Computational Journalism

The contemporary availability of data and the growing possibility of their processing have also inf luenced
the journalistic field. Several global news companies have embraced and enhanced forms of data use. This
article provides an overview of research and analysis on the journalistic use of data. It discusses three broad
definitions of data, computational, and automated journalism. It then debates their epistemological implications
at each stage of news production (access, processing, and editing). Finally, it outlines factors that
inf luence their future implication, focusing on education.

Data-driven journalism (DDJ) can be considered as journalism’s response to the datafication of society. To better understand the key components and development of this still young and fast evolving genre, we investigate what the field itself defines as its ‘gold-standard’: projects that were nominated for the Data Journalism Awards (DJA) from 2013 to 2016 (n= 225). Using a content analysis we examine, among other aspects, the data sources and types, visualisations, interactive features, topics, and producers. Our results demonstrate, for instance, only a few consistent developments over the years and a predominance of political pieces, of projects by newspapers and by investigative journalism organisations, of public data from official institutions as well as a glut of simple visualisations, which in sum echoes a range of general tendencies in data journalism. On the basis of our findings we evaluate DDJ’s potential for improvement with regard to journalism’s societal functions.

The advent of new technologies has always spurred questions about changes in journalism – its content, its means of production, and its consumption.  A quite recent development in the realm of digital journalism is software-generated content, i.e. automatically produced content. Companies such as Automated Insights offer services that, according to themselves “humanizes big data sets by spotting patterns, trends and key insights and describing those findings in plain English that is indistinguishable from that produced by a human writer” (Automated Insights, 2012).

This paper seeks to investigate how readers perceive software-generated content in relation to similar content written by a journalist. The study utilizes an experimental methodology where respondents were subjected to different news articles that were written by a journalist or software-generated. The respondents were then asked to answer questions about how they perceived the article; its overall quality, credibility, objectiveness etc.

The paper presents the results from a first small-scale study and they indicate that the software-generated content is perceived as, for example, descriptive, boring and objective, but not necessarily discernable from content written by journalists. The paper discusses the results of the study and its implication for journalism practice.

Una de las principales características del Periodismo de datos es la
disponibilidad de bases de datos para la investigación de temas de
interés público, lo que nos ha llevado a estudiar las relaciones entre la
nueva cultura de la transparencia y el auge de las herramientas propias
del Big Data en periodismo. Todo ello, a partir del primer enfoque de
lo que Anderson denominó “sociología del periodismo
computacional: política y políticas públicas” (Anderson 2012: 1011).
Mediante entrevistas en profundidad a cinco periodistas de datos de
Eldiario.es, Elconfidencial.com y el CEPID se ha intentado determinar de
qué manera la Ley de Transparencia y el Portal de Transparencia han
afectado a la producción periodística en el Periodismo de datos.
Como resultado, se observa que, a pesar de existir un buen
Periodismo de datos en España, la insuficiencia de la ley y el portal no
permiten que vaya más allá de ser una disciplina incipiente.

My new book -- preview here
http://www.press.uillinois.edu/books/catalog/53paw9sp9780252040511.html (google books preview)

Emerging out of changes in technology, culture, and economics, interactive journalism is a visual presentation of storytelling that allows users to interact with the reporting of information. Today it stands at a nexus: part of the traditional newsroom, yet novel enough to contribute innovative practices and thinking to the industry.

Nikki Usher's comprehensive portrait of this new journalistic identity examines the impact of digital technology on reporting, photojournalism, graphics, and the other disciplines that define interactive journalism. Her eyewitness study ranges from the interactive creation of Al Jazeera English to the celebrated data desk at the Guardian to the New York Times' Pulitzer-endowed efforts in the new field. What emerges is a richly reported profile of the people coding a revolution that may reverse the decline and fall of traditional journalism.

"The future of interactive journalism will not depend on whether it can increase page views or session times, but whether it can deepen our readers' and viewers' engagement with complex issues. Nikki Usher's Interactive Journalism is a great introduction into this emerging field of journalism where the most collaborative and interdisciplinary team players will thrive."--Wolfgang Blau, Director of Digital Strategy, Chief Digital Officer, Condé Nast International

"In Interactive Journalism, Nikki Usher skillfully answers three questions rarely addressed at the same time: how are newsrooms changing with their adoption of interactive journalism, what economic and cultural factors are driving this adoption, and why new ways of telling stories may affect the impact of journalism."--James T. Hamilton, author of All the News That's Fit to Sell: How the Market Transforms Information into News

"Nikki Usher is once again on the frontline of the newsroom, with this vivid account of the rise of maker culture in online news. Expertly cutting through the techno-jargon, Usher provides the definitive portrait of interactive journalism--from its economic benefits and professional challenges to its potential to fundamentally transform how all of us see and engage with the world."--Rod Benson, New York University

Nikki Usher is an assistant professor at the George Washington University's School of Media and Public Affairs. She is the author of Making News at the New York Times.

