SEO for Research Networking: How to boost Profiles/VIVO traffic by an order of magnitude

"Redwoods" by Michael Balint (cc-by)

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.

1. Measure Everything

  • Install Google Analytics
    • Set it up on every page of the site
  • Learn how to use it
  • Segment on-campus vs. off-campus use
    • Find your “service provider” name(s) at Audience > Technology > Network
    • Create an advanced segment that includes only your service provider(s), and one that excludes it/them
    • Use these two segments to analyze everything (internal and external visitors are totally different, and need to always be analyzed separately)
  • Register with Google Webmaster Tools
    • Go to google.com/webmasters/tools
    • Follow the directions to register your site
    • See how your site’s indexed on Google, and check for issues
  • Check the Recommendations for RNS Usage Tracking

2. Ignore Your Homepage, Focus on Profile Pages

  • On a mature search-optimized RNS like UCSF Profiles, only 2.6% of visits start on the homepage
  • If you’re successful with steps 3-4, traffic directly to profile pages will skyrocket, and dominate traffic. That means you need to focus most of your attention on the care, feeding, and design of profile pages, vs. the home page.

3. Search Engine Optimization (SEO)

  • Make sure search engines can see your pages
    • Tweak your robots.txt so search engines can see all your pages (robotstxt.org)
    • Create a dynamically-generated sitemap of all your profile pages (sitemaps.org)
    • Mention your sitemap in your robots.txt file, and then register it with Google Webmaster Tools
    • Wait a day, use Google Webmaster Tools to validate that your sitemap works
  • Improve the copy on your profile page titles and descriptions
    • Make the page <title> on profile pages short and globally unique
    • Make <meta name=”description”> on profile pages readable and descriptive
      (e.g. “Jane Doe’s profile, publications, research topics, and co-authors”)

4. Add extra professional metadata

  • Follow the directions at schema.org and schema.org/Person to add people-oriented HTML metadata to your profile pages
  • Use google.com/webmasters/tools/richsnippets to test your syntax
  • OPTIONAL: Use “pretty” URLs — and include names if possible (e.g. http://www.yoursite.edu/firstname.lastname)
    • Pretty URLs should be the “real” final URL, not just a redirect
    • All old or alternative profile URLs should do a 301 redirect to the pretty URL
  • OPTIONAL: Prevent indexing of multiple versions of your page
    • If you have multiple versions of your page getting indexed (e.g. /url/ vs. /url/?a=b), tell search engines which version is the main one by using the rel=canonical canonical link element

5. Get Inbound Links

  • Get webmasters to link to your homepage from campus resource guides, etc.
  • Get webmasters to link to individual profiles from departmental faculty profiles, news stories, campus directory, etc.
  • Encourage reuse of your data via APIs, and ask for a link back as attribution (downstream users save time and money; you get links back in return)
  • All these new links may not send traffic, but will help SEO.

Have questions? Suggestions? Leave a comment below, or contact Anirvan Chatterjee directly.

Photo credit: Michael Balint, used under Creative Commons attribution license

UCSF Profiles coauthorship networks, by degree

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:

Avg # contacts, 1 degree away

The numbers jump when you go one degree further out, though the relative proportions are similar:

1 and 2 degree

The numbers grow further when we count first, second, and third degree coauthors.

1-3 degree contacts

My big takeaways are unsurprising:

  • The number of UCSF co-authorships generally grow with seniority — which may correlate with both the length of one’s career, as well as one’s tenure at UCSF
  • Even in the case of professors’ 1st-3rd degree, connections, we’re maxing out at 180 people, out of about 6,500 people in UCSF Profiles. This number may correlate to the size of one’s department/field at UCSF.
  • If we showed logged-in UCSF Profiles users a visualization showing “here’s how you know this person” when looking at another random user’s profile, it would kick in pretty infrequently — thought that might be different for folks in the same field/department

UCSF dentistry co-authorships, internal vs. external (by institutions)

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.

UCSF vs External Co-Authoring InstitutionsView as PDF

Method: I searched Web of Science for dentistry-related articles published between January 1-December 5, 2013. I began by running a search for any articles published in 2013 matching a number of dentistry-related keywords (dental, dentistry, electrogalvanism, endodontics, jaw relation record, mouth rehabilitation, odontometry, oral, orthodontics, periodontics, prosthodontics, teeth, tooth), then filtered only those that matched the “DENTISTRY ORAL SURGERY MEDICINE” Web of Science category. Web of Science automatically attempts to normalize institution names; in addition, I lumped all institution labels with names that start with “UCSF”, “UC San Francisco”, or “UCSF Sch ” to “Univ Calif San Francisco” as part of the main UCSF grouping.

