An article covering the “Sober Curious Movement” was published in the Chicago Tribune a few weeks ago. My brother shared it with me, and I’m still thinking about it. The article discusses a “sober curious” movement in America and interviews a number of people in Chicago that have chosen to quit drinking. Apparently because they quit drinking for different reasons than alcoholism or binge drinking, they are “sober curious” instead of simply “sober”. (It’s a book too).
My brother sent it to me because I don’t drink either, which can feel like an oddity in your twenties. I quit drinking at concerts when I was 22, after I went to a concert, had one drink, and ended up fainting in between the opener and the headliner. Thinking it was just a fluke of that night, I tried again at another show a few months later, and spent the headlining set sitting down in the back of the venue to avoid fainting a second time. After that I realized that it wasn’t worth it, and never drank at a concert again.
It took longer for me to quit drinking overall, and I’d make exceptions at time for special occasions when it just felt too awkward to not drink—weddings, parties, first dates—but after awhile I decided to stop making the exceptions. It was part personal challenge, and part health-conscious decision. My body had never responded well to alcohol, what with lightheadedness or nausea following anything more than a couple drinks. By the time I was 22 I had a short list of “okay alcohols” and quantities, and by the time I was 26 I’d grown tired of bothering.
My life had shifted to involve fun activities beyond drinking, and my friends weren’t drinking-focused either. I’d be going to concerts or to the gym/the soccer pitch every other day, and drinking just didn’t fit anywhere. I’d spent time in college not drinking at various parties, where I knew I had to be fresh for studying the next day, so I knew I could still have fun without drinking. Choosing to quit drinking overall felt like a natural progression.
So where does that leave me now, and why am I still so peeved at that article? For one, it only quotes women. I like to see women quoted by journalists, but by only quoting women, the choice to be sober felt somewhat trivialized. In addition, the women’s comments were contextualized with talk of mindfulness and yoga, as though this is a choice being made by a particular type and class of woman, and no others. It also perpetuates the notion that having fun without drinking is some strange novelty. There are a lot of people out there that have fun without drinking. Indeed, as one of the women in the article points out—it’s a challenge to your confidence to go out and be all of yourself, without alcohol. But it can be that much more invigorating in that way. You get to challenge your social anxiety and actively build confidence, rather than relying on alcohol and wondering if you can talk to strangers without it at all.
I think there’s also harm in talking about sobriety distinct from alcoholism. A lot of quitting drinking is about realizing that you don’t like who you are when you drink (or after you drink). The recent essay about the Joe Beef restaurateurs makes this clear. Some people have the lifestyles, genetic predisposition, or experienced traumas that escalate their alcohol consumption to recognizable alcoholism. Others have a dependence on it that they dislike, even if others don’t see it as an issue (as one of the women interviewed in the Chicago Tribune article mentions). It’s more than okay to share that common understanding, rather than separate ourselves into different groups, “the sober curious” and “the fully sober due to addiction”. That’s harmful. Indeed, the sober curious meetup in Chicago also includes “young women in recovery”. They get it.
Often, quitting drinking feels like a social choice more than a personal choice. It feels that way largely due to the fact that there often aren’t that many sober social activities out there. It’s hard to stay out late with friends sober when the only places open late are bars. It’s harder to choose yourself over alcohol, when it can often mean isolating yourself from friends. So while I struggle with the rhetoric and the patronizing presentation of the “sober curious” movement, I absolutely support it as an overall societal direction. Here’s to more late-night diners, pastry places like Mission Pie, and sober pop-ups like Brillig Dry Bar that help us sober people stay up late and out with friends.
This past year I added some additional datasets to the Splunk environment I use to analyze my music: information about tickets that I’ve purchased, and information about upcoming concerts.
Ticket purchase analysis
I started keeping track of the tickets that I’ve purchased over the years, which gave me good insights about ticket fees associated with specific ticket sites and concert promoters.
Based on the data that I’ve accumulated so far, Ticketmaster doesn’t have the highest fees for concert tickets. Instead, Live Nation does. This distinction is relatively meaningless when you realize they’ve been the same company since 2010.
However, the ticket site isn’t the strongest indicator of fees, so I decided to split the data further by promoter to identify if specific promoters had higher fees than others.
