The measurement of meaning

Deciding What's News: A Study of CBS Evening News, NBC Nightly News, Newsweek, and Time

The deceptively simple question “What is news?” remains pertinent even as we ponder the future of journalism in the digital age. This article examines news values within mainstream journalism and considers the extent to which news values may be changing since earlier landmark studies were undertaken. Its starting point is Harcup and O’Neill’s widely-cited 2001 updating of Galtung and Ruge’s influential 1965 taxonomy of news values. Just as that study put Galtung and Ruge’s criteria to the test with an empirical content analysis of published news, this new study explores the extent to which Harcup and O’Neill’s revised list of news values remain relevant given the challenges (and opportunities) faced by journalism today, including the emergence of social media. A review of recent literature contextualises the findings of a fresh content analysis of news values within a range of UK media 15 years on from the last study. The article concludes by suggesting a revised and updated set of contemporary news values, whilst acknowledging that no taxonomy can ever explain everything.

https://www.tandfonline.com/doi/pdf/10.1080/1461670X.2016.1150193

What is news? News values revisited (again)

Stereotyping, prejudice, and discrimination

Исследование влияния пола и психологических характеристик автора на количественные параметры его текста с использованием программы Linguistic Inquiry and Word Count

The huge collections of news content which have become available through digital technologies both enable and warrant scientific inquiry, challenging journalism scholars to analyse unprecedented amounts of texts. We propose Latent Dirichlet Allocation (LDA) topic modelling as a tool to face this challenge. LDA is a cutting edge technique for content analysis, designed to automatically organize large archives of documents based on latent topics, measured as patterns of word (co-)occurrence. We explain how this technique works, how different choices by the researcher affect the results and how the results can be meaningfully interpreted. To demonstrate its usefulness for journalism research, we conducted a case study of the New York Times coverage of nuclear technology from 1945 to the present, partially replicating a study by Gamson and Modigliani. This shows that LDA is a useful tool for analysing trends and patterns in news content in large digital news archives relatively quickly.

Quantitative analysis of large amounts of journalistic texts using topic modelling

Computational text analysis has become an exciting research field with many applications in communication research. It can be a difficult method to apply, however, because it requires knowledge of various techniques, and the software required to perform most of these techniques is not readily available in common statistical software packages. In this teacher’s corner, we address these barriers by providing an overview of general steps and operations in a computational text analysis project, and demonstrate how each step can be performed using the R statistical software. As a popular open-source platform, R has an extensive user community that develops and maintains a wide range of text analysis packages. We show that these packages make it easy to perform advanced text analytics.

Text Analysis in R

On newspaper websites, journalists can observe the preferences of the audience in unprecedented detail and for low costs, based on the audience clicks (i.e. page views) for specific news articles. This article addresses whether journalists use this information to cater to audience preferences in their news selection choices. We analyzed the print and online editions of five national newspapers from the Netherlands with a mixed-method approach. Using a cross-lagged analysis covering 6 months, we found that storylines of the most-viewed articles were more likely to receive attention in subsequent reporting, which indicates that audience clicks affect news selection. However, based on interviews with editors we found that they consider the use of this information for news selection to conflict with professional norms. We elaborate on the implications of this discrepancy in the norms and behaviors of journalists, and project directions for future studies.

News selection criteria in the digital age: Professional norms versus online audience metrics

The semantic mapping of words and co-words in contexts

Meaning can be generated when information is related at a systemic level. Such a system can be an observer, but also a discourse, for example, operationalized as a set of documents. The measurement of semantics as similarity in patterns (correlations) and latent variables (factor analysis) has been enhanced by computer techniques and the use of statistics; for example, in "Latent Semantic Analysis". This communication provides an introduction, an example, pointers to relevant software, and summarizes the choices that can be made by the analyst. Visualization ("semantic mapping") is thus made more accessible.

Kasper Welbers

Papers

Quantitative analysis of large amounts of journalistic texts using topic modelling

Text Analysis in R

News selection criteria in the digital age: Professional norms versus online audience metrics

The semantic mapping of words and co-words in contexts

The semantic mapping of words and co-words in contexts