Pour évaluer les possibilités et limites de la génération automatique de textes dans un contexte journalistique, cette recherche itérative s’articule en deux chapitres complémentaires : un état de l’art (mise en contexte et analyse des enjeux socio-professionnels) et une approche fondée sur la linguistique computationnelle (analyse des processus de génération automatique de textes en langue naturelle et évaluation qualitative des textes générés).
Dans ce cadre, un échantillon de trois textes générés, dans le domaine économique et financier, a été soumis à un panel de 80 juges humains. Celui-ci est principalement constitué d’experts en rédaction sollicités au Royaume-Uni et aux Etats-Unis, via des organisations professionnelles. Si les juges humains ont souligné les caractères de précision et d’objectivité des textes, ils ne les ont pas estimés plaisant à lire et bien rédigés. Dans deux cas, ils n’ont pas reconnu le caractère non-humain des textes.
Les principales possibilités des systèmes de génération résident dans leur capacité à traiter rapidement de larges volumes de données dans des générations de surface calibrées en fonction du type de données et de la demande du client média. Leurs limites se situent davantage en amont de la génération de textes (aspects éthiques, éditoriaux et qualité des données).

El periodismo computacional ha irrumpido con fuerza en el intenso panorama de las innovaciones periodísticas, debido a
su gran potencial de impacto en las redacciones. Dada la reciente implantación de esta especialidad, todavía en fase experimental
en las redacciones que lo han incorporado, en este trabajo presentamos un resultado de tipo exploratorio sobre el
periodismo computacional, a la vez que lo relacionamos con variaciones bien implantadas del periodismo, como el periodismo
de datos. El trabajo se ha realizado a partir de la revisión bibliográfica y de los principales informes sobre esta materia,
así como a partir de una serie de estudios de caso. Los resultados pueden ayudar tanto a enfocar nuevas investigaciones en
este campo, como a completar el panorama de la innovación para profesionales e investigadores del sector que necesiten
disponer de una visión global del impacto que puede alcanzar el periodismo computacional.


Computational journalism has burst into the intense panorama of journalistic innovations, due to its great impact potential
on newsrooms. Given the recent implantation of this specialty, still in the experimental phase in the newsrooms that have
incorporated it, in this work we present an exploratory result on computational journalism, at the same time that we relate
it with well-established variations of journalism, such as data journalism. The work has been carried out from the review of
the main reports on this matter, as well as from a series of case studies. The results can help both to focus new research in
this field, and to complete the panorama of innovation for professionals and researchers in the sector who need to have a
global vision of the impact that computer journalism can have.

Applied research in computational journalism offers opportunities for scholars to engage with data and platforms by developing original code-based scholarship and research methods. However, scholars who write code need a place to publish about it. This paper suggests new article forms and academic publishing conventions that will allow the field of computational journalism to expand. It explores logistical details associated with sharing and publishing code, and describes reproducible research methods in use in other disciplines.

The spread of 'fake' health news is a big problem with even bigger consequences. In this study, we examine a collection of health-related news articles published by reliable and unreliable media outlets. Our analysis shows that there are structural, topical, and semantic patterns which are different in contents from reliable and unreliable media outlets. Using machine learning, we leverage these patterns and build classification models to identify the source (reliable or unreliable) of a health-related news article. Our model can predict the source of an article with an F-measure of 96%. We argue that the findings from this study will be useful for combating the health disinformation problem.

Journalism, more so than other professions, is entangled with technology in a unique
and profoundly impactful way. In this context, the technological developments of the past decades have fundamentally impacted the journalistic profession in more ways than one, opening up new possibilities and simultaneously creating a number of concerns for people working in the media industry. The changes that were brought about by the rise of automation and algorithmic technology can mainly be observed in four distinct fields of application within journalism: automated content production, data mining, news dissemination and content optimization. This article focuses on algorithmic journalism and aims to highlight the ways that algorithmic technology is being utilized within those fields, as well as pointing out the ways in which these developments have altered the way journalism is being exercised in the modern world. The study also discusses challenges related to these technologies that are yet to be addressed, as well as potential future implementations related to algorithmic journalism that has the capacity to improve on the foundation of automation in the news industry.

