Master programme


  1. Generate experts on webdatametrics who are able to assimilate the state of the art from a multidisciplinary perspective and under the framework of a solid theoretical background and experience in applying that theoretical knowledge.
  2. Generate experts on webdatametrics who have transferable skills: the ability to use knowledge in a changing global society.
  3. These objectives will be reached by providing students with the opportunity to specialize in a specific discipline within the topic of webdatametrics: either survey research, non-survey research (non-reactive data collection, online qualitative research), analysis of online data or webdata management.
  4. Developing students’ expertise in a field of application of webdatemetrics (such as sociology, economics, psychology, linguistics, cultural, media and marketing research, but also health studies, law, product evaluations among others).
  5. Giving students the expertise to transfer webdata skills to specialize across application fields.
  6. Allowing students to identify frontiers of knowledge on the topic and extend those frontiers through their Master ́s research and thesis.
  7. Encouraging students’ creative thinking and innovation.
  8. Offering students the opportunity of a training period which will help ease their access to the labour market.



The post-graduate course has 120 ECTS credits and duration of two years (four semesters). Semester 1 and 2 are dedicated to core courses, semester 3 for elective courses and in semester 4, the student must complete an internship period in one of our partner institutions and write and defend the master’s dissertation thesis.
Master courses are divided in 3 itineraries that cover the main areas of the webdata collection and analysis field:

a) Webdata management and analysis

b) Online survey research

c) Non-reactive data and internet based experimenting and testing



The master follows a blended methodology, with a mix of face to face classes and online 3.0. teaching. On-site classes take place at the beginning of each semester (September and end of January) for approximately one month. Then the courses continue with online supervision until the end of the semester, when final exams take place. Studium, the virtual campus of the University of Salamanca, provides the tools for an useful and enjoyable 3.0. online learning experience.

The programme is entirely run in English.



There is a clear and proven growing relevance of internet research and an increasing demand of Online data collection experts. The employment prospects of future webdatametricians are potentially immense, since web data collection and analysis is a growing field which will be relevant in many areas of knowledge (economics, sociology, psychology, media, opinion and marketing research, but also others, such as law, health sciences, manufacturing etc). Therefore, employment prospects will emerge from a wide variety of employers, from teaching, academic, research and governmental institutions to private enterprises and corporations.

The Webdatametrics master will constantly work to increase and identify employment prospects for students by generating links between the consortium and potential employers that, in many cases, will be associated partners which will actively participate in the academic activities. This strategy for extending networks of influence to increase employment prospects will be achieved mainly by increasing the opportunities during the training period.



The training period is a key opportunity for the students to gain professional experience and putting into practice the skills acquired during their master studies.

The training period is also a compulsory part of the master with comprises 375 hours (15 ECTS), equivalent to 10 weeks of full time work in one of our associated partners.

Internships are placed in semester four (second academic year) and will be normally offered on a full time basis. However, the Academic Board Commission could arrange other formats (ie. different dates or part time traineeships) to suit student ‘s requirements or demands. During the internship, students will be supervised by two tutors, one from the master and one from the host institution/company.

Student’s previous relevant professional experience in the field of webdata collection and analysis may be validated by the master’s academic board upon formal request. These students would be exceptionnaly exempt of doing the internship period.



What is a Webdatametrics master dissertation thesis?

It is an unique piece of research done by each student individually which proves that he or she has adquired the skills and knowledge to do scientific research in the field of collection and analysis of webdata. The end result consists of a well written text in English which has the potential to be published in an academic journal and/or implemented simultaneously in a enterprise project. You will also demonstrate your oral skills by defending your thesis during a public session. A thesis which is judged to be of very good or excellent quality will be a guarantee that the student is fit for an academic and/or enterprise career as researcher, consultant or analyst.

The thesis is an important part of the course and comprises 15 ECTS out of a total of 120 ECTS. It is expected to be defended at the end of the second academic year (May – September).

The master thesis dissertation elaboration comences during the second semester, when master students’ will take the 5 ECTS module “Directed Studies towards Master Dissertation Thesis”: students will embark on a negotiated module under the supervision of a participating academic on a topic germane to the specialization area of their master dissertation thesis. The topic and scope of such a module is to be agreed in advance through a learning contract countersigned by the student, module supervisor (usually the future tutor of the master dissertation thesis) and the Academic Board Commission. It is anticipated that such a module would typically include a research review component, research question, objectives and hypothesis, empirical data collection and an element of novel research which will be deepened and expanded during the completition of the master dissertation thesis.