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E10. Analyze and evaluate the role of digital communities and social media in business.
E13. Identify the basic tools of e-Marketing.
E14. Apply the knowledge acquired to the management of digital communities.
E9. Apply technological tools for the use of business resources through Marketing.
G1. Be able to work in a team, actively participate in tasks and negotiate in the face of dissenting opinions until reaching consensus positions, thus acquiring the ability to learn together with other team members and create new knowledge.
G2. Be able to innovate by developing an open attitude to change and be willing to re-evaluate old mental models that limit thinking.
T4. Master computer tools and their main applications for ordinary academic and professional activity.
During the first years the student has learned about the use of social media for marketing in a qualitative way. This qualitative knowledge, however, does not help us to work with large social networks where we do not know people but only their data and connections on the network.
The subject studies the formalization of social networks, and the quantitative methods that can be applied to them.
The aim is for students to learn the different types of networks that can be given and to measure their different structural characteristics. Understand how this structure affects the way information is disseminated and helps to form opinions.
The different and current communication disorders are presented as complex phenomena, associated with the loss of confidence in political, media and business actors. The social and psychological factors that explain the belief in non-facts or false information through academic concepts (polarization, third-person effect o echo chambers).
At the end of the course the student must be able to work with social networks from a formal point of view, knowing how to distinguish and identify the types of networks that exist and which metrics can be applied. The student must understand the meaning of current metrics and have a sufficient theoretical foundation to be able to learn and interpret new metrics. The goal is for you to be able to discuss with the company’s data managers what values you want to extract from the data.
Know the operation of social networks as well as the existence of different basic technological tools useful for the use of e-Marketing resources, and social networks to support business decision making.
MD1.Master class: The work methodology will be based on the inverted class, in which the student will have the materials some time before the class so that he can study them. During the class, the most relevant points will be highlighted, doubts will be resolved and exercises will be done on the topics covered.
MD2. Lectures: Face-to-face or streaming sessions, both in university classrooms and in the framework of another institution, in which one or more specialists present their experiences or projects to students.
MD3. Presentations: Multimedia formats that support face-to-face classes
MD5. Seminars: Face-to-face format in small work groups (between 14 and 40). These are sessions linked to the face-to-face sessions of the subject that allow to offer a practical perspective of the subject and in which the participation of the student is key.
MD7. Case study: Dynamics that starts from the study of a case, which serves to contextualize the student in a specific situation, the teacher can propose different activities, both individually and in groups, among their students
MD9. Planned session with established and organized tasks.
Intensive use will be made of the tools and support technologies needed to monitor each of the topics, taking into account that the main spaces will be:
Plataforma institucional: The virtual classroom will be the place where to find all the necessary instructions for the follow-up of the subject. It is also the space for communication and evaluation.
Social media analysis software: Software packages that the student must use to be part of their work
This course, due to the situation generated by COVID, the sessions will be held in hybrid format: face-to-face and online (via streaming). This will allow students to rotate to face-to-face classes, respecting the maximum number of students per classroom imposed by the distance measures. When they are not in contact, they will be able to follow the class online from home.
This subject has methodological and digital resources to make possible its continuity in non-contact mode in the case of being necessary for reasons related to the Covid-19. In this way, the achievement of the same knowledge and skills that are specified in this teaching plan will be ensured. The TecnoCampus will make available to teachers and students the digital tools needed to carry out the course, as well as guides and recommendations that facilitate adaptation to the non-contact mode.
The classroom (physical or virtual) is a safe space, free of sexist, racist, homophobic, transphobic and discriminatory attitudes, either towards students or teachers. We trust that together we can create a safe space where we can make mistakes and learn without having to suffer the prejudices of others.
Topic 1. Networks from a formal point of view
Methods of representation
Subject 2. Characterization of the structure of the network
Topic 3. Social Network Analysis (SNA)
Measurements in networks
Topic 4. SNA tools
Item 5. Obtaining networks
Item 6. Networked communities
Subject 7. Communicative disorders in the network
Third person effect
AF1. Theoretical sessions
AF3. Work in group
AF4. Individual work
AF5. Personal study
SE1. Participation in the activities proposed in the classroom and internships in pairs (30%) - Non-recoverable.
SE2. Group work group (30%) - Recoverable in group.
SE4. Content tests Final exam (40%) - (20% mid-term test + 20% final test) - Recoverable.
It is necessary to have a 4 in each of the parts to be able to pass the subject. The student will only be able to retake the part of the content tests. If a group does not reach group work at 4 (or all members fail the subject) they can retake the group work.
Tsvetovat, Maksim, Kouznetsov, Alexander (2011) Social Network Analysis for Startups: Finding connections on the social web. O'Reilly
Hanneman, R., Riddle, M. (2005) Introduction to Social Networks Methods. http://faculty.ucr.edu/~hanneman/nettext/
Easley, David, Kleinberg, John. (2010) Networks, Crowds, and Markets: Reasoning About a Highly Connected World. Cambridge University Press. http://www.cs.cornell.edu/home/kleinber/networks-book/