Listening to Music while Sheltering in Place

The world is, to varying degrees, sheltering-in-place during this global coronavirus pandemic. Starting in March, the pandemic started to affect me personally: 

  • I started working from home on March 6th. 
  • Governor Gavin Newsom announced on March 11 that any gatherings over 250 people were strongly discouraged, effectively cancelling all concerts for the month of March. 
  • On March 16th, the mayor of San Francisco along with several other counties in the area, announced a shelter-in-place order. 

Ever since then, I’ve been at home. Given all these changes in my life, I was curious what new patterns I might see in my music listening habits. 

With large gatherings prohibited, I went to my last concert on March 7th. With gatherings increasingly cancelled nationwide, and touring musicians postponing and cancelling events, March 27th, Beatport hosted the first livestream festival, “ReConnect. A Global Music Series”. Many more followed. 

Industry-wide studies and data analysis have attempted to unpack various trends in the pandemic’s influence on the music industry. Analytics startup Chartmetric is digging into genre-based listening, geographical listening habits, and Billboard and Nielsen conducting a periodic entertainment tracker survey.

Because I’m me, and I have so much data about my music listening patterns, I wanted to explore what trends might be emerging in my personal habits. I analyzed the months March, April, and May during 2020, and in some cases compared that period against the same period in 2019, 2018, and 2017. The screenshots of data visualizations in this blog post represent data points from May 15th, so it is an incomplete analysis and comparison, given that May in 2020 is not yet complete. 

Looking at my listening habits during this time period, with key dates highlighted, it’s clear that the very beginning of the crisis didn’t have much of an effect on my listening behavior. However, after the shelter-in-place order, the amount of time I spent listening to music increased. After that increase it’s remained fairly steady.

Screenshot of an area chart depicting listening duration ranging from 100 minutes with a couple spikes of 500 minutes but hovering around a max of 250 minutes per day for much of january and february, then starting in march a new range from about 250 to 450 minutes per day, with a couple outliers of nearly 700 minutes of listening activity, and a couple outliers with only a 90 minutes of listening activity.

Key dates such as the first case in the United States, the first case in California, and the first case in the Bay Area are highlighted along with other pandemic-relevant dates.

Listening behavior during March, April, and May over time

When I started my analysis, I looked at my basic listening count from traditional music listening sources. I use Last.fm to scrobble my listening behavior in iTunes, Spotify, and the web from sites like YouTube, SoundCloud, Bandcamp, Hype Machine, and more. 

Chart depicting 2700 total listens for 2017, 2000 total listens for 2018, and 2300 total listens for 2019 during March, April, and May, compared to 3000 total listens in that same period in 2020.

If you just look at 2018 to 2020, it seems like my listening habits are trending upward, maybe with a culmination in 2020. But comparing against 2017, it isn’t much of a difference. I listened to 25% fewer tracks in 2018 compared with 2017, 19% more tracks in 2019 compared with 2018, and 25% more tracks in 2020 compared with 2019. 

Chart depicting total weekday listens during March, April, and May during 2017, 2018, 2019, and 2020 with total weekend listens during the same time. 2017 shows roughly 2400 listens on weekdays and 200ish for 2017, 2000 weekday listens vs 100 weekend listens for 2018, 2100 weekday listens vs 300 weekend listens in 2019, and 2500 weekday listens vs 200 weekend listens in 2020

If I break that down by when I was listening by comparing my weekend and weekday listening habits from the previous 3 years to now, there’s still perhaps a bit of an increase, but nothing much. 

With just the data points from Last.fm, there aren’t really any notable patterns. But number of tracks listened to on Spotify, SoundCloud, YouTube, or iTunes provides an incomplete perspective of my listening habits. If I expand the data I’m analyzing to include other types of listening—concerts attended and livestreams watched—and change the data point that I’m analyzing to the amount of time that I spend listening, instead of the number of tracks that I’ve listened to, it gets a bit more interesting. 

Chart shows roughly 12000 minutes spent listening in 2017, 10000 in 2018, 12000 in 2019, and 22000 in 2020While the number of tracks I listened to from 2019 to 2020 increased only 25%, the amount of time I spent listening to music increased by 74%, a full 150 hours more than the previous year during this time period. And May isn’t even over yet! 

