Reinventing TV

  • “The news has a boring problem”: Sean McLaughlin has big ideas to save TV news
    Tired of the constant, unvaried nature of today’s television newscasts, Sean McLaughlin – former anchor, reporter, and news director for various news stations – has dedicated his recent career to innovating newsrooms nationwide, going so far as to eliminate anchor roles and changing the newscast format.  Most recently, he served as the senior vice president
  • Learning from TikTok: Lessons for TV News in How #BookTok Broke Big on Social Media
    Growing up, Kayla Agnoli’s head was always buried in a book. She spent hours immersed in different worlds, captivated by different storylines. While her time was spent transporting herself through literature, her classmates couldn’t understand why she wouldn’t just watch TV.  Joining TikTok gave her a community of over 6,000 followers and 627.4k likes, where
  • How Vox uses animation to make complicated topics digestible for everyone
    With almost 12 million subscribers on YouTube, Vox has established itself as one of the most prominent video media outlets. Explainer videos such as “Why we all need subtitles now” and “Teaching in the US vs. the rest of the world” have garnered millions of views with thousands of comments.  It is no surprise that
  • Northeastern University’s Reinventing Local TV News Project kicks off a year of experimentation
    Northeastern University’s Reinventing Local TV News Project (RLTVN), supported by the Stanton Foundation, is embarking on an exciting new phase in 2024 with the hiring of four fellows who are working in new roles for television stations around the country. Building on its foundational work since 2017, the project continues its journey to revolutionize local
  • Getting started with stringr for textual analysis in R
    Manipulating characters – a.k.a. non-numerical data – is an essential skill for anyone looking to visualize or analyze text data. This tutorial will go over a few of the base R functions for manipulating strings in R, and introduce the stringr package from the tidyverse. The datasets being used are being analyzed as part of