Based on that data you can see that the one show I went to promoted by AT&T had fee percentages of nearly 37%, and that shows promoted by Live Nation (through their evolution and purchase by Ticketmaster) also had fees around 26%. Shows promoted by independent venues have somewhat higher fees than others, hovering around 25% for 1015 Folsom and Mezzanine, but shows promoted by organizations whose only purpose is promotion tend to have slightly lower fees, such as select entertainment with 18%, Popscene with 16.67%, and KC Turner Presents with 15.57%.
I realized I might want to refine this, so I recalculated this data, limiting it to promoters from which I’ve bought at least two tickets.
It’s a much more even spread in this case, ranging from 25% to 11% in fees. However, you can see that the same patterns exist— for the shows I’ve bought tickets to, the independent venues average 22-25% in fees, while dedicated independent promoters are 16% or less in added fees, with corporate promoters like Another Planet, JAM, and Goldenvoice filling the middle of the data ranging from 18% to 22%.
I also attempted to determine how I’m discovering concerts. This data is entirely reliant on my memory, with no other data to back it up, but it’s pretty fascinating to track.
It’s clear that Songkick has become a vital service in my concert-going planning, helping me discover 46 shows, and friends and email newsletters from venues helping me stay in the know as well for 19 and 14 shows respectively. Social media contributes as well, with a Facebook community (raptors) and Instagram making appearances with 10 and 2 discoveries respectively.
Concert data from Songkick
Because Songkick is so vital to my concert discovery, I wanted to amplify the information I get from the service. In addition to tracking artists on the site, I wanted to proactively gather information about artists coming to the SF Bay Area and compare that with my listening habits. To do this, I wrote a Songkick alert action in Python to run in Splunk.
Songkick does an excellent job for the artists that I’m already tracking, but there are some artists that I might have just recently discovered but am not yet tracking. To reduce the likelihood of missing fast-approaching concerts for these newly-discovered artists, I set up an alert to look for concerts for artists that I’ve discovered this year and have listened to at least 5 times.
To make sure I’m also catching other artists I care about, I use another alert to call the Songkick API for every artist that is above a calculated threshold. That threshold is based on the average listens for all artists that I’ve seen live, so this search helps me catch approaching concerts for my historical favorite artists.
Also to be honest, I also did this largely so that I could learn how to write an alert action in Splunk software. Alert actions are essentially bits of custom python code that you can dispatch with the results of a search in Splunk. The two alert examples I gave are both saved searches that run every day and update an index. I built a dashboard to visualize the results.
I wanted to use log data to confirm which artists were being sent to Songkick with my API request, even if no events were returned. To do this I added a logging statement in my Python code for the alert action, and then visualized the log statements (with the help of a lookup to match the artist_mbid with the artist name) to display the artists that had no upcoming concerts at all, or had no SF concerts.
For those artists without concerts in the San Francisco Bay Area, I wanted to know where they were going instead, so that I could identify possible travel locations for the future.
It seems like Paris is the place to be for several of these artists—there might be a festival that LAUER, Max Cooper, George Fitzgerald, and Gerald Toto are all playing at, or they just happen to all be visiting that city on their tours.
I’m planning to publish a more detailed blog post about the alert action code in the future on the Splunk blogs site, but until then I’ll be off looking up concert tickets to these upcoming shows….
I moved to San Francisco from the Midwest a few years ago, and I’d been missing a strong sense of history since then. I’ve been to a few events in an attempt to learn more about my new home, such as a Dolores Park history day, or a history-relevant event in the Mission as part of Litcrawl, but I struggled to absorb a history for the city that went beyond “gold rush, earthquake, tech boom, bust, boom”.
But last week I was at the library and saw an event that was being held in conjunction with the display of the Bay Model throughout SF public libraries and Take Part SF, called Vanished Waters. It was about Mission Bay history so I skipped my regular workout to attend. It was well worth it!
Vanished Waters is also a book, so that was the loose structure that the talk revolved around, and was given by Chris Carlsson, an expert on San Francisco history and an engaging speaker. He co-founded Shaping SF, helping to maintain a digital archive of the city’s past.
