The term bibliometrics comprises a set of methods used to study or measure texts and information. Whilst bibliometric methods are most often used in the field of library and information science, they have wide applications in other areas. In fact, they are used to explore the impact of their field, the impact of a set of researchers, or the impact of a particular paper.
Common indicators studied in bibliometrics are:
• Publication count: total number of scientific publications or patents published by re- searchers in a specified field. They provide an estimate of research interest, and total research output in a field.
• Citations and impact factor: this is the number of citation, and proxies the scientific impact of given research. The assumption is that a higher number of citations reflect a more influential the work.
• Co-citation and co-word analysis: is used to measure linkages among publications and patents. Co-citation and co-word indicators can be combined with publication and citation counts to build multifaceted representations of research fields, the linkages among them, and the actors who are shaping them.
Bibliometrics is a useful and adaptable tool to support FLAs, as it can allow identifying emerging research fields that can offer disruptive technologies in the short, middle or long run, at the same time, bibliometric information can be used to inform innovation forecasting models.
When integrated with other methods such as patents analysis, literature review, scenarios and expert panels, bibliometric studies have been widely used as a valuable source of data for FTA. For example, Shibata et al (2011) try to distinguish between incremental and radical innovations identification of emerging clusters on the basis of quantitative analysis of citations and keywords for a particular technology field.
In this case the results have created a background for further qualitative studies. Furthermore, bibliometric data can be used for distinguishing between groups of technologies that do and do not follow the linear model of innovation (Jarvenpaa et al, 2011), which gives experts an opportunity to focus on particular technology areas using relevant qualitative methods.