Welcome to Sounds: Analytical!
For a long time, we here at Sounds: Analytical have been wanting to release a music review website. Between the two of us, we listen to a lot of music and are constantly recommending music to each other and our friends. The biggest problem for us is that the internet is a crowded place to have a music blog. What we needed was a way to distinguish ourselves from other sites so that we wouldn’t just be another opinion/score in the sea of music reviews that float around the web.
In our discussions, we realized that what we really got excited about were lists and graphs. Lists are always two things: arbitrary and contentious. Every time Rolling Stone publishes their newest “Top 100 Artists that have had a #7 single” list, people whine and moan and say they could do better, but the key thing is that people read those lists and love arguing about them. We don’t plan on changing the way lists are done, but we do plan on releasing a lot more of them.
On the other side of things, xkcd, Graphjam, Indexed and others have taught us that people like graphs. I would always rather see a cool graph in a review than read some blow-hard ramble on for four pages about how some album reminds him of his first ski trip to the Alps (speaking of being a blow-hard, this welcome post is long, so if you’d like to see some graphs, just scroll down a bit).
There are more sections to the site as outlined below, but the core thing to remember is that we want you to actually get into and enjoy the content on this site instead of checking numbers/scores and then sprinting away.
There are only two of us here, so initially the content will be limited, but we hope to get some volunteer contributors to send in graphs, lists, mixtapes and other research to get a rich body of info here on the page. If you are interested, please email us at admin@soundsanalytical.com. Read on if you want to learn about the specific sections of the site, but if you are at all like me, you probably just want to scroll down and see the pretty pictures. Enjoy!
Current Findings
Current Findings is the unfiltered brain dump of interesting music-related finds around the internet. While we think that all the tracks posted here are worth listening to, we will mark some as “Statistically Significant” meaning that those are the best or most important new tracks we’ve heard in a while. We will provide individual posts or you can go to the Current Findings landing page and play all of the tracks as one continuous playlist.
Music Diagnostics
The meat of Sounds: Analytical will be our daily album and/or track diagnostics. Every review will contain a graph or some sort of analysis of the song/album, and in the end we will give a final grade. We will roughly grade records and songs based on the scale below. Keep in mind that in the subjective world of music reviewing, no one is perfect at grading an album, and tastes may change over time (as seen in Figure 3).
A+: One of the best albums of the decade
A: One of the top albums of the year
A-: A great album that will probably be top 20 for the year
B+: A very good album that will probably make the top 50
B: A good album that might make that top 50
B-: A pretty good album
C+: A better than average album that has nothing special to it
C: A wholly average album
C-: A slightly worse than average album
D: A bad album
F: A terrible album
Among these grades, we will highlight a number of albums/tracks as “Statistically Significant”, which means that we think they are good enough that they deserve a listen no matter what genres of music you prefer (as discussed in the Current Findings portion. These albums/songs will be included in the sidebar for instant access around the site.
Over the course of the year, we will probably listen to a lot of albums in the C range, but you will probably see our average scores creep towards a B rating. The primary reason behind this is that we are only reviewing five albums or songs a week, and there is a lot of unmemorable stuff that’s just not worth reviewing leaving us to generally review better albums. We will be sure to perform review statistics on our own site periodically and post them in the Further Research section of the site.
Included in the sidebar for each specific review will be a number of pieces of information. We’ll have iTunes and Amazon links to buy the mp3s of the album, related artists, genres, and we’ll even have full streaming of our three favorite tracks from the album.
With this all being said, what does a typical review graph look like? I’ve included two graphs below to display two examples of what our review content will look like. Keep in mind that the radar chart and the scatter plot are only two styles of graphs, and we will be employing a wide variety of graphs for our albums and tracks.
Figure 1: Track review for “Tik Tok” by Ke$ha
One thing to note is that our review grades will often not be strictly based on our included graphs. For example, while people might want to average out the scores of the radar chart in Figure 1 to get a score of ’3′ for the song, we are actually giving this song a D. To be fair, a ’5′ in sass doesn’t mean that a particular song is actually any good.
Figure 2: Album review for Bromst by Dan Deacon
The same is true for albums in what I like to call the Sound Of Silver effect. If I were to individually review each track off of LCD Soundsystem’s Sound Of Silver and then average them, I would probably get a score in the B range because songs 6-8 aren’t amazing and I didn’t even like song 9 “New York, I Love But You’re Bringing Me Down”. However, the first five tracks are so strong that they overcome the last four and bring the albums grade to a high A. Figure 2 plots each track from Bromst by Dan Deacon to show the combination of awesome and annoying (something Dan Deacon does so well). You can definitely infer that “Wet Wings” isn’t a great track, while “Snookered” and “Surprise Stefani” are. However, to reiterate, the final grade may not always be directly related to the graph.
We initially considered being very strict with our ratings and tying them to the graphs in order to be as objective as possible in our final scores, but the problem was that individual pieces of our graph were subjective. Trying to create objectivity from a corpus of subjective information doesn’t work, which is why our grades may not match our graphs, but the graphs are still important ways to convey info.
Listology
This section really speaks for itself. It’s made up of two main parts: lists and mixtapes.
Lists will be released weekly and will fall under two categories:
Objective Lists:
- “Top 10 Most Purchased Songs from Soundtracks in 2009 (from iTunes)”
- “Top 5 Best Selling Albums of all Time with the word ‘Black’ in the Title”
Subjective Lists:
- “Top 5 Worst Rapper Haircuts”
- “Top 20 Worst Lyrics in 2010″
- “Top 10 Best Bands with 11 or more Members”
Mixtapes will be a themed collection of music that we curate. Most mixtapes will be a list of songs, but some will be cohesive full-lengths that have been released for free around the web.
For Example:
- “Riding a Banana Boat in the Gulf of Mexico Mix”
- “Songs That Say the Word ‘Poop’”
- Lil Wayne |Â No Ceilings
- The Hood Internet |Â The Mixtape Volume Four
Further Research
Finally, this section will be a place for us to really dive down and do analysis outside of albums or songs. The Artist Focus section will be a place for us to break down all of the work released by a specific artist and list our favorite 2-3 songs from each album.
Pop Theory involves more graphs, so I know people will be excited about this. There’s a lot of interesting info about the music industry in general that could really use a deeper look. Â For example, see Figure 3 below for a graph of the scores of Pitchfork’s Top 50 Albums Of 2009.
Figure 3: Pitchfork’s Top 50 Albums Of 2009
If a perfect robot had reviewed albums for a year and then released a top 50 list, you would probably see a linear graph with a small but always positive slope (if the albums are plotted from 50 to 1). Since there are probably few to no robots working at Pitchfork, you get a much more interesting graph. As mentioned above, I fully expect our year end list (and graph) to be similarly jumpy merely because an album that may warrant a ‘C’ at the time of review might grow on you over the next few months (for those of you wondering about the major outlier in Figure 3, it’s the tUnE-yArDs album BiRd-BrAiNs which earned a 6.8 in April of 2009).
There will be a lot more graphs of this nature, and in the Pop Theory section, we will go into a lot more detail about the information presented.
Conclusion
What we are not doing here at Sounds: Analytical is attempting to change the way the world reviews music. I know that sometimes I hear an album and fall in love with it having no idea how that will translate into something that I can analyze. This is the problem with any place that reviews albums. There are as many different musical tastes as there are people in the world, and all we want to do is express our opinions and recommendations in a way that provides you with a hint of visual stimulation to complement your listening experience.