SoMA was really hilly and marshy, but then some dude with a steam shovel was like “sup let me move that sand for you” and also “sup let me help you fill in this lot that you bought that is literally just water”. That’s my paraphrasing, but the actual details are to be read on Found SF.
The whole idea to fill the San Francisco Bay in is hard to imagine now because it’s not polluted, but if it was a stinky polluted putrid mess full of garbage it’s easier to imagine it being a good idea. (The whole idea to fill in the Bay is why the SF Bay Model was built).
However, my favorite part of the talk was when Carlsson discussed using this history to inform our present and future decisions. He pointed out that there is a lot of rhetoric in San Francisco about how to build more housing to manage the growth of the city, and what kinds of development is best suited to accommodating all of the people that move here.
However, there’s not much rhetoric (if any) about staging a managed retreat from climate change. San Francisco is a coastal city, built on top of marshland, sand dunes, or literal land fill. What happens when the sea level begins to rise, or more volatile weather patterns cause bigger storms and potential flooding?
I realized after this talk that some city dwellers love to judge southeastern coastal city residents that build or rebuild homes in the path of hurricanes or immediate climate change threats, and yet, New York City and San Francisco are both at high risk from sea level rise.
It’s fascinating to explore what the city used to look like less than 200 years ago, and imagine what it might look like in 2057 in the face of climate change. I lost nearly an hour clicking around the maps on David Rumsey’s website (recommended by Carlsson).
Disclaimer: I’m a Splunk employee, and I’m not a Cribl customer, but I do know the founders (including the author of the blog post). I figured I’d write this exploration up here rather than as an exceedingly-long Twitter thread. My reactions are all to the content of the blog post, not actual use of the product.
If I’m reading this blog post from Cribl correctly, their product makes it easy to enrich events with metadata at ingest-time. This is relevant/exciting for me because when I’m ingesting music data for my side project, I’m only ever getting the initial slice that’s available from a specific REST endpoint or in a file.
I’ve been identifying and collecting additional data sources that I want to enrich my dataset with, but doing so requires extra calls to other endpoints in the same API, or other web services, which means I then need to figure out where I want to store all of that data.
It quickly turns into an architectural and conceptual headache that I delay handling, because I know I’d either be dumping a lot of data into lookups / the KV store, or having to seriously level up my Python skills and do data processing and enrichment in my code before sending it to Splunk Enterprise.
As a specific example, I use the Last.fm getRecentTracks endpoint to send my listening data to Splunk Enterprise, but to enrich that data with additional metadata like track duration, or album release date, I’d have to hit 2 additional endpoints (track.getInfo and album.getInfo, respectively).
Deciding when in the data processing pipeline to hit those endpoints, how to hit them, and where to store that information to enrich my events has been a struggle that I’ve been avoiding dealing with.
There is an advantage to collecting the metadata once and storing it in a lookup or the KV store, because the metadata is relatively static. That means that it is relatively straightforward to call an endpoint, collect the data, and store it somewhere for when I need it. That means that I then have the added flexibility to enrich my events with extra data at search time when I want to, but not otherwise.
However, this means that I’m having to make conceptual decisions at multiple points—when collecting the data, when deciding what format to store it in, and where, and when I am enriching events at search time. It’s a lot of added complexity, but this type of enrichment doesn’t affect the size of my originally-indexed events, though it might end up being indexed separately instead.
But with Cribl’s solution, I’d be making that choice once. That does mean I lose potential flexibility about when and which events I can enrich with the data, but it also means that the conceptual decisions aren’t something I have to belabor. I can enrich my listening data at ingest-time with additional metadata about the album, artist, and track, then send it on to be indexed. Then when I’m searching and want to perform additional work with the metadata, it’s all right there with my events already.
This is a convenient, if imperfect, solution for my use case. But my use case is pretty basic: enrich events with static information that might be shared across many events. That’s a use case with a lot of potential solutions. I could use this approach if I didn’t care about reducing the amount of data that I indexed to the bare minimum, and focused instead on convenience and context for my data ingestion, allowing me to save time when searching my data.
This solution is much more exciting for use cases other than mine, where you’re enriching events with dynamic information that is relevant and true for specific events at index-time. The blog post includes an example of this, combining the web access logs with context from proxy logs, making the time-to-discovery for investigations that use web access logs shorter.