It’s worth briefly noting that I’m estimating, rather than directly calculating, the amount of time spent listening to music tracks and attending live music events. To make this calculation, I’m using an estimate of 3 hours for each concert attended, 4 hours for each DJ set attended, 8 hours for each festival attended, and an estimate of 4 minutes for each track listened to, based on the average of all the tracks I’ve purchased over the past two years. Livestreamed sets are easier to track, but some of those are estimates as well because I didn’t start keeping track until the end of April.

I spent an extra 150 hours listening to music this year during this time—but when was I spending this time listening? If I break down the amount of time I spent listening by weekend compared with weekdays, it’s obvious:

Chart depicts 10000 weekday minutes and 5000 weekend minutes spent listening in 2017, 9500 weekday minutes and 4500 weekend minutes in 2018, 14000 weekday minutes and 2000 weekend minutes in 2019, and 12000 weekday minutes and 13000 weekend minutes in 2020

Before shelter-in-place, I’d spend most of my weekends outside, hanging out with friends, or attending concerts, DJ sets, and the occasional day party. Now that I’m spending my weekends largely inside and at home, coupled with the number of livestreaming festivals, I’m spending much more of that time listening to music. 

I was curious if perhaps working from home might reveal new weekday listening habits too, but the pattern remains fairly consistent. I also haven’t worked from home for an extended period before, so I don’t have a baseline to compare it with. 

It’s clear that weekends are when I’m doing most of my new listening, and that this new listening likely isn’t coming from my traditional listening habits. If I split the amount of time that I spend listening to music by the type of listening that I’m doing, the source of the added time spent listening is clear.

Depicts 11000 minutes of track listens and 1000 minutes of time spent at concerts in 2017, 8000 minutes spent listening to music tracks and 2000 minutes spent at concerts in 2018, 10000 minutes spent listening to music tracks and 3000 minutes spent at concerts in 2019, and 12000 minutes spent listening to music tracks and 9000 minutes listening to livestreams, with a sliver of 120 minutes spent at a single concert in 2020

Hello, livestreams. If you look closely you can also spy the sliver of a concert that I attended on March 7th.

Livestreams dominate, and so does Shazam

All of the livestreams I’ve been watching have primarily been DJ sets. Ordinarily, when I’m at a DJ set, I spend a good amount of time Shazamming the tracks I’m hearing. I want to identify the tracks that I’m enjoying so much on the dancefloor so I can track them down, buy them, and dig into the back catalog of those artists. 

So I requested my Shazam data to see what’s happening now that I’m home, with unlimited, shameless, and convenient access to Shazam.

For the time period that I have Shazam data for, the correlation of Shazam activity to number of livestreams watched is fairly consistent at roughly 10 successful Shazams per livestream.  

Chart details largely duplicated in surrounding text, but of note is a spike of 6 livestreams with only 30 or so songs shazammed, while the next few weeks show a fairly tight interlock of shazam activity with number of livestreams

Given the correlation of Shazam data, as well as the continued focus on watching DJ sets, I wanted to explore my artist discovery statistics as well. Especially when it seemed like my listening activity hadn’t shifted much, I was betting that my artist discovery statistics have been increasing during this time. If I look at just the past few years, there seems to be a direct increase during this time period. 

Chart depicts 260ish artists discovered in March, April, and May of 2018, 280 discovered in 2019, and 360 discovered in 2020Chart depicts 260ish artists discovered in March, April, and May of 2018, 280 discovered in 2019, and 360 discovered in 2020. Second chart shows the same data but adds 2017, with 390 artists discovered

However, after I add 2017 into the list as well, the pattern doesn’t seem like much of a pattern at all. Perhaps by the end of May, there will be a correlation or an outsized increase. But at least for now, the added number of livestreams I’ve been watching don’t seem to be producing an equivalently high number of artist discoveries, even though they’re elevated compared with the last two years. 

That could also be that the artists I’m discovering in the livestreams haven’t yet had a substantial effect on my non-livestream listening patterns, even if there’s 91 hours of music (and counting) in my quarandjed playlist where I store the tracks that catch my ear in a quarantine DJ set. Adding music to a playlist, of course, is not the same thing as listening to it. 

Livestreaming as concert replacement?