UCSF dentistry co-authorships, internal vs. external

What does a typical UCSF publication look like, in terms of internal vs. external co-authors? Here’s a breakdown of each type of co-author, among dentistry-related publications by UCSF researchers published in 2013.

Three immediate take-aways:

  • I was surprised to see so many co-authorships between a single UCSF researcher and one or more external researchers — the very top row of results. By volume, this accounts for 52% of the papers we looked at.
  • When every author is internal to UCSF, there’s an average of 3.5 UCSF co-authors
  • When there’s an external collaboration, there’s an average of 2.0 UCSF co-authors

UCSF vs External Co-AuthorsView as PDF

Method: I searched Web of Science for dentistry-related articles published between January 1-December 5, 2013. I began by running a search for any articles published in 2013 matching a number of dentistry-related keywords (dental, dentistry, electrogalvanism, endodontics, jaw relation record, mouth rehabilitation, odontometry, oral, orthodontics, periodontics, prosthodontics, teeth, tooth), then filtered only those that matched the “DENTISTRY ORAL SURGERY MEDICINE” Web of Science category. Web of Science automatically attempts to normalize institution names; in addition, I lumped all institution labels with names that start with “UCSF”, “UC San Francisco”, or “UCSF Sch ” to “Univ Calif San Francisco” as part of the main UCSF grouping.

UCSF dentistry collaborations, mapped

Social network graphs are pretty, but they’re not the only way we can try to visualized cross-institutional research collaborations. Here’s a geographic view of some of the institutions that UCSF dentistry researchers have co-authored with over the course of 2013.

UCSF Dentistry Collaborations, Jan 1 - Dec 5, 2013 (World)

UCSF Dentistry Collaborations, Jan 1 - Dec 5, 2013 (USA)

UCSF Dentistry Collaborations, Jan 1 - Dec 5, 2013 (Europe)

Method: I searched Web of Science for dentistry-related articles published in 2013 (i.e. from January 1-December 5, 2013). I began by running a search for any articles published in 2013 matching a number of dentistry-related keywords (dental, dentistry, electrogalvanism, endodontics, jaw relation record, mouth rehabilitation, odontometry, oral, orthodontics, periodontics, prosthodontics, teeth, tooth), then filtered only those that matched the “DENTISTRY ORAL SURGERY MEDICINE” Web of Science category. I pulled out institution names, tried to geolocate them using the OpenStreetMap Nominatim service, and used Google Fusion Maps to put them on a map. This map is by no means authoritative, given that a significant number of institutions could not be trivially geolocated.

UCSF dentistry collaborations, visualized

Looking at cross-institutional co-authorship networks is a useful way of seeing not only who we work with, but also where there may be gaps of interest.

I first looked at dentistry-related publications by UCSF researchers published in 2013, breaking out the institutions we co-authored with. And there we are, sitting pretty in the center of our universe, collaborating with major institutions in the US, Korea, Australia, Italy, Denmark, and more.

(Details: Institution node sizes indicate the total volume of dentistry-related articles published. Connecting line widths indicate the number of articles co-authored between two institutions. Distance between nodes indicates the tightness of co-authorship networks, and different sets of node colors help distinguish groups of institutions whose researchers frequently co-author together. Of 462 institutions that collaborated with UCSF researchers, we’re showing only 91 that had 10 or more cross-institutional articles in that time.)

View full-size visualization (PDF)

UCSF dentistry research co-authorships, Jan 1 - Dec 5 2013

Then I looked at the total universe of dentistry-related publications published in 2013 (see below). Notice a difference? I have to admit that it took me a while to find UCSF in the mess of dots. (If you look at the full-size view, we’re in the medium blue section, next to the pinks.) Of course this says more about the sheer volume of research being published by universities all over the world, than about any lack of cross-institutionally collaborative spirit on our part; in fact I hid over 80% of the institutions in the first image to keep it readable, which accounts for a a good chunk of the difference. But the sheer weight of institutions from Europe, East Asia, and Latin America in this second image that aren’t there in the first is intriguing, and something I’m going to try digging into.

(Details: Institution node sizes indicate the total volume of dentistry-related articles published. Connecting line widths indicate the number of articles co-authored between two institutions. Distance between nodes indicates the tightness of co-authorship networks, and different sets of node colors help distinguish groups of institutions whose researchers frequently co-author together. Of 2,575 institutions that we found, we’re showing only 374 that had 10 or more cross-institutional articles in that time.)

View full-size visualization (PDF)

Dentistry research co-authorships, Jan 1-Dec 5 2013

(And yes, I realize fully well that I’m probably looking at the wrong things here, privileging increasing the count of cross-institutional collaborations as an end in itself, avoiding any consideration of research quality, and giving greater visual weight to institutions that publish more, regardless of the size of the institution or the quality of work. Pretty pictures lie can hide lots of flaws. I hope you’ll bear with me as I publicly iterate through these topics, step by step, hopefully getting just a little bit less dumb every time.)