There is flexibility in combining data at search time, but there is complexity with that approach as well. Cribl shows that there is convenience in creating that context at index-time as well.
The annual Noise Pop music festival starts this week, and I purchased a badge this year, which means I get to go to any show that’s a part of the festival without buying a dedicated ticket.
That means I have a lot of choices to make this week! I decided to use data to assess (and validate) some of the harder choices I needed to make, so I built a dashboard, “Who Should I See?” to help me out.
First off, the Wednesday night show. Albert Hammond, Jr. of the Strokes is playing, but more people are talking about the Baths show the same night. Maybe I should go see Baths instead?
If I’m making my decisions purely based on listen count, it’s clear that I’m making the right choice to see Albert Hammond, Jr. It is telling, though, that I’ve listened to Baths more recently than him, which might have contributed to my indecision.
The other night I’m having a tough time deciding about is Saturday night. Beirut is playing, but across the Bay in Oakland. Two other interesting artists are playing closer to home, Bob Mould and River Whyless. I wouldn’t normally care about this so much, but I know my Friday night shows will keep me busy and leave me pretty tired. So which artist should I go see?
It’s pretty clear that I’m making the right choice to go see Beirut, especially given my recent renewed interest thanks to their new album.
I also wanted to be able to consider if I should see a band at all! This isn’t as relevant this week thanks to the Noise Pop badge, but it currently evaluates if the number of listens I have for an artist exceeds the threshold that I calculate based on the total number of listens for all artists that I’ve seen live in concert. To do this, I’m evaluating whether or not an artist has more listens than the threshold. If they do, I return advice to “Go to the concert!” but if they don’t, I recommend “Only if it’s cheap, yo.”
Because I don’t need to make this decision for Noise Pop artists, I picked a few that I’ve been wanting to see lately: Lane 8, Luttrell, and The Rapture.
While my interest in Lane 8 has spiked recently, there still aren’t enough cumulative listens to put them over the threshold. Same for Luttrell. However, The Rapture has enough to put me over the threshold (likely due to the fact that I’ve been listening to them for over 10 years), so I should go to the concert! I’m going to see The Rapture in May, so I am gleefully obeying my eval statement!
On a more digressive note, it’s clear to me that this evaluation needs some refinement to actually reflect my true concert-going sentiments. Currently, the threshold averages all the listens for all artists that I’ve seen live. It doesn’t restrict that average to consider only the listens that occur before seeing an artist live, which might make it more accurate. That calculation would also be fairly complex, given that it would need to account for artists that I’ve seen multiple times.
However, number of listens over time doesn’t alone reflect interest in going to a concert. It might be useful to also consider time spent listening, beyond count of listens for an artist. This is especially relevant when considering electronic music, or DJ sets, because I might only have 4 listen counts for an artist, but if that comprises 8 hours of DJ sets by that artist that I’ve listened to, that is a pretty strong signal that I would likely enjoy seeing that artist perform live.
I thought that I’d need to get direct access to the MusicBrainz database in order to get metadata like that, but it turns out that the Last.fm API makes some available through their track.getInfo endpoint, so I just found a new project! In the meantime I am able to at least calculate duration for tracks that exist in my iTunes library.
I now have a new avenue to explore with this project, collecting that data and refining this calculation. Reach out on Twitter to let me know what you might consider adding to this calculation to craft a data-driven concert-going decision-making dashboard.
If you’re interested in becoming a technical writer, or are new to the field and want to deepen your skills and awareness of the field, this blog post is for you.
What do technical writers actually do?
Technical writers can do a lot of different things! People in technical writing write how-to documentation, craft API reference documentation, create tutorials, even provide user-facing text strings to engineers.
Ultimately, technical writers:
Research to learn more about what they are documenting.
Perform testing to verify that their documentation is accurate and validate assumptions about the product.
Write words that help readers achieve specific learning objectives and that capture what the writer has learned in the research and testing processes.
Initiate reviews with engineers, product managers, user experience designers, quality assurance testers, and others to validate the accuracy, relevancy, and utility of the content.
Advocate for the customer or whoever uses the product or service being documented.
