Britt Lower's Genius Severance Easter Egg | Emmy's - Brit + Co
The long-awaited second installment of the series is on its way!| Brit + Co
by Anthony Murisco, Public Engagement Librarian We all want work-life balance. It’s beneficial to both physical and mental health. But what would you do to achieve it? That’s the conceit at the heart of the hit Apple TV+ show, Severance. Now … Continue reading →| Books, Health and History
The long-awaited second installment of the series is on its way!| Brit + Co
The year’s leader in nominations (27 overall) could walk away with, at most, 20 trophies. But given the impressive competition from “The White Lotus,” “Andor,” and “The Pitt,” should Apple’s breakout drama dominate the winners' circle or share it?| Galleries – IndieWire
Emmy-nominated casting directors celebrate the work of their peers from across 2025.| Galleries – IndieWire
2025 Emmys Predictions in Every Category include wins for "Severance," "The Studio," "Adolescence," "Hacks," "Andor" and "The Penguin."| Variety
This analysis was made possible by the mdr R package, which used data originally compiled by Sam_Badi on Reddit. The data consists of all elevator dings in the Severance episodes along with the episode number, time stamp, pitch of the ding, and the action associated. Examining the plot below, we see across all dings the G is associated with both innie and outies going to sleep, the C# is consistently associated with both innies and outies waking up. (Spoiler: There is one notable exception, a...|
This analysis was made possible by the mdr R package, which used data originally compiled by the Severance wiki. Here, we create a little sentiment profile for each episode, binning them in three minute increments and calculating the AFINN average sentiment score in each. library(tidytext)library(mdr)library(tidyverse)df <- transcripts |>mutate(timestamp_seconds =as.numeric(timestamp), bin =floor(timestamp_seconds /180) *180) |>left_join(episodes, by =c("season", "episode"))df |>mutate(id = g...|
In this analysis, I use my mdr R package, which used data originally compiled by the Severance wiki. For each episode we count the number of words each of the four main characters (Mark, Helly, Dylan, and Irving) speak for in each minute and visualize them below. Click on the tabs to switch episodes. library(tidyverse)library(tidytext)library(ggiraph)library(mdr)make_plot <-function(input) {data <- transcripts |>mutate(speaker =case_when(grepl("Cobel", speaker) ~"Cobel", speaker =="Mark W"~"M...|
This would be a game-changer.| StyleCaster
