SciVal Topics
Topics enhances SciVal’s capabilities as an advanced evaluative and analytical tool and an important part of strategic research planning.
Conduct a portfolio analysis to identify which Topics your institution is currently active in, and which Topics have high momentum, and so are likely to be well-funded1 se abre en una nueva pestaña/ventana through analysis of around 94,000 Topics and 1,500 Topic Clusters. Enrich your strategic planning with Topic overviews of peer institutions, countries or researchers and gain insight into which researchers are active in specific Topics, which Topics your peers and competitors are active in and the related Topics of which you should be aware.
A Topic is a collection of publications with a common intellectual interest, based on direct citations, that represent fields of research globally. Topics can be large or small, new or old, growing or declining. Over time, new Topics will surface, and as Topics represent fields of research, they are dynamic and will evolve. A publication can belong to only one Topic and a Topic can belong to only one Topic Cluster.
As with the nature of research many Topics are multidisciplinary, and older Topics may be dormant, but they still exist. In addition, researchers themselves are mobile, and work across many research areas, and thereby contribute to many Topics. Scopus publications from 1996-present are clustered into the Topics and Topic Clusters using direct citation analysis (as opposed to co-citation analysis).
How can I use Topics?
University leaders, Senior Research Officers, Deans and department heads can enrich strategic research planning with portfolio overviews of their own and peer institutions to identify research strengths and support strategic partnership decisions
Research Services teams and libraries can enrich management level reports, facilitate and enhance collaboration efforts and support targeted funding bids through facilitating workshops and providing insights around the key institutions and researchers in Topics and research fields of interest
Faculty and researchers can identify experts and potential cross-sector collaborators in specific Topics to strengthen their project teams and funding bids, and identify Topics which are likely to be well funded — they can also uncover new publications to read in key areas of interest
Governments and funding agencies can profile the research activities of their nations and identify the key institutions and researchers working in Topics of interest or focus
Corporate Research & Development teams can identify potential strategic technology partners, locate key academic expertise in strategic or niche fields and profile Topics competitors are active in
Case study: Arizona State university identifies and connects expertise with SciVal
Download case study se abre en una nueva pestaña/ventana
The Topic wheel and Scatterplot views provide overviews of the Topics an entity of interest is contributing to and clear ways to analyze the Topics in more detail in other modules.
Newly emerged Topics
Newly emerged Topics represent areas of research that have seen a significant growth in recently published outputs, citations and have attracted recent funding as determined by acknowledgement of grants in publications1 se abre en una nueva pestaña/ventana. We look at a combination of the emergence potential (number of publications recently vs previous years), size of the Topic, new citation relationships and funding to classify a newly emerged Topic.
Please see our openly accessible newly emerged Topics page se abre en una nueva pestaña/ventana to get insights into the 70 newly emerged Topics identified in 2024.
Methodology — how are Topics and Topic Clusters created?
We take the entire citation network — over 1.5 billion citation links between 59+ million Scopus-indexed publications from 1996 forward and an additional 24+ million non-indexed documents that are cited at least twice, and indexed and non-indexed publications from before 1996 — and break that network into around 94,000 Topics.
All Scopus publications are clustered into Topics using direct citation analysis (as opposed to co-citation analysis). A Topic is created where the direct citation linkages within the Topic are strong and the direct citation linkages outside the Topic are weak. Only the indexed publications are included in Topics.
The borders between clusters (Topics) are identified by looking at where the citation links are weak. Where the links are weak, the clusters are split into separate Topics.
Topic Clusters are formed using the same direct citation algorithm that creates Topics. When the strength of the citation links between Topics reaches a threshold, a Topic Cluster is formed. A Topic Cluster is an aggregation of Topics with similar research profiles into broader, higher-level areas of research. These Topic Clusters can be used to get a broader understanding of the research being done by a country, institution (or group) or researcher (or group), before drilling into the more specific or niche underlying Topics.
Each of the 94,000 Topics have been matched with one of the 1,500 Topic Clusters. As with Topics, a researcher or institution can contribute to multiple Topic Clusters, but a Topic can only belong to one Topic Cluster and a publication can only belong to one Topic (and, therefore, one Topic Cluster).
In May 2024 we launched a new updated set of Topics and Topic Clusters – next generation SciVal Topics. Drawing upon recent methodological advancements2 se abre en una nueva pestaña/ventana, the new updated set of Topics is more cohesive, with a noticeably higher proportion of publications being strongly linked to a Topic, providing greater relevance and precise insights.
What is prominence?
Prominence is an indicator of the momentum/movement or visibility of a particular Topic. Prominence does not signify 'Importance'. Calculating a Topic’s Prominence combines three metrics to indicate the momentum of the topic:
Citation count in year n to papers published in n and n-1
Scopus views count in year n to papers published in n and n-1
Average CiteScore for year n
Prominence does not signify 'Importance'
Due to the nature of certain research fields there are Topics which will never become ‘prominent’. However, this does not mean the Topic is not important.
How does prominence relate to funding?
There is a correlation between the prominence (momentum) of a particular Topic and the amount of funding per author within that topic1 se abre en una nueva pestaña/ventana. On average, the higher the momentum, the more money per author is available for research on that Topic.
SciTech Strategies identified a correlation between the prominence of a Topic and the amount of funding per author within a Topic by assigning 314,000 grants worth $203 billion from the STAR METRICS database, a large project-level funding database that accounts for 24 percent of US federal funding, to all 96,000 Topics through textual similarity. The grant data were split into two time periods for each Topic and the correlation analyzed. The model also showed that the correlation between Prominence and future funding is 0.616, thus Prominence accounts for 38% (or 0.6162) of the variance of future funding.
1Research Portfolio Analysis and Topic Prominence se abre en una nueva pestaña/ventana Richard Klavans and Kevin W. Boyack
2An improved practical approach to forecasting exceptional growth in research se abre en una nueva pestaña/ventana Kevin W. Boyack and Richard Klavans
Additional information
For further information regarding Topics of Prominence please see the following papers and documents:
Identifying Emerging Topics in Science and Technology se abre en una nueva pestaña/ventana, Henry Small, Kevin W. Boyack and Richard Klavans
A New Methodology for Constructing a Publication-Level Classification System of Science se abre en una nueva pestaña/ventana, Ludo Waltman and Nees Jan van Eck
In the first of a regular series looking at who is producing highly cited research in different areas, THE explores a subject currently deemed the ‘most prominent’ by Elsevier metrics