Throughout the last 6 weeks, 100 Warm Tunas has been aggregating your votes posted to popular social networks to provide the internet’s most accurate prediction of triple j’s Hottest 100 of the Decade.
Summary
- We collected 3,181 entries.
- We tallied 29,123 votes across these entries.
- triple j counted approximately 1,800,000 votes.
- Therefore, we collected a sample of 1.62%.
- 11.2% of votes were collected via Instagram direct message.
- We did not successfully predict #1
- We predicted 6 out of the top 10 songs.
- We predicted 25 out of the top 30 songs.
- We predicted 79 out of the 100 songs played in the countdown.
Evidently the amount of data collected was less than the Hottest 100 of 2019 however, our prediction still performed better when looking at the overall count of predicted songs in the top 100.
Technical Analysis
Similar to the Hottest 100 of 2019, we were not able to predict the outright winner of the countdown ,however we did successfully predict 25 of the songs to rank in the top 30.
Lets take a look at the top 10 of the official countdown and match it up with the predicted places in 100 Warm Tunas:
| Artist | Title | ABC Rank | Tunas Rank | Difference |
|---|---|---|---|---|
| Tame Impala | The Less I Know The Better | 1 | 5 | 4 |
| Gotye | Somebody That I Used To Know {Ft. Kimbra} | 2 | 6 | 4 |
| Arctic Monkeys | Do I Wanna Know? | 3 | 3 | 0 |
| Violent Soho | Covered In Chrome | 4 | 1 | 3 |
| RUFUS DU SOL | Innerbloom | 5 | 4 | 1 |
| Gang Of Youths | Magnolia | 6 | 2 | 4 |
| Foster the People | Pumped Up Kicks | 7 | 13 | 6 |
| Flume | Never Be Like You {Ft. Kai} | 8 | 15 | 7 |
| Angus & Julia Stone | Big Jet Plane | 9 | 21 | 12 |
| Matt Corby | Brother | 10 | 11 | 1 |
Lets pull apart this table a bit more and grab some statistics about how we did with our prediction overall:
| Predicted | Out Of Top N | Percentage |
|---|---|---|
| 6 | 10 | 60.0% |
| 14 | 20 | 70.0% |
| 25 | 30 | 83.3% |
| 32 | 40 | 80.0% |
| 39 | 50 | 78.0% |
| 50 | 60 | 83.3% |
| 58 | 70 | 82.9% |
| 64 | 80 | 80.0% |
| 72 | 90 | 80.0% |
| 79 | 100 | 79.0% |
| 155 | 200 | 77.5% |
From the above data, we can see that:
- The average error for the top ten ranks was 4.2 positions.
- Warm Tunas predicted 6 out of the top 10 songs.
- Warm Tunas predicted 14 out of the top 20 songs.
- Warm Tunas predicted 25 out of the top 30 songs.
- Warm Tunas predicted 79 out of the 100 songs played in the countdown.
To compare Warm Tuna’s predictions vs actual rankings, a scatter plot has been provided below. We can see as we get closer to rank 1, the 100 Warm Tunas prediction gets better and converges upon the actual rankings played out on the day:
Vote counts over time
Throughout the voting period, we observed a few key changes to the top 10, observing Magnolia and Do I Wanna Know competing for 2nd place in the prediction, as well as The Less I Know The Better and Innerbloom competing for 4th place in the prediction. This is potentially the most movement we have seen in a prediction since starting the project.
Vote counts by social network
The following table provides a break-down of vote counts per social network. There are some strong biases depending on which sources are included when producing rankings for the prediction:
| Song Title | Insta. Feed | Insta. Story | Insta. DM | Sum | Total | ||
|---|---|---|---|---|---|---|---|
| Covered In Chrome - Violent Soho | 314 | 58 | 20 | 27 | 67 | 486 | 479 |
| Magnolia - Gang Of Youths | 212 | 56 | 29 | 30 | 81 | 408 | 394 |
| Do I Wanna Know? - Arctic Monkeys | 183 | 56 | 43 | 23 | 57 | 362 | 357 |
| Innerbloom - RUFUS DU SOL | 185 | 43 | 31 | 31 | 61 | 351 | 344 |
| The Less I Know The Better - Tame Impala | 120 | 53 | 38 | 34 | 76 | 321 | 315 |
| Somebody That I Used To Know {Ft. Kimbra} - Gotye | 161 | 45 | 38 | 13 | 36 | 293 | 287 |
| It’s Nice To Be Alive - Ball Park Music | 162 | 39 | 26 | 18 | 37 | 282 | 270 |
| Breezeblocks - Alt-J | 164 | 29 | 15 | 15 | 39 | 262 | 254 |
| Midnight City - M83 | 141 | 30 | 22 | 23 | 27 | 243 | 240 |
| Runaway {ft. Pusha T} - Kanye West | 121 | 22 | 34 | 21 | 40 | 238 | 237 |
| Brother - Matt Corby | 129 | 48 | 20 | 3 | 34 | 234 | 233 |
| Royals - Lorde | 116 | 38 | 31 | 14 | 23 | 222 | 216 |
| Pumped Up Kicks - Foster the People | 108 | 45 | 22 | 14 | 32 | 221 | 214 |
| Let It Happen - Tame Impala | 87 | 27 | 26 | 45 | 36 | 221 | 213 |
| Never Be Like You {Ft. Kai} - Flume | 125 | 45 | 16 | 9 | 27 | 222 | 213 |
| Clair De Lune {Ft. Christine Hoberg} - Flight Facilities | 119 | 31 | 18 | 7 | 23 | 198 | 189 |
| Let Me Down Easy - Gang Of Youths | 86 | 33 | 21 | 17 | 30 | 187 | 183 |
| King Kunta - Kendrick Lamar | 94 | 25 | 20 | 15 | 24 | 178 | 175 |
| Tokyo (Vampires & Wolves) - The Wombats | 86 | 30 | 18 | 17 | 32 | 183 | 174 |
| Video Games - Lana Del Rey | 100 | 28 | 23 | 10 | 15 | 176 | 171 |
For example, if we only count votes from Instagram Stories, we are able to predict the 10 songs to place in the top 10 (ignoring order). By counting just Instagram Direct Messages and Twitter submissions, we are able to predict 1st place.
