INTEREST CATEGORY: MARKETING COMMUNICATIONS
POSTING TYPE: Calls: Journals

Author: Jisu Huh

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Proposals are being solicited for a special issue of the Journal of Advertising dedicated to Computational Advertising Research Methodology.

Computational social science (CSS) research is a fast-growing interdisciplinary research approach across all social science disciplines. Computational Advertising Research, which applies CSS methodology to advertising research, has emerged in recent years. Still, there are many issues regarding methodological rigor, validity, and research ethics, and a lack of standards and best practice guidelines for this research methodology makes conducting, reviewing, and reading computational advertising research rather difficult. Against this backdrop, this Journal of Advertising Special Issue aims: (1) to examine the most critical methodological developments and issues in the advertising research field in connection to the rise of programmatic advertising, data-driven targeting and personalization, and AI advertising; (2) to set the research standards and ethical guidelines for future researchers using computational social science research methods to address wide-ranging advertising research problems; (3) to provide helpful, practical guidelines that can improve computational advertising research’s internal and external validity; and (4) to contribute to methodological innovation and advancement of the emerging field of computational advertising research in an ethical and responsible manner. This Special Issue is envisioned as a “method go-to” issue like the 2017 JA Themed Issue on Methodology in Advertising Research in the content and form.

Paper proposals for this Special Issue are solicited. The submitted proposals will be reviewed by the JA editorial team, and selected proposal authors will be invited to submit their completed papers to JA, which will undergo a blind review process. Selected authors will also be invited to participate in the Computational Advertising Thought Leadership Forum (TLF) event held at the University of Minnesota in Minneapolis, MN, in fall 2023 (tentative date: October 19-20, 2023), where the computational advertising research methodological issues will be discussed in depth.

The tentative timeline for this Special Issue project is as follows:

• Paper proposal submission deadline: July 31, 2023
• Decisions made and authors notified: August 31, 2023
• Computational Advertising Thought Leadership Forum (TLF): October 19-20, 2023
• Submission of completed papers: January 31, 2024
• First-round reviews due: March 1, 2024
• First-round review decisions and R&R letters to authors: March 15, 2024
• Author first R&R’s due: April 15, 2024
• Second-round reviews due: May 15, 2024
• Second-round review decisions and letters to authors: May 31, 2024
• Author second R&R’s due: June 30, 2024
• Final review decisions: July 15, 2024
• Submission of final revised manuscripts due: July 31, 2024
• Author Final Manuscripts to Production: August 15, 2024
• Tentative Print Publication: October/December 2024

Relevant topics include:

1. Overview of Computational Advertising Research Methodology – Core Principles and Issues (How CSS differs from more traditional advertising research, what are the boundaries, what kinds of data are gathered and analyzed, what’s unique here in our field, etc.)
2. Revisiting Concept Explication and Measurement Validity for Computational Advertising Research
3. Computer-Assisted Advertising Content Analysis (text, audio, video ad content analysis)
4. Sentiment Analysis
5. Affective Computing and Emotion AI
6. Attention Analysis (eye-tracking, neuroscience, Google Glass data, etc.)
7. Network Analysis (inter-consumer connections, consumer-advertiser connections)
8. Computational Experimental Research
9. Measuring Behavioral Responses to Advertising
10. Neuromarketing Research
11. Multimethod Research Approach for Methodological Triangulation
12. Ethical Issues in Computational Advertising Research (this can be broken into multiple articles, including the following topics)
13. Privacy issues and human subject protection (including institutional norms and how to inform institutions to promote better self-regulation)
14. Artificial intelligence (including generative AI such as ChatGPT) and Implications for Advertising Research

III.     Algorithmic bias and fairness

1. Open science principles (including conflicts between protecting participants as the data source vs. promoting open science)
2. Ethics and potential conflicts of interests in industry-academy collaboration and permission
3. Institutional transformation in response to computational research – pipeline infrastructure transformation (Institutions can include universities, journals, P&T research evaluation issues in collaborative interdisciplinary research (research model differences))
4. Opportunities, Challenges, and Pitfalls in Computational Advertising Research
5. Future Development in Computational Advertising Practice and Research (untapped research areas, methods, and data sources)

Proposal Submission Guidelines 

All proposals should be submitted via email to Dr. Jisu Huh, Editor-in-Chief, at jaeditor@umn.edu

Proposal requirement:

• Maximum 2-page description of the article and justifications
• Authors’ brief biographical information and maximum 5 key publications relevant to the proposed article topic

Submission deadline: July 31, 2023

 Any questions about the Special Issue can be sent to the Editor-in-Chief at jaeditor@umn.edu.

Please consider contributing to this Special Issue and help spread the word among your colleagues.

Sincerely,

Jisu Huh
Editor-in-Chief
Journal of Advertising