The goal of any academic publication is to transfer the knowledge it contains to the mind of the reader. Traditionally, this was done through printed journals and other hands-on mediums, but today, a wider audience is targeted through web-based publications. Some readers prefer to use traditional sources, but more and more data is showing the trend of digital readership.

Using electronic sources as a form of publication and knowledge transfer has another advantage. It leaves a record of anyone who reads the source and what they do with the article if they cite it. This collection of readership data allows scholars and publishers to track what’s working, adjust what needs to be changed, and determine overall academic impact. But it can’t be done randomly, with anyone deciding what’s important based on their own input. Instead, this readership data is collected through specific metrics.

What is Readership Data, Specifically?

The term “readership” applies to the idea that a written item has been read specifically by a human. This is important to clarify, with so many artificial intelligence applications that arise all the time. The data collected through “readership” consists of statistics such as how many times a book has been requested and checked out through a library, how many times a document has been accessed off a web crawler, and how many times a journal article was downloaded.

Readership indicators include download and access counts as correlated with reader numbers to show how often an item was read (downloaded by the same reader multiple times does not apply). These statistical correlations are analyzed through data collection metrics and are tracked through samples that are considered to be unbiased, and from there, the academic impact is determined.

How the Impact of Research is Assessed

Through bibliometrics that collect different types of data, an article’s overall impact can be tracked and follows. Some of these databases, like Scopus and Science Direct, collect different metrics which, combined, give a clear picture of the work’s global impact.

Some examples of the data collected include:

●      A compilation of how many times the article was cited

●      The article’s peer reviews and the feedback obtained

●      The number of times an article was mentioned in another researcher’s work

●      How many times the article was directly searched for or downloaded from a web crawler

●      Specific search terms and keywords that are used to link readers to the article

With all of these metrics and more in use, the researcher can drive future publications based on what is working and what needs to be changed to account for greater academic impact.

Advantages and Disadvantages of Readership Data

Of course, using technological metrics to determine academic impact means that there is a wider net of information to be gathered. However, this quantitative data is sourced through a formula and is, therefore, not always completely transparent. It could also be biased if the user base of a journal or other publication source is not represented fairly.

Still, advantages make this a regular, preferred source of academic impact analysis, such as:

●      Less of bias over traditional citation indexes because of the widespread potential user base

●      Collection of readership data is free; traditional citation indexes charge, limiting their poll considerable

●      Readership data offers a bigger picture than citation counts alone

●      Scholars can track their academic impact based on more than citation counts

Disadvantages to watch for as a scholar include:

●      Lack of explanation of the data collected

●      No qualitative reasoning as to why an author chose the citation that was referenced

●      Possible inconsistency in altmetric data collected due to the lack of standardization used throughout the world’s providers and the sources themselves

●      Delays in standards, differences in behaviors and expectations, and other factors that exist through the various subjects and disciplines create changes in data that are not completely taken into account with the readership data impact results

The researcher that uses readership data to follow the academic impact of their publication and to use it to drive further work should be aware of the advantages and disadvantages and adjust for them in their project.

Using Impactio to Follow Academic Impact

Multiple sources today use readership data to determine academic impact, but Impactio is an all-in-one source that does this and so much more.

With Impactio, everything you need to create your publication and then follow it’s trail once it’s submitted is available in one source. Turn your research into professional PDF documents and web pages, submit your work with impressive subsections, charts, and graphs, and then monitor the ripple effect that occurs as your article takes off and its impact spreads.

Impactio is the platform used by scholars and experts around the world as a trusted program that has everything the researcher needs to make an impact with their work.