Scaling up Content Analysis

ABSTRACT

Employing a number of different standalone programs is a prevalent approach among communication scholars who use computational methods to analyze media content. For instance, a researcher might use a specific program or a paid service to scrape some content from the Web, then use another program to process the resulting data, and finally conduct statistical analysis or produce some visualizations in yet another program. This makes it hard to build reproducible workflows, and even harder to build on the work of earlier studies. To improve this situation, we propose and discuss four criteria that a framework for automated content analysis should fulfill: scalability, free and open source, adaptability, and accessibility via multiple interfaces. We also describe how to put these considerations into practice, discuss their feasibility, and point toward future developments.     

More than Bags of Words: Sentiment Analysis with Word Embeddings

ABSTRACT

Moving beyond the dominant bag-of-words approach to sentiment analysis we introduce an alternative procedure based on distributed word embeddings. The strength of word embeddings is the ability to capture similarities in word meaning. We use word embeddings as part of a supervised machine learning procedure which estimates levels of negativity in parliamentary speeches. The procedure’s accuracy is evaluated with crowdcoded training sentences; its external validity through a study of patterns of negativity in Austrian parliamentary speeches. The results show the potential of the word embeddings approach for sentiment analysis in the social sciences.     

Placing Facebook

Facebook is challenging professional journalism. These challenges were evident in three incidents from 2016: the allegation that Facebook privileged progressive-leaning news on its trending feature; Facebook’s removal of the Pulitzer Prize-winning “Napalm Girl” photo from the pages of prominent users; and the proliferation of “fake news” during the US presidential election. Using theoretical concepts from the field of boundary work, this paper examines how The Guardian, The New York Times, Columbia Journalism Review and Poynter editorialized Facebook’s role in these three incidents to discursively construct the boundary between the value of professional journalism to democracy and Facebook’s ascendant role in facilitating essential democratic functions. Findings reveal that these publications attempted to define Facebook as a news organization (i.e., include it within the boundaries of journalism) so that they could then criticize the company for not following duties traditionally incumbent upon news organizations (i.e., place it outside the boundaries of journalism). This paper advances scholarship that focuses on both inward and outward conceptions of boundary work, further explores the complex challenge of defining who a journalist is in the face of rapidly changing technological norms, and advances scholarship in the field of media ethics that positions ethical analysis at the institutional level.     

Expanding opportunities to learn to support inclusive education through drama‐enhanced literacy practices

This study examines how the Early Years Educators at Play (EYEPlay) professional development (PD) programme supported inclusive learning settings for all children, including English language learners and students with disabilities. The EYEPlay PD model is a year‐long programme that integrates drama strategies into literacy practices within real‐classroom contexts. Inclusive education refers to ensuring equal opportunities to access and participation in learning activities for all students. Cultural‐historical activity theory was used to understand and unpack the drama practices. Twelve semi‐structured focus group interviews were conducted with 19 preschool teachers. The data were analysed via constant‐comparative and interpretive methods. The study findings showed that EYEPlay PD practices enhanced inclusive learning settings for diverse groups of students by increasing access and expanding opportunities to learn, and supporting a positive learning environment.     

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.