The UCSF Profiles team recently did a deep dive into what factors are most predictive of the popularity of a given profile page.
We did a regression analysis of 14 different factors, added in our own experience with the site, and ended up with 5 key lessons for profile owners:
Research networking systems (RNS) like Vivo, Profiles, SciVal, and Pure are meant to be used — but often fail to be discoverable by real users because of poor search engine optimization (SEO).
That’s why we’re releasing RNS SEO 2015, the first-ever report describing how RNS performs in terms of real-world discoverability on Google.
The UCSF Profiles Team got more international attention for its enhancements to the Profiles product and the level of engaged users last year. Over the past several months, the Special Program for Research and Training in Tropical Diseases (TDR) has been in talks with UCSF Profiles to gain insight and plan an approach to create a system that will show and track their researchers’ work around the globe. TDR is a global collaborative program sponsored by the United Nations Children’s Fund (UNICEF), the United Nations Development Program (UNDP), the World Bank and World Health Organization (WHO). Continue reading
UCSF Profiles is an example of a Research networking system (RNS). These systems provide automated aggregation and mining of information to create profiles and networks of the people that make up an academic institution. RNS’s have in effect, become a new kind of ‘front door’ for the university, providing access to the university’s intellectual capital in a manner previously unattainable — i.e. one focused on expertise rather than schools or departments, thus intermingling experts regardless of where they’re officially housed. Against this backdrop, we wanted to understand how such a tool might enhance access to academic expertise by external partners, specifically industry, and improve UCSF’s response to industry interest. Continue reading
The UCSF Profiles team has increased site usage by over an order of magnitude since the site’s big campus-wide launch in 2010. This “growth hacking” cheat sheet distills the key lessons learned during that period, and can be applied to almost any research networking platform, including VIVO, Profiles, and home-grown solutions. Continue reading
We’re using UCSF Profiles data to explore whether co-authorship networks are a good way to show the connections between researchers at UCSF.
We can start off by looking at immediate co-authorship connections. I was surprised at how few current UCSF co-authors most users have. The flip side of co-authoring widely outside of one’s institution is that there are fewer internal co-authors:
What does a typical UCSF publication look like, in terms of the number of internal co-authors vs. the number of external co-authoring institutions? Here’s a breakdown among dentistry-related publications by UCSF researchers published in 2013. (This is the same analysis as yesterday, but looking at the number of external institutions, vs. the number of external people.)
Again, I was surprised to see so many co-authorships between a single UCSF researcher and one or researchers from one or more external institutions (the very top row of results), which accounts for 52% of the papers we looked at.
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