Finally, by excluding data collected from Instagram Feed, but using all other sources (Instagram DM, Instagram Story, Twitter, Reddit), we are able to provide a reasonably accurate prediction of the top 10:
| Artist | Title | ABC Rank | Tunas Rank | Difference |
|---|---|---|---|---|
| Tame Impala | The Less I Know The Better | 1 | 1 | 0 |
| Gotye | Somebody That I Used To Know {Ft. Kimbra} | 2 | 6 | 4 |
| Arctic Monkeys | Do I Wanna Know? | 3 | 3 | 0 |
| Violent Soho | Covered In Chrome | 4 | 4 | 0 |
| RUFUS DU SOL | Innerbloom | 5 | 5 | 0 |
| Gang Of Youths | Magnolia | 6 | 2 | 4 |
| Foster the People | Pumped Up Kicks | 7 | 10 | 3 |
| Flume | Never Be Like You {Ft. Kai} | 8 | 16 | 8 |
| Angus & Julia Stone | Big Jet Plane | 9 | 23 | 14 |
| Matt Corby | Brother | 10 | 11 | 1 |
This trend continues throughout the result set:
| Predicted | Out Of Top N | Percentage |
|---|---|---|
| 7 | 10 | 70.0% |
| 14 | 20 | 70.0% |
| 27 | 30 | 90.0% |
| 33 | 40 | 82.5% |
| 39 | 50 | 78.0% |
| 47 | 60 | 78.3% |
| 54 | 70 | 77.1% |
| 61 | 80 | 76.2% |
| 73 | 90 | 81.1% |
| 80 | 100 | 80.0% |
| 154 | 200 | 77.0% |
The accuracy of the top 10 is at 70%, the top 30 at 90%, and the top 100 at 80%. Whilst the accuracy across the top 200 stays almost constant these are some clear improvements over the results when Instagram feed images are included.
This trend is really interesting because counting just these sources means only 12,247 votes across 1,352 entries are counted toward the tally (compared to 29,123 across 3,181 entries). Perhaps this bias is an indication that it might be time to pull the plug on collecting data from the Instagram Feed and rely on these newer, more accurate sources?
Social Network Breakdown
We are now collecting votes from a handful of different sources. Here is the break down of how many votes were counted across the different sources:
| Source | Num Entries | Num Votes | Votes Per Entry |
|---|---|---|---|
| feed | 1888 | 17383 | 9.2071 |
| story | 490 | 4330 | 8.8367 |
| 357 | 3262 | 9.1373 | |
| reddit_submission_comment | 169 | 1482 | 8.7692 |
| direct_message | 356 | 3344 | 9.3933 |
| Sum | 3260 | 29801 | 9.1414 |
| Sum (after de-duplication) | 3181 | 29123 | 9.1553 |
Vote Submissions
It comes as no surprise that the most popular day for people to share their votes was on the day of voting opened with 442 entries collected, followed by the day voting closed with 391 entries collected.
Wrap Up
Whilst we didn’t pick the outright winner, we did successfully predict 25 of the 30 of the songs which landed in the top 30, as well as 79 of the top 100. As mentioned in the 2019 countdown wrap-up, with the shrinking amount of data and general biases across different voting sources, it’s getting harder and harder to pick the outright winner with certainty.
We’d like to thank everyone who shared their votes, visited our site or interacted with us on Instagram. Without our audience, 100 Warm Tunas wouldn’t be possible.
We are looking forward to running the prediction again in December for triple j’s Hottest 100 of 2020. Time to start collating that shortlist now!