Shelter-in-place brought with it a slew of event cancellations and postponements. My live events calendar was severely affected. As of now, 15 concerts were affected in the following ways:

Chart depicts 6 concerts cancelled and 9 postponed

The amount of time that I spend at concerts compared with watching livestreams is also starkly different.

Chart depicts 1000 minutes spent at concerts in 2017, 2000 minutes at concerts in 2018, 2500 minutes at concerts in 2019, and 8000 minutes spent watching livestreams, with a topper of 120 minutes at a concert in 2020

I’ve spent 151 hours (and counting) watching livestreams, the rough equivalent of 50 concerts—my entire concert attendance of last year. This is almost certainly because I’m often listening to livestreams, rather than watching them happen.

Concerts require dedication—a period of time where you can’t really do anything else, a monetary investment, and travel to and from the show. Livestreams don’t have any of that, save a voluntary donation. That makes it easier to turn on a stream while I’m doing other things. While listening to a livestream, I often avoid engaging with the streaming experience. Unless the chat is a cozy few hundred folks at most, it’s a tire fire of trolls and not a pleasant experience. That, coupled with the fact that sitting on my couch watching a screen is inherently less engaging than standing in a club with music and people surrounding me, means that I’m often multitasking while livestreams are happening.

The attraction for me is that these streams are live, and they’re an event to tune into, and if you don’t, you might miss it. Because it’s live, you have the opportunity to create a shared collective experience. The chatrooms that accompany live video streams on YouTube, Twitch, and especially with Facebook’s Watch Party feature for Facebook Live videos, are what foster this shared experience. For me, it’s about that experience, so much so that I started a chat thread for Jamie xx’s 2020 Essential Mix so that my friends and I could experience and react to the set live. This personal experience is contrary to the conclusion drawn in this article on Hypebot called Our Music Consumption Habits Are Changing, But Will They Remain That Way? by Bobby Owsinski: “Given the choice, people would rather watch something than just listen.”. Given the choice, I’d rather have a shared collective experience with music rather than just sit alone on my couch and listen to it. 

Of course, with shelter-in-place, I haven’t been given a choice between attending concerts and watching livestreamed shows. It’s clear that without a choice, I’ll take whatever approximation of live music I can find.

 

My 2018 Year in Music: Data Analysis and Insights

This past year has been pretty eventful in music for me. I’ve attended a couple new festivals, seen shows while traveling, and discovered plenty of new bands. I want to examine the data available to me and contrast it with my memories of the past year.

I’ve been using Splunk to analyze my music data for the past couple years. You can learn more about what I’ve learned from that in the past in my other posts, see Reflecting on a Decade of Quantified Music Listening and Best of 2017: Newly-Discovered Music. I also wrote a blog post for the Splunk blog (I work there) about this too: 10 Years of Listens: Analyzing My Music Data with Splunk.

Comparing Spotify’s Data with Mine

Spotify released its #2018wrapped campaign recently, sharing highlights from the year of my listening data with me (and in an ad campaign, aggregate data from all the users). As someone that uses Spotify but not as my exclusive source of music listening, I was curious to compare the results with my holistic dataset that I’ve compiled in Splunk. 

Top Artists are Poolside, The Blaze, Justice, Born Ruffians, and Bob Moses. Top Songs are Beautiful Rain, For the Birds, Miss You, Faces, and Heaven. I listened for 30.473 minutes, and my top genre was Indie.

Spotify’s top artists for me were somewhat different from the results that I found from the data I gather from Last.fm and analyze with Splunk software.  Spotify and my holistic listening data agree that I listened to Poolside more than anyone else, and was also a big fan of Born Ruffians, but beyond that they differ. This is probably due to the fact that I bought music and when I’m mobile I switch my primary listening out of Spotify to song files stored on my phone. 

Table showing my top artists and their listens, Poolside with 162 listens, The Vaccines with 136, Young Fathers with 124, Born Ruffians with 102 and Mumford and Sons with 99 listens.

In addition, my top 5 songs of the year were completely different from those listed in Spotify. My holistic top 5 songs of the year were all songs that I purchased. I don’t listen to music exclusively in Spotify, and my favorites go beyond what the service can recognize.

Table showing top songs and the corresponding artist and listen count for the song. Border Girl by Young Fathers with 35 was first, followed by Era by Hubert Kirchner with 32, Naive by the xx with 29, Sun (Viceroy Remix) by Two Door Cinema Club with 27 and There Will Be Time by Mumford & Sons with Baaba Maal also with 27 listens.

