Year: 2010
Type: editorial
Abstract: I recently received an email from a company essentially offering a social networking platform for scientists. Recipient scientists are encouraged to create a ‘brand’ for themselves that is recognised by influential people through the popularity of the scientists' blogs and tweets. These instruments could be used, according to the advert, to help scientists be recognised as ‘thought leaders’. Social networking platforms are nothing new, of course, in professional and freelance circles, but I find the promotion and growth of such services in scientific research interesting because it generates a means of judging impact that runs parallel to the traditional bibliometric measures, and is recorded – potentially for all to search and see, free of charge – in cyberspace. In theory, it would even be possible to judge the credibility of particular scientists in this context: the combination of the quality of feedback that they receive to a particular blog or tweet that they post, combined with their degree of inward connectivity (i.e. links that others make to them, not the reverse) in the network, could serve as such a measure. There are currently various ways of measuring individual scientists' performance, influence or recognition (whether for good or bad reasons). Examples are the personal impact factor, the Hirsch factor, in its various weighted or unweighted forms, and just looking at the number of the audience at a scientific talk during parallel sessions of a conference. All methods are flawed to some extent. Might the social networking factor of a scientist be more reliable? In one sense it would be: though the Hirsch factor (and other measures based on citation) is perfectly capable of continuing to rise after a scientist's death, it is unlikely that a dead scientist will do much more social networking (or give talks at meetings, for that matter). Also, if used responsibly by scientists, social networking would be capable of recording the origin of truly revolutionary ideas in science, disseminating them most rapidly for others to comment on, and measuring the quantity of interest and concordance with the proposition.
Source: BioEssays
Author: Andrew Moore
Language: English
Subfield: Statistics, Probability and Uncertainty
Field: Decision Sciences
Domain: Social Sciences
Open Access status: bronze
OpenAlex ID: W1836839038