Let’s take the definitions from our last post for a test drive on tweeted percentiles for a hypothetical set of 100 papers, presented here in order of increasing readership with our assigned percentile ranges:
- 10 papers have 0 tweets (0-9th percentile)
- 40 papers have 1 tweet (10-49th)
- 10 papers have 2 tweets (50-59th)
- 20 papers have 5 tweets (60-79th)
- 1 paper has 9 tweets: (80th)
- 18 papers have 10 tweets (81-98th)
- 1 paper has 42 tweets (99th)
If someone came to us with a new paper that had 0 tweets, given the sample described above we would assign it to the 0-9th percentile (using a range rather than a single number because we roll like that). A new paper with 1 tweet would be in the 10th-49th percentile. A new paper with 9 tweets is easy: 80th percentile.
If we got a paper with 4 tweets we’d see it’s between the datapoints in our reference sample — the 59th and 60th percentiles — so we’d round down and report it as 59th percentile. If someone arrives with a paper that has more tweets than anything in our collected reference sample we’d give it a 100th percentile.
(This is part 4 of a series on how total-impact will give context to the altmetrics we report.)