Altmetric data captures a range of interactions such as comments, posts, tweets about research activities via the social web and mainstream media, as well as article level metrics very quickly. In this way you can see at a glance the extent to which your research is being shared and discussed by others.
As an indicator of engagement and potential reach of research, qualitative altmetric data may supplement and affirm actual impacts and applications of research by the target audiance or stakeholders.
Comments and conversations about your research gleaned via the social web may facilitate connections with potential collaborators at a global level, both within the academy and beyond.
Cons
Altmetric data is gathered via the social web and as such it can be subject to gaming and artificial bias by individuals who want to influence the number of times their research content is accessed and used by others.
As an evolving set of impact indicators, altmetrics data is used inconsistently across academic disciplines. There is currently a stronger emphasis in the sciences and medicine. As a result, interdisciplinary comparison of altmetric data is not recommended.
To date there is no consensus regarding the use of altmetrics to support faculty tenure applications, grant applications and overall scholarly research impact.
More research needs to be conducted to determine if altmetrics can be a factor in predicting research impact.
