Social media, the pandemic, and environmental hazards have all played a role in shifting the landscape of risk communication. This paper takes a retroactive risk approach to study how COVID-19 messaging was shaped in the first 2 years of the pandemic. Using a corpus of 764 news releases from five health departments, I combine corpus analysis with coding based on government capacities to show that health departments highlighted public health data (surveillance) and risk guidance (governance), while downplaying enforcement (coercion). This process of revisiting communication from an acute risk phase can help us recalibrate how public health roles are constituted through language to prepare for future events.

Asking for money is one of the core communicative functions of a crowdfunding campaign. This article uses a novel corpus analysis scoring technique to investigate appeals language in a corpus of 312,529 Kickstarter campaigns. Our results show distinctive use patterns involving the verbs need , raise , please , make , and hope . Conceptual patterns, such as inviting the reader to participate in the creation of a product, underlie specific formulations of successful and unsuccessful word patterns and sentences. We conclude with theoretical and practical outcomes to aid technical communicators in more effectively writing crowdfunding campaigns on Kickstarter.

Social justice is a framework that has been at the forefront of technical communication in recent years. While social justice is often applied in participatory studies, it can also feature in studies using quantitative methods. In this study, I use corpus-based critical discourse analysis to investigate the portrayal of migrants in the World Migration Reports, the flagship publication of the International Organization for Migration. I emphasize context to bring in the social justice framework in this analysis. This study finds that the World Migration Reports represent migrants within various topoi, with a particular focus on the topos of advantage and that of danger/threat.

A quantitative research study collects numerical data that must be analyzed to help draw the study’s conclusions. Teaching quantitative data analysis is not teaching number crunching, but teaching a way of critical thinking for how to analyze the data. The goal of data analysis is to reveal the underlying patterns, trends, and relationships of a study’s contextual situation. Learning data analysis is not learning how to use statistical tests to crunch numbers but is, instead, how to use those statistical tests as a tool to draw valid conclusions from the data. Three major pedagogical goals that must be taught as part of learning quantitative data analysis are the following: (a) determining what questions to ask during all phases of a data analysis, (b) recognizing how to judge the relevance of potential questions, and (c) deciding how to understand the deep-level relationships within the data.

The authors examine language from the perspective of models of empirical sciences, which discipline studies the relationship between reality, models, and formalisms. Such a perspective allows one to notice that linguistics approached within the classical framework share a number of problems with other experimental sciences studied initially exclusively within that framework because of making the same sort of assumptions. By examining solutions to some of these problems found in contemporary science, the authors point out alternative approaches, which could be relevant for linguistics research, and some of which have already been tested in language studies. In particular, Corpus Linguistics is presented as an especially promising approach, positioned to avoid many of the pitfalls of the classical framework. Consequently, it seems that the future of linguistics, from theoretical to applied, such as Technical Writing, must be embraced by Corpus Linguistics research.

A qualitative study using reading protocols suggests that when readers of informative documents understand conveyed information satisfactorily, they make direct confirmations and positive comprehension evaluations. When readers are uncertain about the accuracy of their understanding, they guess, make assumptions, or render the text's language into their own words. When readers' understanding is impaired, they ask for more clearly established links or relationships in the text, or they pinpoint some ambiguity or lack of resolution. When readers' understanding is unsatisfactory but not impaired, they request additional information. In addition, readers make evaluative suggestions that introduce, focus, emphasize, or reiterate their other comprehension-related responses. The response patterns isolated in this qualitative study indicate the need for specific quantitative research and suggest some directions for developing reader-based heuristics for informative writing.