Do altmetrics measure influence and quality or attention and self-promotion?
In the absence of peer-review and within the infinite universes of social networks and the web, some scholars have turned to describing altmetrics as discovery tools rather than assessments of the worth of a particular work. In this view, Altmetrics act (1) as a filter pointing to something that might be of importance. That is, there is an assumption that a positive correlation exists between the number of tweets and hits in other social media and the potential importance of a work. In addition, discovery of a different type happens when (2) altmetrics pull together the online data, discussions, and evolution of ideas that lay behind a finished work. In doing so, altmetrics is said to provide a richer experience than that which can be obtain by exposure to only a finish product, e.g. an article.
Use More Than One Tool
It is important to use multiple tools, because there is no one database that includes it all (all articles, all blogs, all works, or all journals or all issues of journals). Like traditional bibliometrics, altmetrics can only be as comprehensive as the sources from which their data are drawn.
It is important to know the origins of the data so that you know what might be missing as well as if this particular tool is suitable for your discipline. For example, many altmetrics rely on Mendeley data, which is primarily used by the sciences (though this may be changing). Others rely on Google Scholar data which, as with all sets, has certain limitations.
Some limitations specific to altmetrics and ALMs:
Unlike library catalogs, which practice "authority control," some tools do not uniformly distinguish between authors with the same or similar names or pull together all publications by an author who has published with name variations. This is a problem within and between all traditional and unconventional bibliographic tools.
It is possible that works by authors with the same name will be counted as works by one author. Hence, it is important to look at the actual works by which the impact and other measurements are being calculated. In short, make sure the author and work match the author whose work you wish to analyze.
If an author has not consistently published with the same name or exact spelling or format of her name, not all of her work will appear in a single search of Google Scholar, for example. Furthermore, her name may be listed differently within Google Scholar than in Web of Science, which in turn may both list the author differently than does Northwestern Scholars. Some platforms use first names while others use first initials or first initials and a wildcard, some may include a middle name, etc. There can be even greater complications in regard to name identification within social networks.
This issue is known as "author disambiguation" or the "management of authorial identity."