Jobs-to-Be-Done and Journalism Innovation: Making News More Responsive to Community Needs

Developing successful innovations in journalism, whether to improve the quality and reach of news or to strengthen business models, remains an elusive problem. The challenge is an existential concern for many news enterprises, particularly for smaller news outlets with limited resources. By and large, media innovation has been driven by never-ending pivots in the search for a killer solution, rather than by long-term strategic thinking. This article argues for a fresh approach to innovation built around the "jobs to be done" (JTBD) hypothesis developed by the late Clayton Christensen and typically used in business studies of innovation. However, attempts to bring the JTBD framework into the news industry have never taken hold, while scholars, too, have largely overlooked the framework in their study of journalism innovation. We argue that the JTBD approach can foster local journalism that is more responsive and relevant to the needs of local communities. It reorients journalism by focusing on identifying and addressing the underserved needs of communities, as understood by the communities themselves. It suggests that a bottom-up approach to appreciating the "jobs" that community members want done offers a model that supports both the editorial and business imperatives of local news organizations

Journalism in an Era of Big Data: Cases, Concepts, and Critiques

Introduction to a special issue of Digital Journalism, Volume 3, Issue 3: "Journalism in an Era of Big Data: Cases, Concepts, and Critiques."“Journalism in an era of big data” is thus a way of seeing journalism as interpolated through the conceptual and methodological approaches of computation and quantification. It is about both the ideation and implementation of computational and mathematical mindsets and skill sets in newswork—as well as the necessary deconstruction and critique of such approaches. Taking such a wide-angle view of this phenomenon, including both practice and philosophy within this conversation, means attending to the social/cultural dynamics of computation and quantification—such as the grassroots groups that are seeking to bring pro-social “hacking” into journalism (Lewis and Usher 2013, 2014)—as well as the material/technological characteristics of these developments. It means recognizing that algorithms and related computational tools and techniques “are neither entirely material, nor are they entirely human—they are hybrid, composed of both human intentionality and material obduracy” (Anderson 2013, 1016). As such, we need a set of perspectives that highlight the distinct and interrelated roles of social actors and technological actants at this emerging intersection of journalism (Lewis and Westlund 2014a). To trace the broad outline of journalism in an era of big data, we need (1) empirical cases that describe and explain such developments, whether at the micro (local) or macro (institutional) levels of analysis; (2) conceptual frameworks for organizing, interpreting, and ultimately theorizing about such developments; and (3) critical perspectives that call into question taken-for-granted norms and assumptions. This special issue takes up this three-part emphasis on cases, concepts, and critiques

Competition, Change, and Coordination and Collaboration: Tracing news executives’ perceptions about participation in media innovation

Introduction Research Questions and Methods Results Discussion and conclusion Additional information Footnotes References Full Article Figures & data References Citations Metrics Licensing Reprints & Permissions View PDF View EPUB ABSTRACT Technological disruptions and increasing competition in the digital mediascape have fundamentally altered the market conditions for news media companies, raising corresponding concerns about the future of journalism. News media firms can adapt their business models by more purposefully focusing on media innovation, or the development and implementation of new processes, products or services. Specifically, this article focuses on innovation-centric coordination and collaboration—namely, coordination of knowledge and innovation activities among social actors in news media organizations. In doing so, this article builds on the knowledge-based view (KBV) of the firm and its core argument that coordination of knowledge is essential for organizational innovation. It presents findings from a series of cross-sectional surveys with newspaper executives carried out bi-annually from 2011 to 2017, examining executives’ perceptions of collaborative potential for digital media innovation at the intersection of editorial, business, and information technology (IT) departments. The findings suggest that there has been a significant increase in perceived collaboration more recently, and that the IT department is perceived to have become more important to innovation over time.This work was supported by Volda University College: [Grant Number Professor II research support to Oscar Westlund].publishedVersio

Actors, actants, audiences, and activities in cross-media news work: A matrix and a research agenda

