The phrase "author level" is correct and usable in written English.
It can be used to refer to the rank, status, or expertise of an author, often in contexts related to publishing, writing, or academic contributions.
Example: "The journal requires submissions to meet a certain author level to ensure quality and credibility."
Alternatives: "author rank" or "author status".
Content rank will take into account the authority of a source down to the author level, social buzz, sentiment, as well as how much that article is being linked to.
For an interesting study of bibliometric indicators on the author level, see e.g. [9].
Author name disambiguation is therefore an important prerequisite for the author level analyses of publication data.
Authors can change their research subject during their career, thus making a categorization on the author level difficult.
To check the accuracy of the disambiguation procedure at author level, we have manually verified the authors' list for 100 articles.
However, the systematic correction for self-citations is nearly impossible at the author level because of the strong homonymies among author names.
An integrated editor using a common rule representation model, patient data model, and standard terminologies would assist with this effort at the authoring level.
At this point, the user may choose to view authorship styles at an author-level or message-level perspective (Figure 2).
The h-index is a well-known author-level bibliometric indicator that quantifies the scientific output of a scholar by a single number.
There are different ways of calculating author-level impact: number of article citations, number of publications, or combine the publication and citation counts to create a "hybrid indicator" [13].
In this context, we adapt the Hirsch index (h-index) [3], an author-level metrics that combines the productivity and citation impact of scholars, to the productivity and influence of Twitter users.
