If the Altmetric Attention Score for a research output decreases, it's usually due to one of two things:
Post Deletion
If a social media user (e.g Facebook page administrator, Google+ user or X user) deletes a post or deletes their whole profile, we would automatically remove the post(s) from the relevant details pages, which would cause the score for the research output to go down.
We don't automatically remove blog posts or news stories if they are taken down from sites, but if the author of the blog or news story asked us to remove a blog or news story, we would delete the mention from the relevant details page.
Modifiers for X
The social media modifiers mean that if we deem an X account to have a high bias and a high promiscuity level, those posts will contribute less to the score than posts from unbiased, non-promiscuous accounts. Our algorithm classes an X account as "promiscuous" if that person posts about scholarly content a lot. This is not a problem in itself, and posts from this account would not necessarily be scored lower than posts from other accounts. It's more that the value of posts from these accounts can degenerate over time, if our algorithm calculates that more than a certain number of these posts are about the same domain. If we re-classify a user as having a high bias and promiscuity level, their posts would contribute 0.25 towards the Altmetric Attention Score, rather than 1. When the research output is re-scored, the score will likely decrease for this reason.
The modifiers mean that (for example), posts from journal accounts are often scored lower than posts from individual researchers or members of the general public, as our algorithm calculates that this account is posting lots of papers from the same domain, which is likely for promotional purposes, rather than out of general interest.
Our perspective is that posts from accounts that share articles for promotional purposes shouldn't be scored the same as posts that share articles out of pure interest, as the two types of attention are slightly different, and the implied "impact" of the research output is not the same.
Changes to the Scoring Algorithm
On very rare occasions, we do make small changes to the scoring algorithm and re-score all the articles in the database. This can cause the scores for some articles to decrease.