Rodrigo Zamith

Sourcing the Arab Spring: A Case Study of Andy Carvin's Sources on Twitter During the Tunisian and Egyptian Revolutions

News sourcing practices are critical as they shape from whom journalists get their information and what information they obtain, mostly from elite sources. This study evaluates whether social media platforms expand the range of actors involved in the news through aq uantitative content analysis of the sources cited by NPR’s Andy Carvin on Twitter during the Arab Spring. Results show that, on balance, nonelite sources had a greater representation in the content than elite sources. Alternative actors accounted for nearly half of the messages. The study points to the innovative forms of production that can emerge with new communication technologies, with the journalist as a central node trusted to authenticate and interpret news flows on social awareness streams.

Content Analysis in an Era of Big Data: A Hybrid Approach to Computational and Manual Methods

Massive datasets of communication are challenging traditional, human-driven approaches to content analysis. Computational methods present enticing solutions to these problems but in many cases are insufficient on their own. We argue that an approach blending computational and manual methods throughout the content analysis process may yield more fruitful results, and draw on a case study of news sourcing on Twitter to illustrate this hybrid approach in action. Careful combinations of computational and manual techniques can preserve the strengths of traditional content analysis, with its systematic rigor and contextual sensitivity, while also maximizing the large-scale capacity of Big Data and the algorithmic accuracy of computational methods.

Constructing Climate Change in the Americas: An Analysis of News Coverage in U.S. and South American Newspapers

This study examined the portrayal of climate change in four national newspapers from Argentina, Brazil, Colombia, and the United States. The results indicated that leading media in Brazil and the United States highlighted the policy progress being made to mitigate climate change and presented the issue in economic terms, whereas coverage in Argentina and Colombia portrayed the issue as being urgent and emphasized the catastrophic consequences of climate change. The findings are consistent with previous work indicating a lack of focus on scientific controversy from non-U.S. media and present implications for comparative studies examining nuances in international coverage of climate change.

Content Analysis and the Algorithmic Coder What Computational Social Science Means for Traditional Modes of Media Analysis

To deal with ever-larger datasets, media scholars are increasingly using computational analytic methods. This article focuses on how the traditional (manual) approach to conducting a content analysis—a primary method in the study of media messages—is being reconfigured, assesses what is gained and lost in turning to computational solutions, and builds on a “hybrid” approach to content analysis. We argue that computational methods are most fruitful when variables are readily identifiable in texts and when source material is easily parsed. Manual methods, though, are most appropriate for complex variables and when source material is not well digitized. These modes can be effectively combined throughout the process of content analysis to facilitate expansive and powerful analyses that are reliable and meaningful.

From Public Spaces to Public Sphere

This study examines how journalists and technologists are re-imagining the construction of networked, dynamic spaces for online news discussion through a qualitative study of 126 idea submissions to a popular news innovation contest. We consider these submissions in the light of the concept of the public sphere, with a specific focus on how these submissions might address shortcomings identified in the literature about the ability of the internet, but of news commenting forums in particular, to serve as an extension of the public sphere. Four main themes emerged in the submissions: a need to (1) better organize content, (2) moderate content more effectively, (3) unite disjointed discourse, and (4) increase participation while promoting diversity. We find in these proposed solutions the possibility for relatively low-cost, easy-to-build systems that could moderate comments more efficiently while also facilitating more civil, cohesive, and diverse discourse; however, we also find the lingering danger of designing new systems that could perpetuate old problems such as fragmentation, filter bubbles, and homogenization. Ultimately, it remains to be seen how technological innovations might help or hinder the ability of the internet, and of news commenting spaces in particular, to serve as an extension of the public sphere. More broadly, by studying how these innovation-contest submissions sought to transform the discursive systems of news websites, we can begin to grasp how the evolution of digital journalism, technologically, might facilitate a broader rethinking about how news institutions could better serve the ideals of deliberation in a changing media environment.

On Metrics-Driven Homepages

As audience analytics systems have proliferated in newsrooms, scholars have expressed fears of, and in some cases assumed a shift toward, a metrics-driven workflow where certain gatekeeping decisions are made based on real-time measures of news consumption. This study evaluated the relationship between a news item’s popularity and its subsequent prominence through a two-month analysis of the homepages of 14 news organizations. The results indicated a large divergence between popular and prominent items and limited effects of an item’s popularity on its subsequent prominence and risk of removal from prominent areas of the homepage. The findings give pause to fears of an injudicious turn toward an “agenda of the audience,” at least in the context of content placement, and point to directions for future research on the content-related impacts of audience metrics and analytics.

Capturing and Analyzing Liquid Content

As scholars take greater interest in analyzing digital content, they are being presented with novel methodological challenges. Among these challenges are dealing with the volume and mutable nature of digital content, and especially online content. The present work discusses a computational approach for “freezing” and analyzing aspects of a large volume of “liquid” content using an accessible combination of free software running on consumer hardware. The strengths and limitations of this approach are illustrated through an examination of the method employed in an analysis of more than 125,000 snapshots of the homepages of 21 news organizations over two months.

Are Demographics Adequate Controls for Cell-Phone-Only Coverage Bias in Mass Communication Research?

Cell-phone-only (CPO) households differ along key variables from non-CPO households, creating potential coverage biases in landline-only random-digit-dialing (RDD) surveys. Researchers have attempted to correct for this by weighting their data based on demographic differences. Previous research, however, has not examined CPO coverage biases in media-use surveys—an important oversight as cell phone use is itself a media choice. This article presents a secondary analysis of Pew’s 2012 media consumption survey and concludes that demographics alone are not adequate controls for the CPO bias in media-use surveys.

Quantified Audiences in News Production

A number of social, technological, and economic shifts over the past two decades have led to the proliferation of audience analytics and metrics in journalism. This article contends that we are witnessing a third wave toward the rationalization of audience understanding and distinguishes between audience analytics (systems that capture information) and audience metrics (quantified measures output by those systems). The body of literature on analytics and metrics in the context of news production is then synthesized across the ABCDE of news production: attitudes, behaviors, content, discourse, and ethics. That synthesis leads to an overarching conclusion that while contemporary journalism is not being driven by quantified audiences, both audiences and quantification are playing far more prominent roles in news production than in the past. Scholars and practitioners have also become less pessimistic about analytics and metrics over time, recognizing more nuanced effects and prosocial possibilities. Finally, important gaps in the literature are identified and new research directions proposed to help address them.

A Computational Approach for Examining the Comparability of “Most-Viewed Lists” on Online News Sites:

This study introduces a computational approach for evaluating the lists of most-viewed items present on the homepages of many news organizations, focusing on two dimensions: the list’s rate of change over the course of the day and the median time it takes a news item to appear on the list. That approach is then applied in an analysis of 21 news organizations over 2 months, revealing clusters across those dimensions which indicate the reporting of different data. Scholars are ultimately encouraged to perform their own analyses and cautioned against assuming the lists are comparable just because they appear alike.