Additional uninteresting details: I searched Web of Science for dentistry-related articles published in 2013 (i.e. from January 1-December 5, 2013). I began by running a search for any articles published in 2013 matching a number of dentistry-related keywords (dental, dentistry, electrogalvanism, endodontics, jaw relation record, mouth rehabilitation, odontometry, oral, orthodontics, periodontics, prosthodontics, teeth, tooth), then filtered only those that matched the “DENTISTRY ORAL SURGERY MEDICINE” Web of Science category.

The 100 top researcher keywords at UCSF

I was looking to dig into some examples of collaboration patterns in different research areas, when I realized I didn’t even know the basics — what do UCSF researchers actually research?

UCSF Profiles uses PubMed data to extract MeSH keywords for every publication by every UCSF researcher in the system. We can use this to look at the most commonly used MeSH keywords across every researcher’s body of work. There are lots of caveats here (looking at all publications emphasizes past research interests over current ones; we’re not grouping related obscure MeSH terms with more popular ones; MeSH term assignment practices change over time; and this analysis ignores someone’s role as a first, middle, or last author). But this is certainly a start.

Here’s what I found, using the latest UCSF Profiles data:

  1. 98 researchers have HIV Infections in their top 5 MeSH keywords
  2. 53 researchers have Breast Neoplasms in their top 5 MeSH keywords
  3. 42 researchers have Magnetic Resonance Imaging in their top 5 MeSH keywords
  4. 39 researchers have Tomography, X-Ray Computed in their top 5 MeSH keywords
  5. 39 researchers have Brain Neoplasms in their top 5 MeSH keywords
  6. 37 researchers have Internship and Residency in their top 5 MeSH keywords
  7. 37 researchers have HIV-1 in their top 5 MeSH keywords
  8. 34 researchers have Alzheimer Disease in their top 5 MeSH keywords
  9. 33 researchers have Prostatic Neoplasms in their top 5 MeSH keywords
  10. 32 researchers have Saccharomyces cerevisiae in their top 5 MeSH keywords
  11. 31 researchers have Brain in their top 5 MeSH keywords
  12. 31 researchers have Anti-HIV Agents in their top 5 MeSH keywords
  13. 30 researchers have Neoplasms in their top 5 MeSH keywords
  14. 30 researchers have Smoking in their top 5 MeSH keywords
  15. 29 researchers have Diabetes Mellitus, Type 2 in their top 5 MeSH keywords
  16. 29 researchers have Asthma in their top 5 MeSH keywords
  17. 28 researchers have Stroke in their top 5 MeSH keywords
  18. 28 researchers have Sexual Behavior in their top 5 MeSH keywords
  19. 27 researchers have Myocardial Infarction in their top 5 MeSH keywords
  20. 27 researchers have Proteins in their top 5 MeSH keywords
  21. 26 researchers have Neurons in their top 5 MeSH keywords
  22. 26 researchers have Skin Neoplasms in their top 5 MeSH keywords
  23. 26 researchers have Antineoplastic Combined Chemotherapy Protocols in their top 5 MeSH keywords
  24. 25 researchers have Cognition Disorders in their top 5 MeSH keywords
  25. 25 researchers have Homosexuality, Male in their top 5 MeSH keywords
  26. 25 researchers have Emergency Service, Hospital in their top 5 MeSH keywords
  27. 25 researchers have Students, Medical in their top 5 MeSH keywords
  28. 24 researchers have Obesity in their top 5 MeSH keywords
  29. 24 researchers have Glioblastoma in their top 5 MeSH keywords
  30. 23 researchers have Epilepsy in their top 5 MeSH keywords
  31. 23 researchers have Pancreatic Neoplasms in their top 5 MeSH keywords
  32. 23 researchers have Dementia in their top 5 MeSH keywords
  33. 23 researchers have Liver Transplantation in their top 5 MeSH keywords
  34. 23 researchers have Hispanic Americans in their top 5 MeSH keywords
  35. 23 researchers have Education, Medical, Undergraduate in their top 5 MeSH keywords
  36. 22 researchers have Lung in their top 5 MeSH keywords
  37. 22 researchers have Genetic Predisposition to Disease in their top 5 MeSH keywords
  38. 22 researchers have Saccharomyces cerevisiae Proteins in their top 5 MeSH keywords
  39. 22 researchers have Lung Neoplasms in their top 5 MeSH keywords
  40. 22 researchers have Glioma in their top 5 MeSH keywords
  41. 21 researchers have Drosophila in their top 5 MeSH keywords
