompasses the complexities of the phenomenon in a context of consolidation of social media, to be applied to social sciences.FindingsFollowing the present analysis, UGC is defined as any kind of text, data or action performed by online digital systems users, published and disseminated by the same user through independent channels, that incur an expressive or communicative effect either on an individual manner or combined with other contributions from the same or other sources.Originality/valueThis is the first academic effort that aims to create an in-depth dialogue over the different approaches to UGC across disciplines on the social sciences field. It should help reignite interest in the acronym, which got somehow eclipsed by the broader field of social media; whilst without UGC, social media would not exist or would not have the same social impact it does in its current form. Analogously, UGC as a topic of research has been deeply affected by the emergence and consolidation of Social Media. As this debate evolves, this contribution should be helpful as a reference to operationalize UGC on future research.Peer reviewThe peer-review history for this article is available at: https://publons.com/publon/10.1108/OIR-06-2020-0258
Journal Article
What drives and inhibits researchers to share and use open research data? A systematic literature review to analyze factors influencing open research data adoption
Both sharing and using open research data have the revolutionary potentials for forwarding scientific advancement. Although previous research gives insight into researchers' drivers and inhibitors for sharing and using open research data, both these drivers and inhibitors have not yet been integrated via a thematic analysis and a theoretical argument is lacking. This study's purpose is to systematically review the literature on individual researchers' drivers and inhibitors for sharing and using open research data. This study systematically analyzed 32 open data studies (published between 2004 and 2019 inclusively) and elicited drivers plus inhibitors for both open research data sharing and use in eleven categories total that are: 'the researcher's background', 'requirements and formal obligations', 'personal drivers and intrinsic motivations', 'facilitating conditions', 'trust', 'expected performance', 'social influence and affiliation', 'effort', 'the researcher's experience and skills', 'legislation and regulation', and 'data characteristics.' This study extensively discusses these categories, along with argues how such categories and factors are connected using a thematic analysis. Also, this study discusses several opportunities for altogether applying, extending, using, and testing theories in open research data studies. With such discussions, an overview of identified categories and factors can be further applied to examine both researchers' drivers and inhibitors in different research disciplines, such as those with low rates of data sharing and use versus disciplines with high rates of data sharing plus use. What's more, this study serves as a first vital step towards developing effective incentives for both open data sharing and use behavior.
Journal Article
Measuring Message Credibility
Despite calls to conceptualize credibility as three separate concepts—source credibility, message credibility, and media credibility—there exists no scale that exclusively measures message credibility. To address this gap, the current study constructs and validates a new scale. Results from a confirmatory factor analysis suggest that message credibility, specifically in the context of news, can be measured by asking participants to rate how well three adjectives describe content: accurate, authentic, and believable. Validity and reliability tests are reported, and contributions to credibility research are discussed.
Journal Article
Spanish technological development of artificial intelligence applied to journalism: companies and tools for documentation, production and distribution of information
Artificial intelligence (AI) has been progressively expanding over the last decade, with its transversal application to the journalistic process and the engaging of media and technology companies in developing specific tools and services. This research offers a first catalogue of Spanish technological companies and institutions that develop AI systems applicable to journalism, with services and features grouped into three phases of the journalistic process: 1. Automated gathering and documentation of information; 2. Automated production of content; and 3. Information distribution and audience relations. The research uses a methodology of in-depth interviews with 45 innovation heads of Spanish-based companies and technological centres specialised in the development of AI (N = 25), and is supported by questionnaires to systematise four study categories: company profiles, tools, journalism-specific services and future trends. The results confirm a clear evolution of Spanish technological companies within the AI sector, with services and tools available for the whole journalistic process, mainly in the information gathering and content distribution phases related to monetisation; the automated news production phase is thereby overshadowed. The offering is diversified in terms of formats -textual, audiovisual, sound- and platforms, especially web and social media. The companies consulted testify to the profitability of its implementation and note a growing interest from the media, but warn of an uneven progress that reflects “slowness”, “distrust” and “lack of knowledge” regarding the application of AI.
Journal Article
What Drives Conspiratorial Beliefs? The Role of Informational Cues and Predispositions
Why do people believe in conspiracy theories? This study breaks from much previous research and attempts to explain conspiratorial beliefs with traditional theories of opinion formation. Specifically, we focus on the reception of informational cues given a set of predispositions (political and conspiratorial). We begin with observational survey data to show that there exists a unique predisposition that drives individuals to one degree or another to believe in conspiracy theories. This predisposition appears orthogonal to partisanship and predicts political behaviors including voter participation. Then a national survey experiment is used to test the effect of an informational cue on belief in a conspiracy theory while accounting for both conspiratorial predispositions and partisanship. Our results provide an explanation for individual-level heterogeneity in the holding of conspiratorial beliefs and also indicate the conditions under which information can drive conspiratorial beliefs.
Journal Article