The people reading what technical writers have produced could be using software they’ve purchased from your company, evaluating a product or service they are considering purchasing, undergoing a required process controlled by your organization, writing code that interfaces with your services, configuring or installing modifying hardware produced by your company, or even reviewing the documentation for compliance and certification purposes. Your goal, if you choose to accept it, is to help them get the information they need and get back to work as soon as possible.
Identify what you want from your career
Some general career-assessment tips:
Identify what motivates you and what challenges you.
Identify what type of team environment you want. These are loose descriptions of types of team environments that are out there:
A large highly-collaborative team with lots of interaction
A distributed team that is available for questions and brainstorming as needed, but largely everyone is working on their own thing.
A small team that collaborates as needed.
A team of one, it’s just you, you are the team.
Is technical writing a good fit for you?
Do you enjoy explaining things to other people?
Do people frequently ask you to help explain something to them?
Do people frequently ask you to help them revise content for them?
Do you care or enjoy thinking about how to communicate information?
Do you identify when things are inconsistent or unclear and ask people to fix it? (Such as in a UI implementation, or when reviewing a pull request)
Do you enjoy problem-solving and communication?
Do you like synthesizing information from disparate sources, from people to product to code to internal documentation?
Do you enjoy writing?
My background and introduction to technical writing
I started in technical support. In college I worked in desktop support for the university, wandering around campus or in the IT shop, repairing printers, recovering data from dying hard drives, running virus scans, and updating software. After graduation I eventually found a temp job working phone support with University of Michigan, managing to turn that position into a full-time permanent role and taking on two different queues of calls and emails. However, after a year I realized that was super exhausting to me. I couldn’t handle being “on” all day, and I found myself enjoying writing the knowledge base articles that would record solutions for common customer calls. I wrote fifty of them by the time I discovered a posting for an associate-level documentation specialist.
I managed to get that position, and transferred over to work with a fantastic mentor that taught me a ton about writing and communicating. After a few years in that position, writing everything from communication plans (and the accompanying communications), technical documentation, as well as a couple video scripts, I chose to move to California. With that came another set of job hunting, and realizing that there are a lot of different job titles that technical writing can fall under: UI writer, UI copywriter, technical writer, documentation specialist, information developer… I set up job alerts, and ended up applying, interviewing, and accepting an offer for a technical writing position at Splunk. I’ve been at Splunk for several years now, and recently returned to the documentation team after spending nearly a year working in product management.
Where people commonly go to technical writing from
Technical writers can get their start anywhere! Some people become technical writers right out of college, but others transition to it after their career has already begun.
As a technical writer, your college degrees doesn’t need to be in technical writing, or even a technical-specific or writing-specific field. I studied international studies, and I’ve worked with colleagues that have studied astronomy, music, or statistics. Others have computer science or technical communication degrees, but it’s not a requirement.
For people transitioning from other careers, here are some common starting careers:
That’s obviously a short list, but again if you care about the user and communication in your current role, that background will help you immensely in a technical writing position.
Prepare for a technical writing interview
Prepare a portfolio of writing samples
Every hiring manager wants to see a collection of writing samples that demonstrate how you write. If you don’t work in technical writing yet, you might not have any. Instead, you can use:
How-to processes you’ve written. For example, instructions for performing a code review or a design review.
A blog post about a technical topic that you are familiar with. For example, a post about a newly-discovered functionality in CSS.
Basic task documentation about software that you use. For example, write up a sample task for how to create a greeting card in Hallmark Card Studio.
Your portfolio of writing samples demonstrates to hiring managers that you have writing skills, but also that you consider how you organize content, how you write for a specific audience, and the level of detail that you include based on that audience. The samples that you use don’t have to be hosted on a personal website and branded accordingly. The important thing is to have something to show to hiring managers.
Depending on the interviewer, you might perform a writing exercise in-person or as part of the screening process. If you don’t have examples of writing like this, that’s a good reason to track down some open source projects in need of some documentation assistance!
Learn about the organization and documentation
Going in to the interview, make sure you are familiar with the organization and its documentation.
Read up about the organization or company that you are interviewing with. If you can, track down a mission statement for the organization.
Find the different types of documentation available online, if possible, and read through it to get a feel for what the team might be publishing.