As quantitative forms have become more prevalent in professional journalism, it has become increasingly important to distinguish between them and examine their roles in contemporary journalistic practice. This study defines and compares three quantitative forms of journalism—computer-assisted reporting, data journalism, and computational journalism—examining the points of overlap and divergence among their journalistic values and practices. After setting the three forms against the cultural backdrop of the convergence between the open-source movement and professional journalistic norms, the study introduces a four-part typology to evaluate their epistemological and professional dimensions. In it, the three forms are classified according to their orientation toward professional expertise or networked participation, transparency or opacity, big data or targeted sampling, and a vision of an active or passive public. These three quantitative journalistic forms are ultimately characterized as related but distinct approaches to integrating the values of open-source culture and social science with those of professional journalism, each with its own flaws but also its own distinct contribution to democratically robust journalistic practice.

Does Facebook help or hurt political engagement? Some scholars argue (e.g., Resnick, 1997, 1998) that social media has taken over old media (e.g., newspaper, television) as a leading communication channel, but communication practices of human beings remain unchanged on the web. Resnick suggests the internet neither empowers citizens nor revitalizes democracy, because online communications occur within preexisting economic, legal, and social frameworks. To test this theory called normalization of the cyberspace, this study examines engagement on two verified Facebook pages run by the campaigns of two main candidates of the 2016 U.S. presidential election—Donald Trump and Hillary Clinton. The study combines two computational methods—sentiment analysis and automated topic classification—and a quantitative content analysis method to analyze 6,122 status messages, 2.8 million user comments, and 0.6 million replies. Results largely support the claims of the theory that traditional communication practices of election campaigns are transferred to the internet.

Introducción. La incorporación de elementos de la cultura de la transparencia de la era del Big Data en el periodismo ha dado como resultado lo que se conoce como periodismo de datos (PD). Objetivos. Al depender de instituciones fuera del periodismo, buscamos determinar hasta qué punto ha afectado la Ley de Transparencia española el desarrollo del PD y cómo ha respondido este sector profesional ante estas afecciones. Metodología. Con entrevistas en profundidad a periodistas de datos examinamos que elementos de la ley afectan el desarrollo del PD. A través de un análisis de contenido en medios con unidades de datos, determinamos como responde el sector ante estos elementos que le afectan. Resultados y conclusiones. El PD en España no ha alcanzado su potencial debido a la insuficiencia e incumplimiento de la ley, por lo que los periodistas han posicionado la transparencia como tema fundamental en la agenda pública.

So-called “robot” journalism represents a shift towards the automation of journalistic tasks related to news reporting, writing, curation, and even data analysis. In this paper, we consider the extension of robot journalism to the domain of social platforms and study the use of “news bots”—automated accounts that participate in news and information dissemination on social networks. Such bots present an intriguing development opportunity for news organizations and journalists. In particular, we analyze a sample of existing news bot accounts on Twitter to understand how news bots are currently being used and to examine how using automation and algorithms may change the modern media environment. Based on our analysis, we propose a typology of news bots in the form of a design and editorial decision space that can guide designers in defining the intent, utility, and functionality of future bots. The proposed design space highlights the limits of news bots (e.g., automated commentary and opinion, algorithmic transparency and accountability) and areas where news bots may enable innovation, such as niche and local news.

As new forms of multimedia, data-driven storytelling are produced by news organisations around the world, pro- gramming skills are increasingly required in newsrooms to conduct data analysis and create interactive tools and news apps. This has prompted some universities to combine journalism courses with computer skills and there is much hype about the emergence of hybrid programmer- journalists, journo-coders, journo-devs who are equally proficient writing code and copy. To date, most of the academic research into computational journalism in the newsroom has been restricted to the United States where studies suggest a model whereby the roles of journalist and programmer are merged. There is, therefore, a need to identify the extent to which this organisational model is replicated in newsrooms in other parts of the world. This paper is an exploratory study into two news organisations in the UK – the BBC and the Financial Times – to investigate the extent to which journalism skills and programming skills are being combined and the different professional identities being created. This study finds that the journalists and programmers are considered as two distinct professions and the idea of a hybrid role is rejected by the newsroom staff interviewed. A new model is identified in the newsroom whereby teams consisting of journalists, programmers and designers work closely together on interactive, data-driven projects. These findings are valuable to journalism educators in that they identify the technical skills and attitudes required by journalists working on innovative storytelling formats.

