The U.S. Department of Education’s graduation rate, which is reported through the Integrated Postsecondary Education Data System (IPEDS), is a nationally recognized and commonly used metric in higher education. Graduation rate is calculated as the percentage of first‐time, full‐time, degree/certificate seeking students that complete a CCC program within 150% of the estimated time it takes to complete the program.

Graduate students collect the number of students who have completed all the credits of the curriculum. Students who interrupt their studies Number of students in a study who, without obtaining the degree or moving to another university, do not enroll for two consecutive years. The type of Egress classifies students based on the cause of their egress: graduate, voluntary abandonment (two consecutive years without enrolment), non-compliance with the rules of the permanence regime, change of studies without simultaneity, transfer to another university. Efficiency Rate is the percentage ratio between the total number of credits that have passed the set of graduates of a given academic year throughout the study in which they have graduated and the total number of credits in which they have enrolled. Students in degree adaptation courses and students who have recognized (or adapted or validated) more than 15% of the credits in the curriculum are excluded. Students graduated by degree according to type of graduation, sex, graduate students, who interrupt their studies, who move to another university, who interrupt their studies the first year, duration and efficiency rate.

General data recollected for the studio " Analysis of the Quantitative Impact of Social Networks on Web Traffic of Cybermedia in the 27 Countries of the European Union". Four research questions are posed: what percentage of the total web traffic generated by cybermedia in the European Union comes from social networks? Is said percentage higher or lower than that provided through direct traffic and through the use of search engines via SEO positioning? Which social networks have a greater impact? And is there any degree of relationship between the specific weight of social networks in the web traffic of a cybermedia and circumstances such as the average duration of the user's visit, the number of page views or the bounce rate understood in its formal aspect of not performing any kind of interaction on the visited page beyond reading its content? To answer these questions, we have first proceeded to a selection of the cybermedia with the highest web traffic of the 27 countries that are currently part of the European Union after the United Kingdom left on December 31, 2020. In each nation we have selected five media using a combination of the global web traffic metrics provided by the tools Alexa (https://www.alexa.com/), which ceased to be operational on May 1, 2022, and SimilarWeb (https:// www.similarweb.com/). We have not used local metrics by country since the results obtained with these first two tools were sufficiently significant and our objective is not to establish a ranking of cybermedia by nation but to examine the relevance of social networks in their web traffic. In all cases, cybermedia whose property corresponds to a journalistic company have been selected, ruling out those belonging to telecommunications portals or service providers; in some cases they correspond to classic information companies (both newspapers and televisions) while in others they refer to digital natives, without this circumstance affecting the nature of the research proposed.
Below we have proceeded to examine the web traffic data of said cybermedia. The period corresponding to the months of October, November and December 2021 and January, February and March 2022 has been selected. We believe that this six-month stretch allows possible one-time variations to be overcome for a month, reinforcing the precision of the data obtained. To secure this data, we have used the SimilarWeb tool, currently the most precise tool that exists when examining the web traffic of a portal, although it is limited to that coming from desktops and laptops, without taking into account those that come from mobile devices, currently impossible to determine with existing measurement tools on the market. It includes:

Web traffic general data: average visit duration, pages per visit and bounce rate Web traffic origin by country Percentage of traffic generated from social media over total web traffic Distribution of web traffic generated from social networks Comparison of web traffic generated from social netwoks with direct and search procedures