Web Science and Digital Libraries Research Group

If you have not already heard of it, NeuroPype is a great tool for developing pipelines to perform sensor data acquisition, processing, analysis, and/or display.  Its Pipeline Designer, based on the Orange application, has a well-developed drag-and-drop interface that makes it easy for anyone from students to experienced clinicians to perform biosignal data analysis.  The NeuroPype - Academic Edition is also freely available to university researchers, faculty and students for non-commercial research. Although the current NeuroPype release comes with hundreds of nodes readily available for use, they may not always provide the functionality that you desire.  Luckily, NeuroPype makes it fairly easy for developers to write and deploy their own Python-based nodes to support their biosignal processing requirements.  In this tutorial, I will take you step-by-step in creating your first NeuroPype custom node.  Getting Started You must first create an account using your school email address

A tweet on September 20, 2020 suggested that the news media was normalizing death not treating the two milestones (100,000 vs. 200,000) of COVID-19 deaths the same. If we look at the quoted tweet closer, we can see that it is a side by side of two front pages of the New York Times. The image on the left shows a full page of names of people who have died due to COVID-19 near the 100,000 milestone. This front page is from May 24, 2020. The image on the right shows a New York Times front page near the 200,000 milestone. That front page is from September 20, 2020. The milestone story is not featured on this page. However, the dates of these two newspapers are not the actual milestone dates. If we evaluate the front page of each web site for other news sources, how did they prioritize these milestones? Are they displayed prominently? How prominently? Are they ranked first? Second? How far into the page does one need to scan before they see a news article mentioning these milestone