Researchers at Concordia’s Gina Cody School of Engineering and Computer Science have developed a new approach to identifying fake news. And they say it will be able to find hidden patterns that reveal whether a particular item is likely fake or not.

The model, called SmoothDetector, integrates a probabilistic algorithm with a deep neural network. It’s designed to capture the uncertainties and key patterns in the shared latent representations of texts and images in a multimodal setting. The model uses annotated text and image data from the United States–based social media platform X and the China-based Weibo to learn. The researchers are currently looking into ways to eventually incorporate functionalities to detect fake audio and video content as well, leveraging every medium to counter misinformation.

The project holds the potential to create numerous jobs and positions the region at the forefront of new energy production.

Japan has five potential consumer segments for Community-Supported Agriculture (CSA), with “Sustainable Food Seekers” showing the highest interest—as shown by scientists from Institute of Science Tokyo (Science Tokyo). Unlike other countries, “Food Education and Learning Opportunities” and “Contribution to Environmental and Social Issues” majorly influenced Japanese consumers’ intentions to participate in CSA. These findings could help CSA organizations, policymakers, and producers develop tailored strategies to promote CSA participation in Japan.