Narrative Persuasion in a New Media Environment: The Impact of Binge-Watching and Second-Screening

The study explored the role of second-screen use and binge-watching in moderating entertainment education (EE) effects. A pretest/posttest experiment of 273 viewers of East Los High measured the effects of exposure to three subplots, concerning alcohol abuse, abortion, and immigration. The effect of identification with characters on change in attitudes was significantly moderated by second-screen use and binge-watching. In particular, second-screening tended to enhance the positive impact of identification; whereas, among respondents who binge-watched the show, the effects of identification were weaker.     

White lies: a racial history of the (post)truth

In the aftermath of the 2016 election of President Trump, a veritable cottage industry of opinion pieces, blogs, and articles emerged overnight, most of which seemed to agree that only the post-truth could explain how a racist, misogynistic, neo-nationalist member of the economic elite could win a presidential election. This article, in contrast, is inspired by Barbara Christian’s injunction that we question why a given statement, concept, or theory is now acceptable when before it was not. Operating in this spirit, we critique post-truth critics for neglecting the material tradition of ideological criticism in favor of epistemological explanations for understanding post-truth literature; we then offer two case studies—American drug policy and housing policy—to illustrate the racial amnesia required for claiming that only now do we live in a post-truth era.     

Nullis in Verba: Advancing Research through Transparency and Openness

Nullis in verba was chosen as the motto of the Royal Society, as it embodied the culture of transparency and collaboration that were the hallmarks of the Royal Society and of the scientific method it promoted. Communication, using the tools of the day, was essential to this community of scientists as they created and shared new knowledge. Almost three hundred years later, libraries continue to advance principles relating to the importance of collaboration and transparency. This two-part article series, published jointly in International Information and Library Review and Technical Services Quarterly explores notions of transparency and collaboration in research and how these ideas are impacting the world of librarianship – from information creation, organization and access perspectives.     

Setting a Non-Agenda: Effects of a Perceived Lack of Problems in Recent News or Twitter

The mere perception that news has given certain problems more coverage can lead the audience to assume that those problems are more important. Given that the news media, at times, obsesses over relatively trivial matters, and given that the audience is increasingly able to filter media exposure, it is worth asking what happens when audience members perceive that recent media coverage has not emphasized any very important problems. In such cases, audience members might assume that any problems facing the nation must not be particularly important. We explicate this attitude of political complacency, test whether perceived media agendas lacking important problems can influence it, and explore whether complacency helps explain political disengagement. We also explore whether these effects generalize beyond news, to new media gatekeepers such as Twitter. Two experiments tested effects of a perceived absence of important problems in recent news or Twitter content. In the case of news, but not Twitter, this increased complacency in both studies. Study 2 added a no-exposure control and found that effects on complacency were driven by the cueing of nonproblem stories, not by the absence of problem story cues. Both studies validated complacency as a predictor of political disengagement.     

Using word embeddings in Twitter election classification

Word embeddings and convolutional neural networks (CNN) have attracted extensive attention in various classification tasks for Twitter, e.g. sentiment classification. However, the effect of the configuration used to generate the word embeddings on the classification performance has not been studied in the existing literature. In this paper, using a Twitter election classification task that aims to detect election-related tweets, we investigate the impact of the background dataset used to train the embedding models, as well as the parameters of the word embedding training process, namely the context window size, the dimensionality and the number of negative samples, on the attained classification performance. By comparing the classification results of word embedding models that have been trained using different background corpora (e.g. Wikipedia articles and Twitter microposts), we show that the background data should align with the Twitter classification dataset both in data type and time period to achieve significantly better performance compared to baselines such as SVM with TF-IDF. Moreover, by evaluating the results of word embedding models trained using various context window sizes and dimensionalities, we find that large context window and dimension sizes are preferable to improve the performance. However, the number of negative samples parameter does not significantly affect the performance of the CNN classifiers. Our experimental results also show that choosing the correct word embedding model for use with CNN leads to statistically significant improvements over various baselines such as random, SVM with TF-IDF and SVM with word embeddings. Finally, for out-of-vocabulary (OOV) words that are not available in the learned word embedding models, we show that a simple OOV strategy to randomly initialise the OOV words without any prior knowledge is sufficient to attain a good classification performance among the current OOV strategies (e.g. a random initialisation using statistics of the pre-trained word embedding models).     

Contesting Communities

This introductory article to the combined special issue of Journalism Studies and Journalism Practice provides an overview of some of the key contemporary approaches to studying journalism and social order. It argues the need to step beyond a functionalist framework when considering the news media’s central role in shaping social connections, community and cohesion. To advance our understandings of social order, our paper suggests a greater emphasis of the significance of journalism’s relationship to the wider social sphere along with three other key considerations, including (1) a critical focus on the relationship between media, politics and social order, especially in defining and/or negotiating “anti-social” practices and social disintegration; (2) a more refined focus on the “imagined” and geographic boundaries of news audiences in digital spaces; and (3) the changing relationship to norms and conventions of journalism practice from trust and legitimacy to the role of journalists as arbiters and connectors across social spaces.     

Rapid mask prototyping for microfluidics

With the rise of microfluidics for the past decade, there has come an ever more pressing need for a low-cost and rapid prototyping technology, especially for research and education purposes. In this article, we report a rapid prototyping process of chromed masks for various microfluidic applications. The process takes place out of a clean room, uses a commercially available video-projector, and can be completed in less than half an hour. We quantify the ranges of fields of view and of resolutions accessible through this video-projection system and report the fabrication of critical microfluidic components (junctions, straight channels, and curved channels). To exemplify the process, three common devices are produced using this method: a droplet generation device, a gradient generation device, and a neuro-engineering oriented device. The neuro-engineering oriented device is a compartmentalized microfluidic chip, and therefore, required the production and the precise alignment of two different masks.