Published on April 16, 2017

Guest editors: Ryan K. Boettger (University of North Texas) and Suguru Ishizaki (Carnegie Mellon University)

The approaches, theories, and technologies that inform professional communication remain a consequential and ever evolving area of study.

In 2006, Thomas Orr guest edited a special issue of IEEE Transactions on Professional Communication that provided insight from corpus linguistics for professional communication [1]. Orr described the “quest” to understand and improve how professionals communicate in the workplace, citing corpus linguistics as a useful and complementary tool for empirically oriented researchers. The issue showcased rhetorical and linguistic analyses of professional genres and language strategies, as well as introduced readers to what is now one of the most widely used text analysis toolkits in the world [2].

The quest to understand the nuances of professional communication continues and now includes a host of new disciplinary partners and approaches. The interdisciplinary field now known as data science (or data-driven science) has emerged as a promising resource for allowing us to engage in new research questions and to expand our thinking about communication artifacts. We are now saturated with terms often associated with data science (e.g., big data, content analysis, text mining, sentiment analysis, topic modeling, network analysis) that span numerous disciplines (e.g., corpus and computational linguistics, learning technologies, artificial intelligence, statistics, and business analytics). Yet the field of professional and technical communication is just beginning to embrace the power of data-driven approaches.

Our proposed special issue extends Orr’s work by exploring advances in data-driven approaches to the study of professional and technical communication in the past decade. We invite submissions from researchers across the disciplines who employ computer-aided approaches to written, oral, visual, and digital forms of professional communication. We are interested in submissions related to the following questions:

  • How has the increasing availability of large-scale data coupled with accessible analysis and visualization tools changed the research, teaching, and practice of professional, technical, and engineering communication? How has our understanding of professional communication reflected the evolving disciplinary landscape of data analysis and facilitated collaborative opportunities?
  • How has technology influenced our understanding of professional communication? What results have been yielded from sentiment analyses and natural language processing as well as by analyzing social media platforms, project management software, and crowdfunding sites?
  • What techniques are professional communicators using to interpret large data sets and produce rhetorically persuasive narratives from data? How are professionals using data-driven approaches and results to solve workplace problems?
  • What data-driven approaches are being used to teach engineers and other STEM specialists the language nuances of communicating in their discipline? What are the challenges of teaching and using data-driven methods for audiences who are not formally trained language specialists?
  • How do the social variables of professional communicators—gender, age, discipline, native-speaker status—influence how they communicate to various audiences?
  • What pedagogical approaches are available for training graduate students to use data-driven approaches to their research?
  • How are data-driven approaches used in technical and professional communication classrooms?

Types of Projects

The types of research projects accepted for this special issue include but are not limited to

  • research articles
  • integrative literature reviews
  • case studies
  • tutorials
  • teaching cases

For further details, please consult project formats supported by the IEEE Transactions on Professional Communication at https://procomm.ieee.org/transactions-of-professional-communication/for-prospective-authors/guidelines-to-follow/.

Submission Process

This special issue has a two-step review process (See below for timeline):

  1. If you have a project that you believe is a good fit, email a 750-word abstract summarizing your proposed article to the guest editors (ryan.boettger@unt.edu and suguru@cmu.edu). The guest editors will use the abstracts to select authors, who will be invited to submit a complete draft.
  2. Once you submit a full article draft, it will be peer reviewed. Based on the peer reviews, the guest editors will select articles for the special issue.

IMPORTANT: If you plan to present the results of a study involving human research subjects or will use examples from corporate or government communications, please obtain all approvals and permissions for publishing your results from your institution, company, and/or agency before you submit your abstract for review.

Timeline for Submissions

Abstract submission deadline June 1, 2017
Notification of authors July 1, 2017
Submission of complete drafts December 15, 2017
Reviews returned to authors March 1, 2018
Revised drafts submitted for second review May 1, 2018
Final and complete articles submitted August 1, 2018
Editing of articles completed by guest editor(s) September 1, 2018
Special issue published December 2018

References

[1]            T. Orr, “Introduction to the special issue: Insights from corpus linguistics for professional communication,” IEEE Transactions on Professional Communication, vol. 49, no. 3, pp. 213-216, 2006.

[2]            L. Anthony, “Developing a freeware, multiplatform corpus analysis toolkit for the technical writing classroom,” IEEE Transactions on Professional Communication, vol. 49, no. 3, pp. 275-286, 2006.