If the organization provides a service or product that you’re able to start using right away, do that!
All of these steps help you better understand how the organization works, what the team you might be working on is producing, and demonstrates to the interviewer that you are motivated to understand what the role and the organization are about. Not to mention, this makes it clear that you have some of the necessary skills a technical writer needs when it comes to information-gathering.
Questions you might want to ask
Find out some basic team characteristics:
How many other technical writers are at the organization?
What org are the technical writers part of?
Is there a central documentation team or are the writers scattered across the organization?
How distributed is the documentation team and/or the employees at the organization?
Learn about the documentation process and structure:
What does the information-development process look like for the documentation? Does it follow semi-Agile methods and get written and researched as part of the development team, or does information creation follow a more waterfall style, where writers are delivered a finished product and expected to document it? Or is it something else entirely?
Are there editors or a style guide?
Do the writers work directly with the teams developing the product or service?
What sort of content management system (CMS) is in use? Is it structured authoring? A static-site generator reliant on documentation files written in markdown stored next to the code? A wiki? Something else?
Find out how valuable documentation is to the organization:
Do engineers consider documentation vital to the success of the product or service?
Do product managers?
Do you get customer feedback about your documentation?
What is the goal of documentation for the organization?
Some resources for getting started with technical writing
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.
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.
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.
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.
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).
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.
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.
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
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.
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.
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.
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.
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.
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 wave of chatbots and virtual assistants like Cortana, Siri, and Alexa means that we’re engaging in conversations with non-humans more than ever before. Problem is, those non-human conversations can turn inhuman when it comes to social norms.
Interactions with virtual assistants aren’t totally devoid of human interaction. Indeed, they often disguise a true human interaction. Many chatbots aren’t fully automated and rely on humans to pick up the slack from the code. More fully-constructed virtual assistants like you find in Amazon’s Echo or your Apple iPhone are carefully programmed by humans. The programming choices they make also define your interactions with the personalities—and these interactions can redefine how you treat people.
A clear indication that someone is truly polite and kind is treating service people with respect, patience, and kindness. The rise of chatbots and virtual assistants, however, means that you’re never quite sure whether you’re speaking to a human. You might think that people can easily tell the difference between when they’re interacting with humans and when they’re interacting with a voice inside a smart box, but as the technology behind virtual assistants like Google Assistant, Amazon Alexa, or used by call centers evolves, that will get harder to evaluate. (Even when you’re calling a call center, it can be hard to tell whether you’ve reached a well-programmed intake bot or a real person who’s fully in the groove of their phone voice).
I find it fascinating (and saddening) that the programmers of Google Assistant’s Duplex chose to program in “umms” and “mmhmms” and did not program in any kindness indicators. Instead the voices come across as impatient and slightly condescending. I listened to the sample clips linked by Ethan Marcotte in his post Kumiho, about Google Duplex. If virtual assistants don’t include programmed kindness, the emotional labor performed by service workers will continue to be too high.
But there’s the rub. Alexa doesn’t acknowledge my thanks. There’s no banter, no trill of mutual appreciation, no silly little, “it is you who must be thanked” line. She just sits there sullenly, silently, ignoring my pleasantries.
And this is starting to feel weird, and makes me wonder if there’s an uncanny valley for politeness. Not one based on listening comprehension, or natural language parsing, but one based on the little rituals of social interaction. If I ask a person, say, what the weather is going to be, and they answer, I thank them, and they reply back to that thanks, and we part happy. If I ask Alexa what the weather is, and thank her, she ignores my thanks. I feel, insanely but even so, snubbed. Or worse, that I’ve snubbed her.”
“It’s the computing equivilent of being rude to waitresses. We shouldn’t allow it, and certainly not by lack of design. Worries about toddler screen time are nothing, compared to future worries about not inadvertently teaching your child to be rude to robots.
As virtual assistants become more common in day-to-day interactions, if they do not account for politeness, we might become a less kind society. Not only that, but impolite virtual assistants will add to the emotional labor performed by the service workers that don’t find their jobs replaced by technology.
After a breakup, how do you rediscover the activities that you enjoy and make you you?
does not want me
it is not the end of the world.
if i do not want me
the world is nothing but endings.
