Bảng xếp hạng của webometrics

[xuandinhbank]

Hiếm hoi lắm mới thấy có một nơi nào đó xếp hạng các trường đại học của Việt Nam. http://www.webometrics.info/rank_by_country.asp?country=vn&offset=0
Tuy nhiên, bảng xếp hạng của họ lại không giống với common sense ở Việt Nam và không giống một tí nào với expectation của em.
Không biết là bạn bè quốc tế nhìn nhận bảng xếp hạng của webometrics như thế nào. Riêng ở Việt Nam, hễ bài báo nào nói về xếp hạng hầu như đều nêu ra ông webometrics.
Điều em không hài lòng là họ không đưa ngôi trường yêu quý của em vào danh sách (ĐH Ngân hàng) và lại cho "Lạc Hồng (http://vietnamnet.vn/giaoduc/2009/08/862510/)" vào "top tier"

Please take into account the following facts about criteria for inclusion and methodology:

* Only universities with an independent domain are considered. If one institution has more than one main domain, we analyze all of them but only the best ranked is published, even if this domain is not the new (current) or the preferred one.
* Since 2009 the ranking is derived from a composite indicator of the normalized values of each variable, not from the ordinals. These individual ranks are provided mainly for reference.
* Strong discrepancies among variables, especially those regarding the Google Scholar figures, concerned us deeply. Some adjustments have been done in several instances.
* One university has been excluded due to bad practices that make impossible a correct calculation of its rank.
* The Bing engine showed an irregular behavior during the period of data harvesting, so it has been excluded temporarily from the present calculations.
* In the last editions a few cases were manipulated to better reflect the overall web performance of the universities. The ranks of the institutions with many and important faculty web domains were obtained merging the data from all of them. As no improvement in the naming practices has been observed, most of these universities are now ranked only with the data obtained for their central web domain.
* Please check the Notes section for explanation of the asterisks.

[phuocddat]

Theo như những gì ghi ở đây, thì có lẽ nếu ĐH nào có "chiêu thức" PR mạnh trên mạng thì nhiều khá năng sẽ được thăng hạng nhanh chóng. Đây thực chất là đo lường về mức độ phổ biến của 1 trường nào đó trong môi trường internet thôi. Mối liên hệ giữa mức độ phổ biến này và chất lượng đào tạo là khá mơ hồ, nếu không muốn nói là nhiều khi khập khiễng. Điều đáng buồn là nhiều nhà giáo dục lại vin vào cái này khi nói về chất lượng giáo dục / ranks của trường ĐH tại VN.

University activity is multi-dimensional and this is reflected in its web presence. So the best way to build the ranking is combining a group of indicators that measures these different aspects. Almind & Ingwersen proposed the first Web indicator, Web Impact Factor (WIF), based on link analysis that combines the number of external inlinks and the number of pages of the website, a ratio of 1:1 between visibility and size. This ratio is used for the ranking but adding two new indicators to the size component: Number of documents, measured from the number of rich files in a web domain, and number of publications being collected by Google Scholar database. As it has been already commented, the four indicators were obtained from the quantitative results provided by the main search engines as follows:

Size (S). Number of pages recovered from four engines: Google, Yahoo, Live Search and Exalead. For each engine, results are log-normalised to 1 for the highest value. Then for each domain, maximum and minimum results are excluded and every institution is assigned a rank according to the combined sum.
Visibility (V). The total number of unique external links received (inlinks) by a site can be only confidently obtained from Yahoo Search. Results are log-normalised to 1 for the highest value and then combined to generate the rank.
Rich Files (R). After evaluation of their relevance to academic and publication activities and considering the volume of the different file formats, the following were selected: Adobe Acrobat (.pdf), Adobe PostScript (.ps), Microsoft Word (.doc) and Microsoft Powerpoint (.ppt). These data were extracted using Google and merging the results for each filetype after log-normalising in the same way as described before.
Scholar (Sc). Google Scholar provides the number of papers and citations for each academic domain. These results from the Scholar database represent papers, reports and other academic items.