  42. 21 researchers have Mass Screening in their top 5 MeSH keywords
  43. 21 researchers have Heart Defects, Congenital in their top 5 MeSH keywords
  44. 21 researchers have Anti-Bacterial Agents in their top 5 MeSH keywords
  45. 21 researchers have Liver in their top 5 MeSH keywords
  46. 21 researchers have Polymorphism, Single Nucleotide in their top 5 MeSH keywords
  47. 21 researchers have Physician-Patient Relations in their top 5 MeSH keywords
  48. 21 researchers have Signal Transduction in their top 5 MeSH keywords
  49. 21 researchers have Primary Health Care in their top 5 MeSH keywords
  50. 21 researchers have Nerve Tissue Proteins in their top 5 MeSH keywords
  51. 21 researchers have Stem Cells in their top 5 MeSH keywords
  52. 21 researchers have Drosophila melanogaster in their top 5 MeSH keywords
  53. 20 researchers have Colorectal Neoplasms in their top 5 MeSH keywords
  54. 20 researchers have Stress Disorders, Post-Traumatic in their top 5 MeSH keywords
  55. 20 researchers have Calcium in their top 5 MeSH keywords
  56. 20 researchers have Health Services Accessibility in their top 5 MeSH keywords
  57. 20 researchers have Smoking Cessation in their top 5 MeSH keywords
  58. 20 researchers have Epithelial Cells in their top 5 MeSH keywords
  59. 20 researchers have Wounds and Injuries in their top 5 MeSH keywords
  60. 20 researchers have Drosophila Proteins in their top 5 MeSH keywords
  61. 20 researchers have Models, Molecular in their top 5 MeSH keywords
  62. 19 researchers have Magnetic Resonance Spectroscopy in their top 5 MeSH keywords
  63. 19 researchers have MicroRNAs in their top 5 MeSH keywords
  64. 19 researchers have Respiratory Distress Syndrome, Adult in their top 5 MeSH keywords
  65. 19 researchers have Curriculum in their top 5 MeSH keywords
  66. 19 researchers have Aging in their top 5 MeSH keywords
  67. 19 researchers have Embryonic Stem Cells in their top 5 MeSH keywords
  68. 19 researchers have Caenorhabditis elegans in their top 5 MeSH keywords
  69. 19 researchers have Kidney Transplantation in their top 5 MeSH keywords
  70. 18 researchers have Heart Failure in their top 5 MeSH keywords
  71. 18 researchers have Membrane Proteins in their top 5 MeSH keywords
  72. 18 researchers have Asian Americans in their top 5 MeSH keywords
  73. 18 researchers have DNA in their top 5 MeSH keywords
  74. 18 researchers have Tuberculosis in their top 5 MeSH keywords
  75. 18 researchers have Mental Disorders in their top 5 MeSH keywords
  76. 18 researchers have Transcription Factors in their top 5 MeSH keywords
  77. 18 researchers have Coronary Disease in their top 5 MeSH keywords
  78. 18 researchers have Gene Expression Profiling in their top 5 MeSH keywords
  79. 17 researchers have DNA-Binding Proteins in their top 5 MeSH keywords
  80. 17 researchers have CD8-Positive T-Lymphocytes in their top 5 MeSH keywords
  81. 17 researchers have Skin Diseases in their top 5 MeSH keywords
  82. 17 researchers have Bacterial Proteins in their top 5 MeSH keywords
  83. 17 researchers have Apoptosis in their top 5 MeSH keywords
  84. 17 researchers have Protein-Serine-Threonine Kinases in their top 5 MeSH keywords
  85. 17 researchers have Homeodomain Proteins in their top 5 MeSH keywords
  86. 17 researchers have Hypertension in their top 5 MeSH keywords
  87. 17 researchers have Stress, Psychological in their top 5 MeSH keywords
  88. 17 researchers have T-Lymphocytes in their top 5 MeSH keywords
  89. 17 researchers have Abortion, Induced in their top 5 MeSH keywords
  90. 17 researchers have Schizophrenia in their top 5 MeSH keywords
  91. 17 researchers have Antineoplastic Agents in their top 5 MeSH keywords
  92. 17 researchers have Proteomics in their top 5 MeSH keywords
  93. 17 researchers have Multiple Sclerosis in their top 5 MeSH keywords
  94. 17 researchers have Teaching in their top 5 MeSH keywords
  95. 17 researchers have Acquired Immunodeficiency Syndrome in their top 5 MeSH keywords
  96. 17 researchers have Hepatitis C in their top 5 MeSH keywords
  97. 17 researchers have Laparoscopy in their top 5 MeSH keywords
  98. 16 researchers have Muscle, Skeletal in their top 5 MeSH keywords
  99. 16 researchers have Amyloid beta-Peptides in their top 5 MeSH keywords
  100. 16 researchers have Ovarian Neoplasms in their top 5 MeSH keywords
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