— nayyirah waheed
For myself, I spent several years in a relationship where I slowly let my own needs, wants, and desires be subsumed by those of my partner’s, and what I anticipated to be his needs, wants, and desires of me. Explicitly and implicitly, I lost myself in becoming who (I thought) he wanted me to be. After we broke up I was left with a profoundly distant sense of self. The last time I’d felt truly myself I was living at home (and that wasn’t a strong confident self). I was nothing like the person I became… or was I?
What followed has been an attempt to rediscover a sense of self and a sense of strength. I retried things I’d enjoyed with my partner in different contexts, and with different people (alone or with new friends), to derive new meaning. I needed to know if I truly enjoyed these activities or if I was only doing them because of him.
Something simple like making a bucket list helped me make real what I care about. Why would I want to go to one place instead of another? What sorts of things do I want to put on my list, activity and location-wise? How do I prioritize myself enough to get to go to those places and do those things? This also helps me tap into the sense of freedom and unpredictability in life, but in an ordered way (because that’s how I roll) that helps me discover my “true self”.
A bucket list also helped me think through shared goals, hopes, or dreams. How can I let go of a dream, or hold onto it, knowing that they might still hold that dream too? How can I travel to certain places without being reminded of them and a future I thought we’d share? How can I separate my dreams from those that we shared, created and dreamed together? Maybe I can’t. But that doesn’t mean I have to give them up. I can assess them, and see if I want to keep those goals, hopes, and dreams in my new life.
I worked to find comfort and strength in art and poetry. I asked a friend of mine for some poems about “living your best life”. I wanted some spiritual salve to learn how to remake myself after the relationship ended. She sent me poems like “My Dead Friends” by Marie Howe, “What the Living Do” by Marie Howe, and “The Journey” by Mary Oliver. I went to art museums, lingering amidst the modern art from Germany, a longtime favorite.
I also revisited things from before we started dating. I had to test things that I once cared about (to see if they still mattered to me). I’d neglected them or moved on from them or never gave myself the chance to fully commit to them. For me that was things like climbing, and going to concerts, or out dancing. I’ll attend my 100th show next month, and I recently got back from the Flash Foxy women’s climbing festival. I found myself again in the familiar experiences of going to shows, and in the community of climbing.
The crux of this process has been learning to feel like myself and like I know myself again.
With a stronger sense of self, I’ve started dating again. This is hard. (All things involving people are hard). This has led me to think a lot about what makes people compatible, and what qualities are important and which ones cannot be compromised on.
I saw author Kim Culbertson speak at a panel at the Bay Area Book Festival, and she said “Lots of people are uncomfortable when they hold themselves up to another person and the edges don’t match.”
That’s a lot of what dating feels like (that’s a lot of what talking to other humans feels like, honestly). One inclination to ease that discomfort is to disengage—this person is different from me, so I won’t talk to them (or share much of myself with them), or befriend or date them. Another way to ease that discomfort is to soften my own edges so that the mismatched edges are less apparent. And that’s where this essay comes in.
I had to re-sharpen the edges that make me me. Now I’m working to remind myself not to soften my own edges, but instead work to find a way to appreciate mismatched edges. I don’t need to find a person that perfectly interlocks with the edges of myself to find joy, happiness, intrigue, and personal growth. I do need to find someone that appreciates my edges (and whose edges I can appreciate).
With that in mind, what does it mean to be compatible with someone? Is it the mutual appreciation of edges, or something else? I think there are various levels of it.
The surface level compatibility that provides the initial intrigue—you find each other attractive, there is some chemistry, you started talking about a shared interest.
A deeper level compatibility when you share interests or passions. It’s easy when someone shares my music taste, or shares my appreciation for music. It’s harder to appreciate the edges of someone who doesn’t like music as much as I do.
The more fundamental, deep levels of compatibility reveal themselves as you get to know someone. You start to learn whether or not your communication styles complement each other or conflict with each other. Maybe you each communicate feelings differently, or miss each other’s “love language” signals. Maybe you want to discuss deep, introspective, existential questions over lunch, and your partner just wants to eat.
The edges of the people I meet and date won’t match up with me perfectly, but part of knowing where my edges are is knowing which edges of mine need to line up with those of someone else, and which ones can be different. (I’m still learning this, and I probably always will be).
