norm_7_final.pdf (422.37 kB)
How to normalize Twitter counts? A first attempt based on journals in the Twitter Index
journal contribution
posted on 2016-02-10, 16:53 authored by Lutz BornmannLutz Bornmann, Robin HaunschildRobin HaunschildOne possible way of measuring the broad impact of research (societal
impact) quantitatively is the use of alternative metrics (altmetrics). An
important source of altmetrics is Twitter, which is a popular microblogging
service. In bibliometrics, it is standard to normalize citations for
cross-field comparisons. This study deals with the normalization of Twitter
counts (TC). The problem with Twitter data is that many papers receive zero
tweets or only one tweet. In order to restrict the impact analysis on only
those journals producing a considerable Twitter impact, we defined the Twitter
Index (TI) containing journals with at least 80% of the papers with at least 1
tweet each. For all papers in each TI journal, we calculated normalized Twitter
percentiles (TP) which range from 0 (no impact) to 100 (highest impact). Thus,
the highest impact accounts for the paper with the most tweets compared to the
other papers in the journal. TP are proposed to be used for cross-field
comparisons. We studied the field-independency of TP in comparison with TC. The
results point out that the TP can validly be used particularly in biomedical
and health sciences, life and earth sciences, mathematics and computer science,
as well as physical sciences and engineering. In a first application of TP, we
calculated percentiles for countries. The results show that Denmark, Finland,
and Norway are the countries with the most tweeted papers (measured by average
tweets per paper).