The proliferation of computational methods has broadened the scope of numerous sectors within communication studies, including in journalism, with an increasing number of scholars leveraging these state-of-the-art
techniques to engage with pertinent issues in this domain. In parallel, journalism is itself currently experiencing profound shifts in its daily practices, business models, professional norms, content creation, and global societal impact. Much of journalism research now centres on automated, data, and immersive journalism. This preconference aims to initiate substantive discussions among scholars of varied expertise and origins, and facilitate robust interdisciplinary collaborations into the methodological, theoretical, and practical aspects of computational journalism studies.
Pushing the boundaries of journalism studies by exploring innovative methodologies and advancing theoretical frameworks.
Identifying and demonstrating the transformative power of computational methods on journalism practice, seeking to further understand and articulate the profound shifts in journalistic norms, practices, and frameworks.
Nurturing communities among scholars who share an interest in employing computational approaches to either conduct research on journalism or practice journalism.
Encouraging meaningful dialogues between scholars with diverse methodological and theoretical backgrounds, hailing from various subdomains such as journalism studies, political communication, communication and technologies, computational methods, and more.
Facilitating networking and collaboration opportunities for scholars at various career stages, across diverse areas of expertise and geographical locations, with an emphasis on inclusivity and representation of scholars from the global south. An ICA 2024 preconference at the intersection of computational methods and journalism studies.