While the most important part of an Altmetric report is the qualitative data, it's also useful to put attention in context and see how some research outputs are doing relative to others. The Altmetric Attention Score for a research output provides an indicator of the amount of attention that it has received. 


The Attention Score is a weighted count


The score is derived from an automated algorithm, and represents a weighted count of the amount of attention we've picked up for a research output. 


Why is it weighted? To reflect the relative reach of each type of source. It's easy to imagine that the average newspaper story is more likely to bring attention to the research output than the average tweet. This is reflected in the default weightings:


News

8

Blog

5

Policy document (per source)

3

Patent

3

Wikipedia

3

Twitter (tweets and retweets)

1

Peer review (Publons, Pubpeer)

1

Weibo (not trackable since 2015, but historical data kept)

1

Google+ (not trackable since 2019, but historical data kept)

1

F1000

1

Syllabi (Open Syllabus)

1

LinkedIn (not trackable since 2014, but historical data kept)

0.5

Facebook (only a curated list of public Pages)

0.25

Reddit

0.25

Pinterest (not trackable since 2013, but historical data kept)

0.25

Q&A (Stack Overflow)

0.25

Youtube

0.25

Number of Mendeley readers

0

Number of Dimensions and Web of Science citations

0


The Altmetric Attention Score always has to be a whole number. This means that mentions that contribute less than 1 to the score sometimes get rounded up to one. So, if we picked up one Facebook post for a paper, the score would increase by 1, but if we picked up 3 more Facebook posts for that same article, the score would still only increase by 1.


It is also important to note that, although the points given above are good indicators to understand the weighting system, our algorithm takes into account many other factors such as duplicate tweets or tiers calculations for different types of news sources. It is therefore not possible to calculate the Altmetric score with just a simple addition of mentions.


More explanations regarding score modifiers can be found here.