Spotify identified that I’ve listened to 30,473 minutes of music, but I can’t make a similarly reliable calculation with my existing data because I don’t have track length data for all the music that I’ve listened to. I can calculate the number of track listens so far this year, and based on that, make an approximation based on the track length data that I do have from my iTunes library. The minute calculation I can make indicates that I’ve so far spent 21,577 minutes listening to 3,878 of the 10,301 total listens I’ve accumulated so far this year (Numbers to change literally as this post is being written).

Screen capture showing total listens of 10,301 and total minutes listened to itunes library songs as 21,577 minutes.

I’m similarly lacking data allowing me to determine my top genre of the year, but Indie is a pretty reliable genre for my taste. 

Other Insights from 2018

I was able to calculate my Top 10 artists, songs, and albums of the year, and drill down on the top 10 artists to see additional data about them (if it existed) in my iTunes library, like other tracks, the date it was added, as well as the kind of file (helping me identify if it was purchased or not), and the length of the track.

Screen capture displaying top 10 artists, top 10 songs, top 10 albums of the year, with the artist Hubert Kirchner selected in the top 10 song list, with additional metadata about songs by Hubert Kirchner listed in a table below the top 10 lists, showing 3 songs by Hubert Kirchner along with the album, genre, rating, date_added, Kind, and track_length for the songs. Other highlights described in text.

There are quite a few common threads across the top 10 artists, songs, and albums, with Poolside, Young Fathers, Gilligan Moss, The Vaccines, and Justice making consistent appearances. The top 10 songs display obsessions with particular songs that outweigh an aggregate popularity for the entire album, leading other songs to be the top albums of the year.

Interestingly, the Polo & Pan album makes my top 10 albums while they don’t make it to my top 10 artist or song lists. This is also true for the album Dancehall by The Blaze. I’m not much of an album listener usually, but I know I listened to those albums several times.

The top 10 song list is more dominated by specific songs that caught my attention, and the top 10 artists neatly reflect both lists. The artists that have a bit more of a back catalog also reveal themselves, given that Born Ruffians managed to crack the top 10 despite not having any songs or albums make the top 10 lists, and Hey Rosetta! makes the top artist and album lists, despite having no top songs.

Screen capture that says Songs Purchased in 2018. 285 songs.

I purchased 285 songs this year, an increase of 157 compared to the year before. I think I just bought songs more quickly after first hearing them this year, and there are even some songs missing from this list that I bought on Beatport or Bandcamp because they weren’t available in the iTunes Store. While I caved in to Spotify premium this year, I still kept up an old promise to myself to buy music (rather than acquire it without paying for it, from a library or questionable download mechanisms) now that I can afford it. 

A Year of Concerts

Screen capture of 4 single value data points, followed by 2 bar charts. Single value data points are total spent on concerts attended in 2018 ($1835.04), total concerts in 2018 (48), artists seen in concert in 2018 (116 artists), and total spent on concert tickets in 2018 ($2109). The first bar chart shows the number of concerts attended per month, 2 in January, 3 in February, 2 in March, 6 in April, 4 in May, 2 in June, 3 in July, 8 in August, 4 in September, 6 in October, 5 in November, and 3 so far in December. The last bar chart is the number of artists seen by month: 5 in Jan, 10 in Feb, 3 in March, 14 in April, 8 in May, 3 in June, 8 in July, 18 in August, 9 in Sep, 22 in Oct, 10 in Nov, 6 in December.

I’ve been to a lot of concerts so far this year. 48, to be exact. I spent a lot of money on concert tickets, both for the shows I attended this year and for shows that went on sale during 2018 (but at this point, might be happening in 2019). I often will buy tickets for multiple people, so this number isn’t very precise for my own personal ticket usage.

I managed to go to at least 2 concerts every month. By the time the year is over, I’m on track to go to 51 different shows. Based on the statistics, there are some months where I went to many more than 1 show per week, and others where I didn’t. Especially apparent are the months with festivals—February, August, and October all included festivals that I attended. 

