Lifehacker: How to Filter Spotify Playlists by Genre or Mood

Lifehacker: How to Filter Spotify Playlists by Genre or Mood. “Odds are good that your ‘Liked Songs’ playlist on Spotify is a mishmash of genres and artists that don’t exactly flow together…. Thankfully, Spotify is adding a new way to filter your Liked Songs playlist via genre and mood tags, meaning you can temporarily pare down your collection to only the songs that fit the vibe you’re after.”

Variety: This Website Creates Spotify & Apple Music Playlists Based on Your Local Weather

Variety: This Website Creates Spotify & Apple Music Playlists Based on Your Local Weather. “Electronica musician Tycho launched a clever promotional website for his new album ‘Weather’ this week: Visitors of Tycho’s website can use a web app to generate a playlist based on their local weather.” Love the idea, but when I tried it, it seemed to hang on saving my playlist to Spotify. Hope it works better for you.

Quartz: You can catch a mood from watching YouTube videos

Quartz: You can catch a mood from watching YouTube videos. “A new study in the journal Social Psychological and Personality Science is the first to measure the effects of YouTube videos on viewers’ emotional state, according to its authors, psychologists Hannes Rosenbusch, Anthony Evans, and Marcel Zeelenberg from Tilburg University in the Netherlands. Previous studies have examined emotional contagion in text-based platforms like Twitter and Facebook, noting that feelings move online from one person to another just as they do in physical environments.”

PLOS: Under the Weather? How social media sentiments reflect weather patterns

PLOS: Under the Weather? How social media sentiments reflect weather patterns. “Grey skies getting you down? Research suggests that weather may impact our emotional state. But in a new PLOS ONE study, Patrick Baylis from the University of British Columbia, Nick Obradovich from MIT, and colleagues wanted to find out if specific weather conditions are associated with the positive or negative feelings expressed via social media. The researchers gathered 2.4 billion posts from Facebook and 1.1 billion from Twitter between 2009 and 2016. They used a categorization tool to analyze the sentiment for each post based on its positive and negative keywords. They also examined weather data for the location and date of each post to look for any associations.”