That knowledge can help me keep my edges intact as I get to know someone. There is a distinct difference between learning to appreciate or respect the interests and passions of someone else and adopting those interests and passions wholesale for myself. I’m trying them out to see what they’re like. As I experience the interests and passions of others, I might be adding new facets to my edges.
But I’m also learning that it’s okay not to share the same interests and passions as the person I’m dating. It’s enough to appreciate that they have those interests and passions. As a perfectionist, I often try to not just to be perfect, but to be perfect for someone. So I have to take a step back (often) and remind myself that other people are flawed, that I’m also flawed, and that not everyone will appreciate raisins in baked goods, or disco music, or staying up late. And that’s okay.
We’re all human, we all have edges. Keep yours sharp, and admire those of others.
The American Top 40 chart includes more dance songs, more songs performed by DJs, and significantly more white artists than its counterpart, the Billboard charts.
Shit’s racist. I used to listen to the Ryan Seacrest Top 40 driving between Chicago and Michigan because it was one of the few things that I could listen to consistently along that entire drive on just a few radio stations. It wasn’t exactly quality radio, but it kept me awake.
The business meets somewhere at the crossroads of public relations and payola—a tradition as old as the music industry itself, historically used to define the illegal practice of record companies paying for commercial radio airtime. (Under U.S. law and FCC regulations, Payola is illegal on radio, but those laws do not apply to digital streaming platforms.) According to a 2015 Billboard article, a major-label marketing executive confirmed that pay-for-play is (or was) definitely happening.“According to a source, the price can range from $2,000 for a playlist with tens of thousands of fans to $10,000 for the more well-followed playlists.” And many are already calling the platform’s new “Sponsored Songs” endeavor a 2017 incarnation of payola.
I keep thinking I’ll get sick of Spotify thinkpieces but I’m not there yet. This one covers (in part) how Spotify structures their service to prioritize playlists over albums or other artist-created works, instead effectively reinstating payola and creating pay-to-playlists that then earn top billing all throughout the service. Me, I make my own playlists most of the time.
Everyone wants streaming music to be cheap or free for listeners, offer every song ever recorded, be made available on every device, be consistently lucrative for the industry, and give new and established artists robust support for new music. We all want snow that isn’t cold or wet. In principle, everyone is willing to pay, and everyone is willing to compromise, but no one is willing to compromise enough.
Womp womp. This is why for all of my use and support of services like Spotify and SoundCloud, now that I can afford it, I’m trying to buy the music that matters to me when possible. Less likely to disappear that way.
Confronting my own aversion to anger asked me to shift from seeing it simply as an emotion to be felt, and toward understanding it as a tool to be used: part of a well-stocked arsenal.
Leslie Jamison is one of my favorite essayists, and this is no exception.
I wrote two posts about analyzing my personal music data corpus. Reflecting on a decade of (quantified) music listening fits in with the rest of my blog posts about music, taking the personal tack to the quantified side of things. I also wrote up how I did all the analysis for my company blog, 10 Years of Listens: Analyzing My Music Data with Splunk. I’ve done some more analyses since these posts, like building something that lets me review the listening patterns for a specific artist compared with the dates that I’ve seen them in concert, and I’m working on analyzing if there is an average listen threshold before I see a band in concert (or not).
I also wrote about the importance that climbing has had in my life over the last year and a half in Finding Myself on the Wall. Grateful to get back on the wall tomorrow.
I took the time last year to start converting a dormant side project into a blogging series to share the links I’d collected. Calling it Borders on the Web, I post reminders of the borders that do exist on the web, as much as the techno-utopians in the world might like to pretend that they’re going away.
The trend in the last year or so toward more disco vibes has been… unexpectedly awesome. Going to see at least three of these artists live in the next few months… hoping to see more music from Thunder Jackson and Disco Despair soon too.
Some great DJ sets / mixtapes on here too. Seeing the xx live last year was a highlight, almost entirely because of Jamie xx. Realized that’s a show I’d pay more than I’d like to admit to go see if it were just him DJing. Haven’t managed to see Alex Cruz yet, though he’s been in the city a couple times since I’ve been here.