Many of those festivals brought me to new-to-me locations, with the Noise Pop Block Party and Golden Gate Park giving me new perspectives on familiar places, and Lollapalooza after shows bringing me out to Schubas Tavern for the first time in Chicago.  

Screen capture listing venues visited for the first time in 2018, with venue, city, state, and date listed. Notable ones mentioned in text, full list of venue names: Audio, The New Parish, San Francisco Belle, Schubas Tavern, Golden Gate Park, August Hall, Noise Pop Block Party, Bergerac, Great American Music Hall, Cafe du Nord, Swedish American Hall.

If you’re reading this wondering what San Francisco Belle is, it’s a boat. That’s one of several new venues that electronic music brought me to—DJ sets on that boat as part of Goldroom and Gigamesh’s tour, plus a day party in Bergerac and a nighttime set at Audio other times throughout the year.

Some of those new venue locations brought newly-discovered music to me as well.

Screen capture showing top 20 artists discovered in 2018, sorted by count of listens, featuring a sparkline to show how frequently I listened to the artist throughout the year, and a first_discovered date. List: Gilligan Moss, The Blaze, Polo & Pan, Hubert Kirchner, Keita Sano, Jude Woodhead, Ben Böhmer, Karizma, Luxxury, SuperParka, Chris Malinchak, Mumford & Sons and Baaba Maal, Jon Hopkins, Yon Yonson,  Brandyn Burnette and dwilly, Asgeir, The Heritage Orchestra Jules Buckley and Pete Tong, Confidence Man, Bomba Estereo, and Jenn Champion.

The 20th-most-popular artist I discovered this year was Jenn Champion, who opened for We Were Promised Jetpacks at their show at the Great American Music Hall. I started writing this assuming that I hadn’t heard Jenn Champion before that night, but apparently I first discovered them on July 9, but the show wasn’t until October 9. 

As it turns out, I listened to what is now my favorite song by Jenn Champion that day in July, likely as part of a Spotify algorithm-driven playlist (judging by the listening neighbors around the same time) but it didn’t stick until I saw them play live months later. The vagaries of playlists that refresh once a week can mean fleeting discoveries that you don’t really absorb.

Screen capture showing Splunk search results of artist, track_name, and time from July 9th. Songs near Jenn Champion's song in time include Mcbaise - Le Paradis Du Cuir, Wolf Alice - Don't Delete the Kisses (Tourist Remix) and Champyons - Roaming in Paris.
Other songs I listened to that day in July

Because of how I can search for things in Splunk, I was also curious to see what others songs I heard when I first discovered Hubert Kirchner, a great house artist.

Songs listened to around the same time as I first heard Hubert Kirchner's song Era.... I listened to Dion's song Dream Lover, Deradoorian's song You Carry the Dead (Hidden Cat Remix) followed by Hubert Kirchner, then listened to Miguel's song Sure Thing, How to Dress Well with What You Wanted, then listen to Rihanna, Love on the Brain, Selena Gomez with Bad Liar, and Descendents with I'm the One. I have no idea how I got into this mix of songs.

I have really no idea what playlist I was listening to that might have led to me making jumps from Sofi Tukker, to Tanlines, to Dion, to Deradoorian, then to Hubert Kirchner, Miguel, How to Dress Well, Rihanna, Selena Gomez, and Descendents. Given that August 24th was a Friday, my best guess is perhaps that it was a Release Radar playlist, or perhaps an epic shuffle session. 

Repeat of earlier screen capture showing top 20 artists discovered in 2018. Sorted by count of listens, featuring a sparkline to show how frequently I listened to the artist throughout the year, and a first_discovered date. List: Gilligan Moss, The Blaze, Polo & Pan, Hubert Kirchner, Keita Sano, Jude Woodhead, Ben Böhmer, Karizma, Luxxury, SuperParka, Chris Malinchak, Mumford & Sons and Baaba Maal, Jon Hopkins, Yon Yonson,  Brandyn Burnette and dwilly, Asgeir, The Heritage Orchestra Jules Buckley and Pete Tong, Confidence Man, Bomba Estereo, and Jenn Champion

For the top 20 bands I discovered in 2018, many of them I started listening to on Spotify, but not necessarily because of Spotify. Gilligan Moss was a discovery from a collaborative playlist shared with those that are also in a Facebook group about concert-going. I later saw them at one of the festivals I went to this year, and it even turned out that a friend knew one of the band members! Their status as my most-listened-to discovery of this year is very accurate.

