Corsi di Studio del Dipartimento di Culture, Politica e Società

https://www.didattica-cps.unito.it/do/offerta.pl/Show?_id=mzpm

The main objective of the course is to offer a detailed, though admittedly not exhaustive, overview of social research methods in the digital age of Big Data and mixed methods. By 'methods' is meant the empirical procedures with which plausible answers to interesting questions about social phenomena are formulated.

The course aims to offer theoretical, methodological, statistical and operational elements that are useful for recognising the reasons of interest of a research question and for assessing the most appropriate paths for arriving at plausible and empirically corroborated answers.

More generally, the course broadens and deepens the methodological preparation provided by the preparatory laboratory - optional but strongly recommended - linked to it (Digital Methods Laboratory CPS 0681) and strengthens the skills of sociological analysis of social phenomena related to ICT solutions addressed in the degree course.

KNOWLEDGE AND UNDERSTANDING

By the end of this course, you will know

the basic concepts of social research applied to the analysis of digital semantic data
the phases into which research design is divided in the analysis of digital semantic data
the minimum algebraic and statistical notions necessary to orient oneself in the analysis of digital semantic data
the qualitative skills required to sociologically interpret digital semantic data and to account for this process in a research report

ABILITY TO APPLY KNOWLEDGE AND UNDERSTANDING

By the end of this course, you will be able to

identify the distinct steps involved in retrieving digital semantic data from public online sources
import digital semantic data into software that allows its analysis, following the construction of a text corpus
cleaning and normalising the corpus thus obtained
process a text corpus by applying, at least in an introductory manner, some of the most common techniques for the quantitative analysis of digital semantic data

AUTONOMY OF JUDGEMENT

At the end of the course, you will be able to formulate a judgement on these aspects:

ethics of Big Data, in general, and of digital semantic data, in particular
limits and opportunities of social research with large amounts of digital semantic data

COMMUNICATION SKILLS

At the end of the course, you will master:

a pro vocabulary derived from social research applied to semantic data
a set of narrative strategies for interpreting digital semantic data

LEARNING SKILLS

By the end of this course, you will have the ability to study independently and critically evaluate the different ways of designing and carrying out social research based on digital semantic data.

Each lesson - strictly in-presence - is structured on the mixed model of learning-by-doing. The standard lesson time (3 hours) will be divided into:
- theoretical and methodological parts referring to media content analysis;
- exercises to become familiar with some free analytics platforms (with the support of a tutor present in the classroom together with the lecturer)
- group work, aimed at acquiring skills for the exam.

CHARACTERISTICS OF THE EXAMINATION TEST

The candidate has exactly 45 minutes to complete a quiz with closed questions or with a space to complete.

EVALUATION SYSTEM

Correct answer = 1 point; wrong answer = -0.25; no answer = 0.

RULES

you need to register on the Moodle page of the course to take the test

the test is timed, at the end of the time it will be sent automatically, even incomplete
those who intend to withdraw write it by email to the teacher
the answers given are no longer editable
it is not allowed to go back to consult the previous questions
the test cannot be restarted or paused
do not click repeatedly on "forward" in case of slow connection, because the skipped questions cannot be recovered afterwards

NB: the exercise, practice and group work will start from the first lesson and will be across the following topics:

minimum alignment of social research methodology
from concepts to indices: social media analytics
quantitative analysis of digital semantic data:
the "classical" quantitative semantics
   lexical co-occurrence analysis
   lexical correspondence analysis
   dimensionality reduction techniques of digital semantic data

Salganik M.J., Bit by Bit: Social Research in the Digital Age, Princeton Univ. Press

Tipaldo, G., 2014 L'analisi del contenuto e i mass media, Bologna, Il Mulino.