We invite the submission of contributions exploring the interface between data and computer science and journalism in three categories: research, practice, and technology.
- Research. Academic research papers exploring a question of interest in journalism or data and computing sciences as it relates back to journalism and news information;
- Practice. Journalist-oriented talks focused on experiences or case studies in journalism including stories, visualizations, investigations, or interactive experiences produced with, by, or about data and algorithms;
- Technology. Descriptions of new computational and data-driven tools, platforms, applications, and services that enable novels ways of finding, producing, interacting with, or distributing news content.
- Research contributions should submit a 5-page paper (including references)
- Practice and Technology contributions may opt to submit either a 5-page paper, or a 1-page abstract. These contributions will be considered for a standalone talk or a panel.
- All submissions must be in PDF and use the standard ACM SIGCHI Template downloadable here.
Please upload your submission to the EasyChair submission site before the deadline.
Wednesday October 31, 8pm eastern time.
Accepted contributions will be invited to present the work in oral, poster, or demo sessions.
Written contributions will be published as part of an online proceedings linked off this site but should be considered “non-archival” for the sake of journal submissions elsewhere. At the same time, we highly encourage unique and novel contributions with limited overlap to other related publications the author may have or intend to publish. You can view selected papers from the C+J 2017 Symposium online. Accepted contributions will be invited to extend papers and abstracts into book chapters for an edited collection to be published by Columbia University Press
Topics of interest include:
- Algorithmic accountability reporting & investigation
- Algorithms in news distribution
- Algorithmic content curation
- Automated and semi-automated content production
- Computational and data journalism education
- Computational propaganda
- Data and computing in different news domains: sports, health, business, economy, politics
- Data visualization and storytelling
- Data and information gathering via computational means
- Design of algorithmic news media applications, tools, or content
- Economic, labor, legal, or policy implications of algorithmic news media
- Fact-checking, verification, and rumor detection and tracking
- Human-computer interaction in news consumption or production
- Journalism ethics
- Journalistic applications of machine learning, data mining, and artificial intelligence
- Media bias and diversity
- Newsbots and chatbots
- Newsroom challenges with algorithms, automation, and data
- News personalization and recommendation
- Prediction and simulation
- Sensor and drone journalism
- Social journalism: sharing, commenting, discussion, community engagement
- Structured journalism
- Tools, platforms, and services to support journalistic work
- Transparency, trust, and credibility
- User experiences & interactivity