In this study, we closely look at the use of social media contents as
source or reference in the U.S. news media. Specifically, we examine about 60 thousand news articles published within the 5 years
period of 2013 − 2017 by 153 U.S. media outlets and analyze use of
social media content as source compared to other sources. We designed a social media source extraction algorithm and investigated
the extent and nature of social media source usage across different
news topics. Our results show that uses of social media content in
news almost doubled in five years. Unreliable media outlets rely on
social media more than the mainstream media. Both mainstream
and unreliable sites prefer Twitter to Facebook as a source of information.

The availability of data feeds, the demand for news on digital devices, and advances in algorithms are helping to make automated journalism more prevalent. This article extends the literature on the subject by analysing professional journalists' experiences with, and opinions about, the technology. Uniquely, the participants were drawn from a range of news organizations—including the BBC, CNN, and Thomson Reuters—and had first-hand experience working with robo-writing software provided by one of the leading technology suppliers. The results reveal journalists' judgements on the limitations of automation, including the nature of its sources and the sensitivity of its " nose for news ". Nonetheless, journalists believe that automated journalism will become more common, increasing the depth, breadth, specificity, and immediacy of information available. While some news organizations and consumers may benefit, such changes raise ethical and societal issues and, counter-intuitively perhaps, may increase the need for skills—news judgement, curiosity, and scepticism—that human journalists embody.

The use of tempting headlines (clickbait) to allure readers has become
a growing practice nowadays. The widespread use of clickbait
risks the reader’s trust in media. According to a study performed
by Facebook, 80% users “preferred headlines that helped them decide
if they wanted to read the full article before they had to click
through”. In this paper, we present a clickbait detection model
which uses distributed subword embeddings and achieves an accuracy
of 98.3%. Powered with the model, we build BaitBuster,
a solution framework (social bot+browser extension), which not
only detects clickbaits floating on the web but also provides brief
explanation behind its action. Moreover, we study 1.67 million contents
created by 153 media organizations and discover the relation
between clickbait usage and media reliability.

The use of tempting and often misleading headlines (click-bait) to allure readers has become a growing practice nowadays among the media outlets. The widespread use of click-bait risks the reader's trust in media. In this paper, we present BaitBuster, a browser extension and social bot based framework , that detects clickbaits floating on the web, provides brief explanation behind its decision, and regularly makes users aware of potential clickbaits.

In the last decades researchers have devoted a fair amount of effort to understand the news geography, i.e. a description of the general patterns for which countries are presented in which other countries' news. These efforts presume that published opinion is a good enough proxy to infer such perception; indeed, that is the case when no other evidence is available. In this work we uncover a new point of view, that of consumers, relying on a rich data set related to the comments posted by users on the largest news media organization in the Middle East region, namely Aljazeera Network. Each comment comes with a body content, a unique identifier of the user, and her IP address, which makes it possible to infer the countries from which comments are posted. All in all, our analysis encompasses over 20,000 articles and more than 2 million comments posted by 90,000 unique readers. Such a rich data set allows us confronting for the first time -to the best of our knowledge- the producer-consumer standpoints.

Storytelling with data has become a trend in journalism with the rise and growth of data-driven journalism practices encompassed in the field of computational journalism. It aims to provide quality information, which may not be made possible without high quality data. According to the ISO 9000, definition of quality is regarded as the ability to satisfy stated or implicit needs. This paper proposes a conceptual framework to assess data quality with a combination of deterministic and empirical quality indicators. If data quality is a multidimensional concept, the object is here to establish how to fit the needs of journalistic projects. Formal quality indicators are essentials when data are collected and/or automated. We can call it the technical challenge. Empirical indicators are also essentials regarding professional practices. We can call it the journalistic challenge. This part of the paper also demonstrates how and why data quality literacy is able to meet and to support journalistic requirements.

Nos ultimos anos, algumas empresas jornalisticas adotaram softwares de Natural Language Generation (NLG) para produzir conteudos automatizados em coberturas de financas, esportes, eleicoes, crimes, terremotos, fenomeno este denominado Jornalismo Automatizado (GRAEFE, 2016) ou Jornalismo Algoritmico (DORR, 2015). Partindo de um ponto de vista simetrico e nao-antropocentrico para observar os agenciamentos entre atores humanos e nao-humanos, como defendido pela Teoria Ator-Rede (LATOUR, 1992, 1994, 2000), este artigo pretende apresentar e problematizar duas das redes sociotecnicas que se articulam em torno do jornalismo automatizado. Uma primeira rede, em geral mais visivel, se efetiva a partir da mobilizacao dos atores em torno da controversia desencadeada pela publicacao dos textos escritos por bots, motivada principalmente por uma possivel substituicao de jornalistas por robos-redatores. Em geral menos evidente, uma segunda rede se revela no complexo processo de producao de noticias...

