Using big data to stop fake news
Posted on October 20, 2017Dongwon Lee, an associate professor in the College of Information Sciences and Technology, and S. Shyam Sundar, distinguished professor in the Donald P. Bellisario College of Communications, will speak on “Big Data and Fake News:
The Penn State Institute for CyberScience (ICS) is hosting the event as part of the ICS CyberScience Seminars, a series of talks on cutting-edge topics of interest to the cyberscience research community at Penn State.
Lee and Sundar will discuss their research on how machine learning may help to detect fake news—stories that are intended to deceive, such as the ones surrounding the recent “Pizzagate” conspiracy theory. Fake news is becoming epidemic; spread through social media and fake news websites, it can even be picked up by mainstream news sources.
Responding to this problem, Lee and Sundar are undertaking a multi-year investigation into the analysis, detection, and educational use of fake news. The ultimate goal is to devise effective machine learning methods for detecting this kind of misinformation.
“This problem is impacting regular citizens around the world. ‘Pizzagate’ is just a single example of how big this epidemic truly is,” said Lee. “Our efforts are to design machine-learning algorithms that will eventually detect false news and fake information in the future.”
Space is limited, so please reserve a seat at the seminar by October 30. The event includes Lee and Sundar’s talk, an extended question-and-answer session, and time to socialize. Refreshments will be served.
ICS CyberScience Seminars explore a wide range of topics. Check out the full slate of speakers for 2017-18.
Lee is an associate professor in the College of Information Sciences and Technology. From 2014 to 2017, he has also served as a program director at National Science Foundation (NSF), co-managing cybersecurity programs such as SFS and SaTC with the yearly budget of $55M. He researches broadly in Data Science, in particular, on the management of and mining in data in diverse forms including structured records, text, multimedia, social media, and Web. He is also interested in applying the human computation framework to solve data science problems, and detecting/curbing challenging online frauds using machine learning techniques.
Sundar is a distinguished professor in the Donald P. Bellisario College of Communications. He is the founder of the Media Effects Research Laboratory, a leading facility of its kind in the country. His research investigates social and psychological effects of technological elements unique to online communication, ranging from websites to newer social and personal media. In particular, his studies experimentally investigate the effects of interactivity, navigability, multi-modality, and agency (source attribution) in digital media interfaces upon online users’ thoughts, emotions, and actions.
Share
Related Posts
- Featured Researcher: Nick Tusay
- Multi-institutional team to use AI to evaluate social, behavioral science claims
- NSF invests in cyberinfrastructure institute to harness cosmic data
- Center for Immersive Experiences set to debut, serving researchers and students
- Distant Suns, Distant Worlds
- CyberScience Seminar: Researcher to discuss how AI can help people avoid adverse drug interactions
- AI could offer warnings about serious side effects of drug-drug interactions
- Taking RTKI drugs during radiotherapy may not aid survival, worsens side effects
- Cost-effective cloud research computing options now available for researchers
- Costs of natural disasters are increasing at the high end
- Model helps choose wind farm locations, predicts output
- Virus may jump species through ‘rock-and-roll’ motion with receptors
- Researchers seek to revolutionize catalyst design with machine learning
- Resilient Resumes team places third in Nittany AI Challenge
- ‘AI in Action’: Machine learning may help scientists explore deep sleep
- Clickbait Secrets Exposed! Humans and AI team up to improve clickbait detection
- Focusing computational power for more accurate, efficient weather forecasts
- How many Earth-like planets are around sun-like stars?
- Professor receives NSF grant to model cell disorder in heart
- SMH! Brains trained on e-devices may struggle to understand scientific info
- Whole genome sequencing may help officials get a handle on disease outbreaks
- New tool could reduce security analysts’ workloads by automating data triage
- Careful analysis of volcano’s plumbing system may give tips on pending eruptions
- Reducing farm greenhouse gas emissions may plant the seed for a cooler planet
- Using artificial intelligence to detect discrimination
- Four ways scholars say we can cut the chances of nasty satellite data surprises
- Game theory shows why stigmatization may not make sense in modern society
- Older adults can serve communities as engines of everyday innovation
- Pig-Pen effect: Mixing skin oil and ozone can produce a personal pollution cloud
- Researchers find genes that could help create more resilient chickens
- Despite dire predictions, levels of social support remain steady in the U.S.
- For many, friends and family, not doctors, serve as a gateway to opioid misuse
- New algorithm may help people store more pictures, share videos faster
- Head named for Ken and Mary Alice Lindquist Department of Nuclear Engineering
- Scientific evidence boosts action for activists, decreases action for scientists
- People explore options, then selectively represent good options to make difficult decisions
- Map reveals that lynching extended far beyond the deep South
- Gravitational forces in protoplanetary disks push super-Earths close to stars
- Supercomputer cluster donation helps turn high school class into climate science research lab
- Believing machines can out-do people may fuel acceptance of self-driving cars
- People more likely to trust machines than humans with their private info
- IBM donates system to Penn State to advance AI research
- ICS Seed Grants to power projects that use AI, machine learning for common good
- Penn State Berks team advances to MVP Phase of Nittany AI Challenge
- Creepy computers or people partners? Working to make AI that enhances humanity
- Sky is clearing for using AI to probe weather variability
- ‘AI will see you now’: Panel to discuss the AI revolution in health and medicine
- Privacy law scholars must address potential for nasty satellite data surprises
- Researchers take aim at hackers trying to attack high-value AI models
- Girls, economically disadvantaged less likely to get parental urging to study computers
- Seed grants awarded to projects using Twitter data
- Researchers find features that shape mechanical force during protein synthesis
- A peek at living room decor suggests how decorations vary around the world
- Interactive websites may cause antismoking messages to backfire
- Changing how government assesses risk may ease fallout from extreme financial events
- Differences in genes’ geographic origin influence mitochondrial function
- ICS Affiliate named AGU fellow
- Institute for CyberScience co-hire hunts security flaws in software