 Polo & Pan was a discovery from a friend, fully brought to life with a playlist built by Polo & Pan themselves and shared on Spotify. Spent some quality time sitting in a park listening to that playlist and just enjoying life. They were at the same festival as Gilligan Moss, playing the same day, making that day a standout of my concerts this year.

Karizma was a discovery from Jamie xx’s set at Outside Lands. I tracked down the song from the set with the help of several other people on the internet (not necessarily anyone I knew) and then the song that was from the set itself wasn’t even on Spotify itself (Spotify, however, did help me discover more of the artist’s back catalog, like my other favorite song ‘Nuffin Else) Apparently I was far behind the curve hearing the song from the set, since it came out in 2017 and was featured in a Chromebook ad, but Work It Out still made me lose my mind at that set. (For the record, so did Take Me Higher, a song I did not manage to track down at all, and have so much thanks for the person that messaged me on Facebook ages later to send me the link!)

Similarly, Luxxury was a DJ I first spotted on a cruise that I went on because it featured other DJs I had heard of from college, Goldroom and Gigamesh, whom I’d discovered through remixes of songs I downloaded from mp3 blogs like The Burning Ear.

~ Finding Meaning in the Platforms ~

Many of these discoveries were deepened by Spotify, or had Spotify as a vector—through a collaborative playlist, algorithmically-generated one, or the quick back-catalog access for a new artist—but don’t rely on Spotify as a platform. I prefer to keep my music listening habits platform-adjacent. 

Spotify, SoundCloud, iTunes, Beatport and other music platforms I use help make my music experiences possible. But the artists making the music, performing live in venues that I have the privilege to live near and afford to visit, they are creating what keep my mind alive and energized.

The social platforms too, mediate the music-related experiences I’ve had, whether it’s with the people I share music and concert experiences with in a Facebook group, the people I exchange tracks and banter with in Slack channels, or those of you reading this on yet another platform. 

I like to listen to music that moves me, physically, or that arrests my mind and takes me somewhere. More now than ever I realize that musical enjoyment for me is an intense instantiation of the continuous tension-and-release pattern that exists in so many human art forms. The waves of neatness that clash and collide in a house music track, or the soaring crescendos of harmonies. 

It’s become clear to me over the years that I can’t separate my enjoyment of music from the platforms that bring me closer to it. Perhaps supporting the platforms in addition to the musical artists, performers, and venues, is just another element of contributing to a thriving music scene.

The Evolution of Music Listening

Pitchfork recently published a great longform essay on music streaming. It covered the past, history, and present of music streaming, and brought up a lot of great points. These are my reactions.

The piece discussed how “the “omnivore” is the new model for the music connoisseur, and one’s diversity of listening across the high/low spectrum is now seen as the social signal of refined taste.” It would be interesting to study how this omnivority splits across genres, age groups, and affinities. I find myself personally falling into omnivore status, as I am never able to properly define my music taste according to genre, and my musical affinities shift daily, weekly, monthly, with common themes.

Also discussed is the cost of music, whether it be licensing, royalties, or record label advances. Having to deal with the cost of music is a difficult matter. I wonder if I would have been such a voracious consumer of music if I hadn’t grown up with so many free options with the library, the radio, and later, music blogs. Now that I’m older, I make the effort to purchase music when I feel the artist deserves it, but as I distance myself (incidentally, really) from storing music on my computer, that effort becomes less important to expend.

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Autobiography through (Musical) Devices (Part Rogue)

Inspired in part by Cyborgology’s Autobiography through Devices series

Autobiography Through Devices (Part 1)

Autobiography Through Devices (Part 2)

I grew up surrounded by music. Dancing wildly in the living room to REM’s Don’t Go Back to Rockville and Rusted Root’s Ecstasy with my siblings as we were toddlers remain fond childhood memories of mine. As I grew older I kept listening to my parents’ music, including an entrenched eighties phase, and as I left Junior High, I owned a Train tape, a Cat Stevens Classics CD, and Motion City Soundtrack’s first album, I Am The Movie, among others. I shied away from the popular music of my peers in Junior High, and avoided Alkaline Trio, System of a Down, and Blink 182 (this was a mistake, I might add).

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