Applying LDA Topic Modeling in Communication Research: Toward a Valid and Reliable Methodology

ABSTRACT

Latent Dirichlet allocation (LDA) topic models are increasingly being used in communication research. Yet, questions regarding reliability and validity of the approach have received little attention thus far. In applying LDA to textual data, researchers need to tackle at least four major challenges that affect these criteria: (a) appropriate pre-processing of the text collection; (b) adequate selection of model parameters, including the number of topics to be generated; (c) evaluation of the model’s reliability; and (d) the process of validly interpreting the resulting topics. We review the research literature dealing with these questions and propose a methodology that approaches these challenges. Our overall goal is to make LDA topic modeling more accessible to communication researchers and to ensure compliance with disciplinary standards. Consequently, we develop a brief hands-on user guide for applying LDA topic modeling. We demonstrate the value of our approach with empirical data from an ongoing research project.     

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.     

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.     

Esports players,got muscle? Competitive video game players’ physical activity,body fat,bone mineral content,and muscle mass in comparison to matched controls

BackgroundEsports players, like traditional athletes, practice for long hours and, thus, are vulnerable to the negative health effects of prolonged sitting. There is a lack of research on the physical activity and the health ramifications of prolonged sitting by competitive players. The purpose of this study was to investigate activity levels, body mass index (BMI), and body composition in collegiate esports players as compared to age-matched controls.MethodsTwenty-four male collegiate esports players and non-esports players between 18 and 25 years of age signed a written consent to participate. Physical activity was examined using daily activity (step count) with a wrist-worn activity tracker. A questionnaire assessing physical activity was also administered. Secondary outcomes included body-fat percentage, lean-body mass, BMI, and bone mineral content measured using dual X-ray absorptiometry.ResultsThe step count in the esports players was significantly lower than the age-matched controls (6040.2 ± 3028.6 vs. 12843.8 ± 5661.1; p = 0.004). Esports players exhibited greater body-fat percentage (p = 0.05), less lean body mass (p = 0.003), and less bone mineral content (p = 0.03), despite no difference in BMI between the esports and non-esports players.ConclusionAs compared to non-esports players, collegiate esports players were significantly less active and had a higher body-fat percentage, with lower lean body mass and bone mineral content. The BMIs showed no difference between the 2 groups. Esports athletes displayed significantly less activity and poor body composition, which are all correlated with potential health issues and risk of injury. BMI did not capture this difference and should not be considered as an accurate measure of health in competitive esports players.     

A CRISPR/Cas12a-empowered surface plasmon resonance platform for rapid and specific diagnosis of the Omicron variant of SARS-CoV-2

The outbreak of the COVID-19 pandemic was partially due to the challenge of identifying asymptomatic and presymptomatic carriers of the virus, and thus highlights a strong motivation for diagnostics with high sensitivity that can be rapidly deployed. On the other hand, several concerning SARS-CoV-2 variants, including Omicron, are required to be identified as soon as the samples are identified as ‘positive’. Unfortunately, a traditional PCR test does not allow their specific identification. Herein, for the first time, we have developed MOPCS (Methodologies of Photonic CRISPR Sensing), which combines an optical sensing technology-surface plasmon resonance (SPR) with the ‘gene scissors’ clustered regularly interspaced short palindromic repeat (CRISPR) technique to achieve both high sensitivity and specificity when it comes to measurement of viral variants. MOPCS is a low-cost, CRISPR/Cas12a-system-empowered SPR gene-detecting platform that can analyze viral RNA, without the need for amplification, within 38 min from sample input to results output, and achieve a limit of detection of 15 fM. MOPCS achieves a highly sensitive analysis of SARS-CoV-2, and mutations appear in variants B.1.617.2 (Delta), B.1.1.529 (Omicron) and BA.1 (a subtype of Omicron). This platform was also used to analyze some recently collected patient samples from a local outbreak in China, identified by the Centers for Disease Control and Prevention. This innovative CRISPR-empowered SPR platform will further contribute to the fast, sensitive and accurate detection of target nucleic acid sequences with single-base mutations.