In recent years, the expansion of Web 2.0 and the emergence of social media as central platforms for social interaction across various domains—from entertainment to politics, and from consumption to work—have significantly altered communication and behavioral patterns, extending beyond personal interactions to political engagement, social movement activism, and marketing strategies.

The digitalized environment has facilitated access to an unprecedented volume of data, known as 'big data.' The development of new methodological and computational tools has enabled the analysis of this data for diverse applications. For instance, digital analytics tools allow organizations, political parties, companies, and influencers to enhance their positioning and effectively reach their target demographics, thereby expanding their membership and voter base, increasing fundraising capabilities, or improving product sales.

This course aims to examine the transformation in communication dynamics induced by digital media proliferation and introduce methodologies for analyzing 'digital trails' for commercial, political, or scientific purposes.

The course structure comprises four main segments:

1. Introduction to the premises of the digital revolution in both scientific and practical research contexts.
2. Overview of analytical methodologies, including statistical, computational, and qualitative approaches, to leverage data effectively, providing a holistic view of the available 'toolkit.'
3. Exploration of data and method applications in contemporary politics and activism, digital marketing, and social sciences.
4. A practical laboratory session where students apply learned methodologies, such as netnography and other advanced analytical techniques, to scientifically investigate and assess digital communication strategies.

The course objectives are threefold:

- Theoretical: to impart knowledge about the digitized landscape;
- Methodological: to provide proficiency in the analytical tools introduced;
- Applicative: to adopt a primarily applicative approach, culminating in a laboratory setting where students gain hands-on experience with the methodological tools discussed.

The program will be discussed in detail during the course and will be subject to adaptations, to meet the learning pace and the prior knowledge of the class. It is proposed to cover the following themes.

• Part one - The context:
  • Internet, digital traces, and big data
  • The networked society
• Part two - The methods:
  • Classical statistical methods
  • Computational methods
  • Qualitative digital methods (netnography)
• Part three - The applications:
  • Social media, Internet, and digital analytics in contemporary politics and activism
  • Digital marketing and optimization
  • Computational social science
• Digital methods laboratory (for attendees)
  • Design:
    • Netnography for defining the concept of an advertising campaign
    • Exploratory analysis of digital data to identify trends and patterns: quantitative analysis and computational text analysis
  • Testing and optimization:
    • A/B testing to choose the best marketing campaign
    • Methods to test the effectiveness of changes in the communication plan of a social media channel

1. Knowledge and understanding skills: of the opportunities and challenges that digital media pose to social and applied research, research methods for analyzing digital data, and applications of these methods to social research and marketing contexts.

1.1 Students achieve this knowledge through individual and group hands-on practice time in class.

The teaching material prepared by the lecturer in addition to recommended textbooks (such as for instance slides, lecture notes, exercises, bibliography) and communications from the lecturer specific to the course can be found inside the Moodle platform › blended.uniurb.it

Teaching

2 weekly appointments of 3 hours each. Lecture, class discussion and project work.

Innovative teaching methods

Attendance

Attend at least 3/4 of the class and take part in the project work activity.

Assessment

Project work and class discussion.

Verification of learning will be mainly by project work (70%). This will be prepared gradually during the course and delivered according to agreed deadlines (10%). The completed paper produced at the end of the course will be discussed in a presentation to the class, to assess both the student's learning of the content and his or her ability to rework and argue (20%).

Will give rise to excellent evaluations: the student's possession of good critical and in-depth skills; the ability to link together the main themes addressed in the course; the use of appropriate language with respect to the specificity of the discipline. Will give rise to fair evaluations: the student's possession of a mnemonic knowledge of the contents; a relative critical ability and ability to connect the topics covered: the use of appropriate language. Will give rise to sufficient evaluations: the student's attainment of a minimal knowledge of the topics covered, despite some formative gaps; the use of inappropriate language. Will give rise to negative evaluations: difficulty in the student's orientation to the topics addressed in the examination texts; formative gaps; the use of inappropriate language.

The group paper will be subject to verification using the anti-plagiarism system in use at the university. Cases of plagiarism will result in a failing grade.

Disability and Specific Learning Disorders (SLD)

Students who have registered their disability certification or SLD certification with the Inclusion and Right to Study Office can request to use conceptual maps (for keywords) during exams.

To this end, it is necessary to send the maps, two weeks before the exam date, to the course instructor, who will verify their compliance with the university guidelines and may request modifications.

Teaching

Non-attending students will be evaluated on knowledge of the following exam material:

Rogers, R. (2013). Digital methods. MIT press. https://direct.mit.edu/books/book/3718/Digital-Methods

Assessment

Multiple-choice exam (in-person) for non-attending students on the topics covered by the following book:

Rogers, R. (2013). Digital methods. MIT press. https://direct.mit.edu/books/book/3718/Digital-Methods

Disability and Specific Learning Disorders (SLD)

Students who have registered their disability certification or SLD certification with the Inclusion and Right to Study Office can request to use conceptual maps (for keywords) during exams.

To this end, it is necessary to send the maps, two weeks before the exam date, to the course instructor, who will verify their compliance with the university guidelines and may request modifications.