You may already be familiar with metrics like Citation Count and Field-Weighted Citation Impact (FWCI), but how about Altmetrics? Altmetrics, also known as Alternative metrics, is not a new concept and the term was coined in 2010. It is also not to be confused with Altmetric, the company that tracks and analyses online activity for scholarly output. If you are an avid social media user, you are already contributing to Altmetrics data when you tweet about a journal article at a conference.
Altmetrics is basically a term that describes web-based and social media focused metrics that are used to measure the impact of scholarly materials. It is an article level metric that measures the number of views, downloads, saves, clicks, shares, tweets, tags, bookmarks, posts, comments etc., that an article receives (Bornmann, 2014). As scholarly outputs are becoming increasingly diverse, Altmetrics has the potential to measure the true impact of scholarship beyond citation counts.
So why the need for Altmetrics when we already have traditional Bibliometrics that have been used for many decades? Wouters and Costas (2012) identified four main arguments supporting the use of Altmetrics when compared to traditional metrics:
For some fields, citations may take a long time. Altmetrics provides an almost instant and real-time measurement of the article’s impact. Altmetrics data can also be gathered quickly by using Application Programming Interfaces (APIs) through social media outlets.
Altmetrics has the potential to measure the broader impact of research beyond academia. Altmetrics can help to quantify the level of interest and the societal or political impact of an academic’s work.
In today’s increasingly digital era, the limits of scholarly outputs are no longer confined to outputs like journal articles, conference proceedings or reviews. Scholars are producing new objects like datasets, codes, websites, blogs and applications. Altmetrics can help to highlight the impact of these non-traditional research outputs.
Freely accessible data used in calculating Altmetrics can be quickly collected through APIs from social media outlets. As such, the data coverage is transparent to all who uses these APIs. Altmetrics are also not dependent on commercial databases like Scopus or Web of Science.
Controversies surrounding Altmetrics
Despite the immense potential of Altmetrics, they are also surrounded by a fair share of controversies. While there are many criticisms faced, the concerns tend to focus on two main areas: data quality and ease of data manipulation.
- Data Quality
Not everyone uses social media. There is a systematic bias towards “younger or more fad-embracing people” (Priem, 2014). Researchers in tech-savvy fields may also use social media more heavily than their counterparts from more technologically conservative disciplines. In addition, there are also geographic biases in the use of social media like how Twitter and Facebook may even be blocked in some countries, for e.g. China.
Everyone knows what is being measured with citation counts, but it is often not clear what is being measured through Altmetrics. There are no clear standards on how some Altmetrics are calculated, for e.g. the inability to quantify the different levels of social media engagement when an article is mentioned on Facebook (Bornmann, 2014). There could be many reasons, good or bad, why an article is mentioned on social media.
Consider this image and article above, do you have any idea why it has been tweeted about so much? *Hint – look at the abstract*
2. Data Manipulation
We have all heard stories where traditional Bibliometrics like the journal impact factor or citation counts are gamed, for e.g. through the formation of “citation cartels” (Priem, 2014). Similarly, Altmetrics can also be manipulated. Social media websites tend not to have any quality control or process to identify its users and it would be easy to systematically generate high Altmetrics scores for a researcher or an article. For e.g. Twitter mentions can be generated through fake accounts and “robot tweeting” (Bornmann, 2014).
Should I use it?
As with all forms of metrics, there are always advantages and disadvantages. It is widely accepted that even though there may be some concerns, Altmetrics is great for measuring impact on today’s diverse scholarly ecosystem (Priem, Taraborelli, Groth, & Neylon, 2010). With an increasing number of subject areas, and higher cross-disciplinarity in research outputs, it may not be sufficient to just rely solely on traditional metrics like citation counts or h-index.
Altmetrics’ popularity is growing, with more researchers exploring and adopting its use. From the growing research done on Altmetrics, there does not seem to be any immediate move for Altmetrics to replace traditional Bibliometrics. Instead, there have been calls to recognise the value of Altmetrics as a complementary tool for citation analysis, and to provide more holistic insights into one’s true scholarly impact in academia and beyond (Bornmann, 2014; Costas, Zahedi, & Wouters, 2015).
There are lots of tools out there providing Altmetrics. Some of them unfortunately require a subscription, but here are some free tools that you can explore if you are interested:
- Altmetric provides Altmetrics details for articles that you have published. You can do so by installing their free bookmarklet that allows you to view the online shares and mentions of an article with a single click. Altmetrics scores are also integrated into our NUS Libraries search engine FindMore@NUSL.
- When using Scopus, PlumX provides article-level metrics, such as: usage, capture, mentions and social media.
- PLOS has an article level metrics tool called ALM Reports that provides metrics for any set of PLOS articles within their database, as well as summarising and visualising the data results.
- Social Science Research Network (SSRN) also has a tool that allows you to search their elibrary. The tool provides article, author and institution ranking based on total number of downloads or total download for the past 12 months.
You are welcome to contact the Bibliometrics Team, should you want to learn more about Altmetrics. We are a team of librarians who are able to teach or assist with the generation of metrics for P & T, Annual Reviews, benchmarking, etc. Please visit our library guide for more information.
Bornmann, L. (2014). Do altmetrics point to the broader impact of research? An overview of benefits and disadvantages of altmetrics. Journal of Informetrics, 8, 895-903.
Costas, R., Zahedi, Z., & Wouters, P. (2015). Do ‘altmetrics’ correlate with citations? Extensive comparison of altmetric indicators with citations from a multidisciplinary perspective. Journal of the association for information science and technology, 66(10), 2003-2019.
Priem, J. (2014) Altmetrics. In Cornin, B., & Sugimoto, C.R. (Eds.), Beyond Bibliometrics: Harnessing multi-dimensional indicators of performance. Cambridge, MA, USA: MIT Press
Priem, J., Taraborelli, D., Groth, P., & Neylon, C. (2010, October 26). Altmetrics: A manifesto. Retrieved from http://altmetrics.org/manifesto
Wouters, P., & Costas, R. (2012). Users, narcissism and control: Tracking the impact of scholarly publications in the 21st century. Retrieved from http://research-acumen.eu/wp-content/uploads/Users-narcissism-and-control.pdf