Amid the rise of computational and data-driven forms of journalism, it is important to consider the institutions, interactions, and processes that aim to help the social worlds of journalism and technology come together and collaborate around a common cause of news innovation. This paper examines one of the most prominent such efforts: the transnational grassroots organization called Hacks/Hackers. Through a two-year qualitative case study, we sought to understand just how journalists and technologists would engage through this organization: what kinds of interactions would occur, and what factors might facilitate collaboration? Drawing upon the science and technology studies concept of “trading zones,” we examine how Hacks/Hackers functions as an informal and transitory trading zone through which journalists and technologists can casually meet and coordinate. The level of engagement between the two groups, we found, depends on a set of social and structural factors, including institutional support and the leadership of key volunteers, and the depth of that engagement depends on sufficient mutual understanding among journalists and hackers. We discuss the implications of these findings for understanding the challenges and opportunities presented through the intersection of journalism and technology.

Data  played  a  major  part  in  the  journalistic  coverage  and understanding  of  the  Covid-19  pandemic.  Particularly  in Italy, one of the countries most affected by the Coronavirus, health  authorities  released  on  a  daily  basis  a  huge  amount of data in regards to the spread of the virus in the country. Based  on  interviews  with  Italian  data  journalists  who covered  the  pandemic,  this  paper  will  discuss  various  issues and flaws related to the Italian data-driven coverage of the Covid-19 pandemic. In particular, the paper aims at discussing journalists’  own  perceptions  of  official  data  reliability,  the effectiveness  of  data  in  explaining  the  contagion’s  progress in  full  and  the  most  effective  strategies  to  cover  such  data without  spreading  misguided  or  biased  information  to  the public.

This paper will review the most important aspects of computational thinking and try to emphasize the most relevant ones for the future of journalism education, by looking at scholarship in the field and assessing abilities associated with computational thinking in the context of journalistic work, from topic identification, to data collection and interpretation, to information presentation and content aggregation and distribution.

ISSN: 2167-0811 (Print) 2167-082X (Online) Journal homepage: http://www.tandfonline.com/loi/rdij20 From Mr. and Mrs. Outlier To Central Tendencies Mary Lynn Young & Alfred Hermida To cite this article: Mary Lynn Young & Alfred Hermida (2015) From Mr. and Mrs. Outlier To Central Tendencies, Digital Journalism, 3:3, 381-397, DOI: 10.1080/21670811.2014.976409 To link to this article: http://dx.doi.org/10.1080/21670811.2014.976409

Incorporating elements of the transparency’s culture of the Big Data era in journalism has become into what is known as Data Journalism (DJ). Objectives: Since it depends on institutions outside journalism, we seek to determine to what extent the Spanish Transparency Law has affected the development of DJ and how this professional sector has responded to these affections. Methodology. We examined what elements of the Law affects DJ with in-depth interviews to data journalists. Through a Content Analysis in medias with data units, we determined how this sector has replied to these elements that affects them. Results and Conclusions. DJ in Spain hasn’t reach its potential because of the insufficiency of the Law and its breach, which is why journalists have placed Transparency in the Public Agenda as a main theme.

Here's the free introduction for the book - via link below. http://www.press.uillinois.edu/books/catalog/53paw9sp9780252040511.html Blurb: Emerging out of changes in technology, culture, and economics, interactive journalism is a visual presentation of storytelling that allows users to interact with the reporting of information. Today it stands at a nexus: part of the traditional newsroom, yet novel enough to contribute innovative practices and thinking to the industry. Nikki Usher's comprehensive portrait of this new journalistic identity examines the impact of digital technology on reporting, photojournalism, graphics, and the other disciplines that define interactive journalism. Her eyewitness study ranges from the interactive creation of Al Jazeera English to the celebrated data desk at the Guardian to the New York Times' Pulitzer-endowed efforts in the new field. What emerges is a richly reported profile of the people coding a revolution that may reverse the decline...

The Panama Papers have been described as “biggest leak in the history of data journalism” with approximately 11.5 million documents provided by an anonymous source to the German newspaper Süddeutsche Zeitung. For all the things that made the Panama Papers exceptional, they also represent the latest step in a development that roughly started in 2010, when WikiLeaks cooperated with The New York Times, The Guardian and Der Spiegel to publish the Afghan war logs. In this article, I discuss how journalists have 'normalized' leaking similar to how other potentially disruptive practices like blogging or user-generated content have been integrated into journalistic working routines and ethics. I suggest that normalizing leaking supports a more collaborative and computational form of journalism.