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Page Rankings: What do they teach us? Faina Linkov, PhD Ronald LaPorte, PhD And the Global Health Network Supercourse project University of Pittsburgh.

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Presentation on theme: "Page Rankings: What do they teach us? Faina Linkov, PhD Ronald LaPorte, PhD And the Global Health Network Supercourse project University of Pittsburgh."— Presentation transcript:

1 Page Rankings: What do they teach us? Faina Linkov, PhD Ronald LaPorte, PhD And the Global Health Network Supercourse project University of Pittsburgh

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3 Google’s description of page rank …PageRank relies on the uniquely democratic nature of the web by using its vast link structure as an indicator of an individual page's value. In essence, Google interprets a link from page A to page B as a vote, by page A, for page B. But, Google looks at more than the sheer volume of votes, or links a page receives; it also analyzes the page that casts the vote. Votes cast by pages that are themselves "important" weigh more heavily and help to make other pages "important…"

4 All search engines assign a value to your site based on inbound links Google calls this relevancy factor “Page Rank” (PR) - synonymous with popularity ranking An inbound link is a vote for your page An outbound link is a vote for the page you’re linking to Understanding Page Rank

5 A page is assigned PR as soon as it’s indexed The page receiving the most inbound links gets the highest page rank You can pass PR around to pages on your site Understanding Page Rank

6 Your popularity is not determined by the sites you link to Your outbound links affect the popularity of the sites you’re linking to Internal links and inbound links have the most impact on your popularity Outbound links help identify you with a hub Outbound Links

7 Page Rankings and the Supercourse

8 Teacher in Mexico Teacher in Santo Domingo Teacher in Havana Teacher in Pittsburgh Teacher in San Francisco Supercourse Model: lecture sharing Teacher in Bolivia

9 Current Status 40000 participants (15 Nobel Prize winners) 151 countries Over 2800 lectures

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11 A Model for Developing and Prescribing Assistive Technology Devices Mary Ellen Buning, PhD, OTR/L, ATP Jue Wang, PhD University of Pittsburgh

12 Cardiovascular Epidemiology: Definitions Historical Perspectives and Assessing Risk of CVD Recent trends and population differences in CHD and CHD risk factors Nathan Wong

13 Topic – Google PPT. lecture ranking for the Supercourse Amebiasis - 2(English) 3 (Spanish) Communicable Disease and disasters - 3/372 Cardiovascular epidemiology- 1&2/9730 Diabetes epidemiology - 3/13,000 Evidenced based public health - 1/158 Global Health - 1&2/3,820,000 Indian Health - 1&2/56,000 Infectious disease epidemiology - 1/21,000 Islamic/Arab health - 2/537 Information on the Web - 1/78 Meta Analysis - 6/116,000 Occupation Cancer - 3/18,000 Pakistani Health - 6&7/18,500 Pitt.edu - 2/2,400,000 Primordial Prevention - 1/126 Russian health- 2&3/19,000 Tsunami - 11/31,000

14 Health (this is a search on the whole web for the term "health" (985,000,000 pages) NIH = 3 WHO = 40 CDC = 220 PAHO= 224

15 Global health (328,000,000 pages) US AID 3 Gates 4 Supercourse 8 CDC 12 WHO 67 NIH 70 PAHO >300

16 Page Rankings within NIH search term, overall, and then only for the Institutes All Only Institutes NLM 3 1 NCCAM 13 2 NIMH 12 3 NHLBI 19 4 CIT 27 5 CSR 29 6 NIAID 30 7 NEI 36 8 NICHD 42 9 NIAMS 48 10 NIDA 56 11 NIA 59 12 NIDDK 62 13 NINDS 66 14 NIAAA 69 15 CC 73 16 NIEHS 75 17 NIDCD 82 18 NCRR 133 19 NINR 205 20 NIBIB 221 21 NCI 236 22 FIC >300 23 NIGRI >300 24 NIGMS >300 25 NCMHD >300 26

17 Conclusions Page ranking is an important tool helping to assess the popularity and the quality of the website Supercourse lectures are scored very highly by Google rankings We need to explore how page rankings can influence information dissemination in the US and worldwide


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