Altmetrics
Although altmetrics are often thought of as metrics about articles, they can be applied to people, journals, books, data sets, presentations, videos, source code repositories, web pages, etc.
[1] Altmetrics could be applied to research filter,[1] promotion and tenure dossiers, grant applications[10][11] and for ranking newly-published articles in academic search engines.
[13] The development of web 2.0 has changed the research publication seeking and sharing within or outside the academy, but also provides new innovative constructs to measure the broad scientific impact of scholar work.
Important in determining the relative impact of a paper, a service that calculates altmetrics statistics needs a considerably sized knowledge base.
Typical sources of data to calculate this metric include Facebook, Google+, Twitter, Science Blogs, and Wikipedia pages.
At this point in time, it is unclear whether higher citations occur as a result of greater media attention via Twitter and other platforms, or is simply reflective of the quality of the article itself.
The study highlights the role of using discussion based platforms, such as Twitter, in order to increase the value of traditional impact metrics.
Altmetric.com uses this information for calculating metrics, while other tools just report where discussion is happening, such as ResearchBlogging and Chemical blogspace.
Proponents of altmetrics make clear that many of the metrics show attention or engagement, rather than the quality of impacts on the progress of science.
[28][4] Thus, altmetrics provide convenient approaches for researchers and institutions to monitor the impact of their work and avoid inappropriate interpretations.
For the nano-scientists that are mentioned on Twitter, their interactions with reporters and non-scientists positively and significantly predicted higher h-index, whereas the non-mentioned group failed.
[43] Altmetrics expands the measurement of scholar impact for containing a rapid uptake, a broader range of audiences and diverse research outputs.
In addition, the community shows a clear need: funders demand measurables on the impact of their spending, such as public engagement.
However, there are limitations that affect the usefulness due to technique problems and systematic bias of construct, such as data quality, heterogeneity and particular dependencies.
[4] As for systematic bias, like other metrics, altmetrics are prone to self-citation, gaming, and other mechanisms to boost one's apparent impact such as performing citation spam in Wikipedia.
[28] For example, the top tweeted articles in biomedicine in 2011 were relevant to curious or funny content, potential health applications, and catastrophe.
[64] With the changing shift in open science and social media use, the consistent altmetrics across disciplines and institutions will more likely be adopted.
The specific use cases and characteristics is an active research field in bibliometrics, providing much needed data to measure the impact of altmetrics itself.
They assume that the positive and significant correlation reveals the accuracy of altmetrics to measure scientific impact as citations.
[60] The low correlation (less than 0.30[4]) leads to the conclusion that altmetrics serves a complementary role in scholar impact measurement such as the study by Lamba (2020) [71] who examined 2343 articles having both altmetric attention scores and citations published by 22 core health care policy faculty members at Harvard Medical School and a significant strong positive correlation (r>0.4) was observed between the aggregated ranked altmetric attention scores and ranked citation/increased citation values for all the faculty members in the study.
However, it remains unsolved that what altmetrics are most valuable and what degree of correlation between two metrics generates a stronger impact on the measurement.
