CCR Special Issue Call for Papers on Generative AI

2024-11-12

Overview 

Generative AI (GenAI) is revolutionizing the communication landscape, enabling machines to generate diverse forms of content such as text, audio, and multimedia. These advances hold immense potential for reshaping how we understand media, as they facilitate faster, more personalized, and scalable content production. However, they also raise significant questions about the ethical implications, accuracy, and societal impacts of machine-generated content. As a result, human-machine communication is emerging as a critical area of inquiry that explores how humans interact with AI-generated content, how GenAI tools can be harnessed to achieve desired societal outcomes, and how these systems shape broader communication ecosystems.

In communication research, GenAI introduces new opportunities both as a subject of study and as a methodological tool. Researchers are increasingly exploring how AI-driven content influences public discourse, media production, and audience engagement. At the same time, GenAI is being integrated into research workflows, offering innovative computational solutions for data generation and analysis. This special issue of Computational Communication Researchwill focus on the diverse ways in which GenAI intersects with communication science, from its theoretical implications to its practical applications in research.

We invite submissions on a wide range of computational communication research topics, including studies on AI’s role in media, public discourse, news production, and other communication phenomena. All submissions must employ computational methods to answer communication research questions.

1. Research Articles: We seek manuscripts that make substantive contributions to communication science by employing computational techniques to study GenAI, either as a communication phenomenon or as a research tool for understanding communication processes and human-AI or AI-AI interactions. Two broad sub-themes emerge under this category:

a. Generative AI as the Object of Research: Manuscripts in this sub-theme should apply computational techniques to investigate GenAI as a communication technology. Some examples include studies that:

  1. Analyze large datasets of machine-generated content.

  2. Apply network analysis to explore how GenAI impacts information diffusion.

  3. Study how AI-generated media affects public discourse and engagement.

  4. Compare AI and human interactions in various platforms, focusing on trust, information exchange, and relationship building.

  5. Evaluate the effectiveness of GenAI tools for misinformation detection.

These articles should use computational methods to analyze the influence of AI-generated content on communication systems and focus on its societal implications.

b. Generative AI as a Methodological Tool: Manuscripts in this sub-theme should demonstrate how computational techniques involving GenAI are used to conduct empirical communication research. Submissions need to go beyond the simple one-shot use of GenAI for dataset generation, content coding, stimuli creation, or agent simulation, by 1) integrating innovative and creative uses of GenAI, or 2) complementing the coding process with robust validation measures, or 3) illuminating potential issues such as biases, hallucinations, etc. Some examples include studies that:

  1. Use GenAI to generate synthetic datasets for communication research.

  2. Use GenAI to annotate or classify communication data, including multimodal data.

  3. Use GenAI to create experimental stimuli.

  4. Use GenAI to develop agents that simulate human behavior.

We also welcome meta-analyses and synthesizing papers that aggregate and assess existing computational research on GenAI’s methodological potential in communication studies, with attention to these AI methodologies’ accuracy, scalability, and reliability.

2. Software Demonstration Articles: Besides traditional research articles, we invite Software Demonstration Articles that introduce new tools, platforms, or software designed to incorporate GenAI into communication research workflows. These articles should offer practical tutorials or demonstrations of software that computational researchers can adopt to integrate GenAI into their empirical work. The emphasis is on practical, open-source tools and frameworks that make it easier for other computational researchers to implement AI-driven methods in their own studies.

Submissions that explore the integration of GenAI with other computational methods and address the ethical considerations surrounding these technologies (such as bias, transparency, replicability, and societal impact) are highly encouraged. We also encourage submissions representing diverse geographical localities, cultural considerations, and disciplinary traditions.

Computational Communication Research is an open-access journal, free for both authors and readers. All accepted papers will be published under a Creative Commons Attribution license.

Submission Guidelines

All special issue extended abstracts should be submitted to the journal’s online system at https://journal.computationalcommunication.org/submission, to the section: 'Special Issue: Generative AI'

Extended abstracts are limited to 1,500 words (excluding the title page, references, tables, and figures) and should follow this format:

  1. Title Page: Include a title, author(s), and affiliation(s), and specify the type of submission (Research Article – GenAI as Object/Tool or Software Demonstration Article).

  2. Proposed Research (up to 1,000 words): For Research Articles, include a review of relevant literature, research questions, hypotheses, and methods. For Software Demonstration Articles, describe the software or tool, the problem it solves, and provide details about its functionality and code availability.

  3. Timeline and Milestones (up to 100 words): Provide a clear outline of when data will be collected and analyzed and when the paper will be drafted.

  4. Contribution to Social Science Research (up to 400 words): Outline how the proposed research or software will contribute to broader social science scholarship, particularly within the domain of computational communication research.

Review Criteria

Abstracts will be evaluated by the guest editors and additional experts as necessary. Review criteria will focus on the relevance of the proposed research to the special issue theme, theoretical and empirical contributions to communication science, methodological rigor, broader impacts, and feasibility. Please note that acceptance of abstracts does not guarantee final publication, as full manuscripts will undergo peer review.

Deadlines

  • -  Extended abstracts due: December 31, 2024

  • -  Decisions on extended abstracts: January 31, 2025

  • -  Full papers for accepted abstracts due: April 30, 2025

  • -  Expected publication of final articles: November 2025

    Inquiries for Guest Editors

    For further questions, please contact the guest editorial team at ccrgenai@gmail.com

    Guest editorial team:
    Subhayan Mukerjee, National University of Singapore Alvin Zhou, University of Minnesota
    Ewa Maslowska, University of Illinois Urbana-Champaign