Two researchers from Syracuse University are part of a team that received a $130,000 planning grant from the National Science Foundation (NSF) Future of Work at the Human-Technology Frontier.
The project, “Planning to study automation and the future of news production,” brings together an interdisciplinary group of scholars to look at the impact of technology on journalists and journalism.
Kevin Crowston, distinguished professor of information science and associate dean for research at the School of Information Studies, is principal investigator. Keren Henderson, assistant professor of broadcast and digital journalism at the Newhouse School, is also part of the team. Other team members include Jeffrey Nickerson, professor at Stevens Institute of Technology’s School of Business, and Lydia Chilton, assistant professor of computer science at Columbia University’s Fu Foundation School of Engineering and Applied Science.
“The future work of journalists is great topic for our study because journalism has long been shaped by new technologies, from the printing press to the telephone to TV to the web, but guided by strong professional norms and values,” Crowston says. “We’re looking forward to understanding how this interplay shapes the use of smarter machines that can share part of the work.”
Henderson is conducting a qualitative case study of a large market local television newsroom. “Under which circumstances do local television journalists embrace technological innovations to improve their ability to inform the public, including professional storytelling across platforms?” Henderson asks.
“Journalists today are understandably concerned about how automation is used as a means of replacing human workers,” says Henderson. “Our team is approaching this research with the journalists’ best interests in mind. We want to help members of the Fourth Estate to do their best work.”
The planning grant supports the researchers as they develop a proposal for sustained research on the future of news production that may be supported by a large-scale grant from NSF. Their work would consider technologies such as natural language processing, crowdsourcing, information visualization and artificial intelligence. The planned work includes refining the project vision and theoretical framework, recruiting field sites and an advisory board, conducting pilot research to identify relevant technologies and impacts and planning of convergent research activities.
Two professors from Syracuse University’s S.I. Newhouse School of Public Communications have received a $830,958 subcontract agreement for the development of technology to detect manipulated media and combat the spread of fake news.
Stephen Masiclat, professor and director of new media management and director of the Thomas and Lisa Mandel Experimental Media Lab, and Regina Luttrell, assistant professor of public relations and director of the W2O Emerging Insights Lab, will work to refine a theoretical framework for the creation and testing of AI algorithms that can identify manipulated media. They will collaborate with researchers from private industry and academia.
The 48-month subcontract is part of the Semantic Forensics (SemaFor) program, funded by an $11.9 million Defense Advanced Research Projects Agency contract with PAR Government Systems Corp. The program seeks to create a system for automatic detection, attribution and characterization of falsified media assets.
“The challenge of fake news and disinformation is something we as communications educators have an obligation to address,” says Newhouse Dean Mark J. Lodato. “This is a new area of research for the Newhouse School, and allows us to contribute to the ongoing national conversation about the importance of reliable, fact-based information for the health of our society. Steve and Gina are doing important work.”
Masiclat and Luttrell have already built a preliminary theoretical framework consisting of an eight-dimensional analysis, and will work with researchers to test and refine their ideas.
They will create large data sets—a massive archive of both real and fake news stories based on their theoretical framework—that will train and validate AI algorithms. “Over the next four years we will evaluate various aspects of our proposed ‘theory of semantic consistency’ that can be used to create and test AI algorithms that detect key flaws,” Masiclat says. “This will allow us to develop a method for separating reliable journalism from deliberate misinformation.”
Wider access to automated manipulation technologies, coupled with the ease of sharing provided by social media platforms, has increased the threat posed by manipulated media, according to DARPA.
“This work signals Newhouse’s commitment to preserving the First Amendment and addressing the impact misinformation spread across social media has on society,” Luttrell says. “The proliferation of fake news over the past few years has caused numerous problems. Grappling with the many questions plaguing the role of truth and trust in news media, social media and society is paramount. It’s our intention that this research will help detect and combat disinformation.”
Masiclat and Luttrell will form a team of doctoral student researchers, based in Newhouse’s Experimental Media and W2O Emerging Insights Labs, to assist with the research.
Assistant Research Professor,
Mindfulness-based interventions are an increasingly popular approach to help diverse groups of professionals, including teachers, nurses, active duty military, and veterans, manage stress and professional burnout, while simultaneously improving focus and empathy. We wanted to test whether using a mindfulness-based intervention would help reduce teacher attrition, which is a nationwide problem. Novice teachers leave the profession at alarming rates. In some districts, over thirty percent of teachers quit within their first few years.
Although mindfulness-based interventions work, getting individuals to stick to the individual and group training sessions is difficult because of the time and travel commitments. Mindfulness-based interventions also have trouble scaling because of the lack of qualified instructors. Our plan is to address the challenges associated with mindfulness interventions by supporting individual and group mindfulness sessions with virtual reality, making it easier for teachers to participate remotely. With virtual reality, we can provide a sense of connection associated with being in a group setting while cutting out the travel time. Our goal is to increase participation in the program and ultimately reduce teacher attrition by giving them the tools they need to manage stress in a healthy manner.
This study has received a 2019 CUSE Grant.
Summary: Goal: The purpose of the study is to examine whether “myths and facts” message variations presented by two different sponsors of the message will make a difference in correcting the misconceptions about vaping among US young adults and preventing them from initiating vaping. With this goal in mind, the current research will test different versions of advocacy communications that debunk pervasive myths about vaping on social media.
Method: In two experiments, the current project examines the interactive effects of “myths and facts” message variations and the sponsors of advocacy message on correcting misconceptions about e-cigarette use and preventing the use of e-cigarettes among young adults.
Rationale: A priority area of the proposed research project focuses on health communication to build a healthier and equitable community. The effort to create a healthy community via tobacco and e-cigarette control has often been challenged by various stakeholders that call for evidence-based regulatory moves, as well as the inclusion of diverse stakeholders that are involved and might be affected. The underlying assumption of this research is that effective anti-vaping advocacy messages targeting today’s generation must be inclusive as well as balanced in argumentation.
This study has received a 2019 CUSE Grant.
The ability to measure audiences during television commercial breaks versus the overall program has created a new challenge for broadcasters. Advertising revenues provide the foundation of a networks ability to invest in programming, including their news product. The ability to maintain audiences during commercial breaks increases the revenue potential and helps maintain a network’s ability to produce independent journalism. With high commercial clutter currently, viewership declines during commercial breaks is high, reducing the amount of revenue network’s earn. Accurate estimation of the extent to which viewership drops when a commercial is presented can have many benefits:
Artificial Neural Network algorithms (ANNs) have been applied to many predictive and forecasting problems and often outperform traditional regression tasks. Recent developments in Deep Learning algorithms have found application in consumer devices, addressing difficult pattern recognition problems that arise in image processing and speech recognition. The proposed work will apply such algorithms to the prediction of reduction in commercial viewership.
Professors Beth Egan and Fiona Chew of the Newhouse School, and Chilukuri Mohan of the College of Engineering and Computer Science, combine expertise from advertising, media studies and machine learning. Much of the research data provided by Comscore.
This study has received a 2019 CUSE Grant.