Citation information: Lewis, S. C., & Westlund, O. (2014). Actors, actants, audiences, and activities in cross-media news work: A matrix and a research agenda. Digital Journalism. doi:10.1080/21670811.2014.927986In contemporary journalism, there is a need for better conceptualizing the changing nature of human actors, nonhuman technological actants, and diverse representations of audiences—and the activities of news production, distribution, and interpretation through which actors, actants, and audiences are inter-related. This article explicates each of these elements—the Four A’s—in the context of cross-media news work, a perspective that lends equal emphasis to editorial, business, and technology as key sites for studying the organizational influences shaping journalism. We argue for developing a sociotechnical emphasis for the study of institutional news production: a holistic framework through which to make sense of and conduct research about the full range of actors, actants, and audiences engaged in cross-media news work activities. This emphasis addresses two shortcomings in the journalism studies literature: a relative neglect about (1) the interplay of humans and technology, or manual and computational modes of orientation and operation, and (2) the interplay of editorial, business, and technology in news organizations. This article’s ultimate contribution is a cross-media news work matrix that illustrates the interconnections among the Four A’s and reveals where opportunities remain for empirical study

A Decade of Research on Social Media and Journalism: Assumptions, Blind Spots, and a Way Forward

Amid a broader reckoning about the role of social media in public life, this article argues that the same scrutiny can be applied to the journalism studies field and its approaches to examining social media. A decade later, what hath such research wrought? In the broad study of news and its digital transformation, few topics have captivated researchers quite like social media, with hundreds of studies on everything from how journalists use Twitter, Facebook, Instagram, YouTube, and Snapchat to how such platforms facilitate various forms of engagement between journalists and audiences. Now, some 10 years into journalism studies on social media, we need a more particular accounting of the assumptions, biases, and blind spots that have crept into this line of research. Our purpose is to provoke reflection and chart a path for future research by critiquing themes of what has come before. In particular, our goal is to untangle three faulty assumptions—often implicit but no less influential—that have been overlooked in the rapid take-up of social media as a key phenomenon for journalism studies: (1) that social media would be a net positive; (2) that social media reflects reality; and (3) that social media matters over and above other factors

Doctors Fact-Check, Journalists Get Fact-Checked: Comparing Public Trust in Journalism and Healthcare

Public trust in journalism has fallen disconcertingly low. This study sets out to understand the news industry’s credibility crisis by comparing public perceptions of journalism with public perceptions of another institution facing similar trust challenges: healthcare. Drawing on in-depth interviews with 31 US adults, we find that although both healthcare and journalism face public distrust, members of the public generally tend to feel more trusting of individual doctors than they do of individual journalists. This is because people (a) perceive doctors to be experts in their field and (b) engage more frequently with doctors than they do with journalists. Consequently, our interviewees described treating their doctors as "fact-checkers" when it comes to health information they find online, demonstrating trust in their physicians despite their lack of trust in healthcare more broadly. Meanwhile, the opposite unfolds in journalism: Instead of using legitimate news sources to fact-check potential misinformation, people feel compelled to "fact-check" legitimate news by seeking alternative sources of corroboration. We conclude that, to improve their credibility among the public, journalists must strike the right balance between persuading the public to perceive them as experts while also pursuing opportunities to engage with the public as peers

Algorithms, Automation, and News

This special issue examines the growing importance of algorithms and automation in the gathering, composition, and distribution of news. It connects a long line of research on journalism and computation with scholarly and professional terrain yet to be explored. Taken as a whole, these articles share some of the noble ambitions of the pioneering publications on ‘reporting algorithms’, such as a desire to see computing help journalists in their watchdog role by holding power to account. However, they also go further, firstly by addressing the fuller range of technologies that computational journalism now consists of: from chatbots and recommender systems, to artificial intelligence and atomised journalism. Secondly, they advance the literature by demonstrating the increased variety of uses for these technologies, including engaging underserved audiences, selling subscriptions, and recombining and re-using content. Thirdly, they problematize computational journalism by, for example, pointing out some of the challenges inherent in applying AI to investigative journalism and in trying to preserve public service values. Fourthly, they offer suggestions for future research and practice, including by presenting a framework for developing democratic news recommenders and another that may help us think about computational journalism in a more integrated, structured manner