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SOCIAL DATA SCIENCE, THEORIES AND APPLICATIONS Single discipline educational activity
Course Sheet Academic Year of enrolment:
Professor and Collaborators:
Hours of classroom activity:
Prerequisites:
Basic statistical knowledge
Objectives
Contents In order to achieve the expected learning outcomes, the course will illustrate the following didactic contents:
- introduction to the paradigms of research in the social sciences with reference to quantitative or standard and qualitative or non-standard approaches;
- the elements and procedures for structuring and defining the research phases: problematization, definition of the research design and choice of techniques for the collection of empirical data;
- the sample survey: from the theory to the hypotheses, the key concepts, the variables, the sampling plan, the construction of the questionnaire, errors of detection, reliability and validity;
- the techniques of the scales: the Likert scale, the Guttman scalogram, the semantic differential, the sociometric test, one-dimensional and multidimensionality;
- naturalistic observation and participant observation: applications and procedures;
- the survey through the interrogation: types of interview and methods of conducting;
- the analysis of qualitative data: the phenomenological approach, the symbolic interactionism and the grounded theory;
- the computational social research: digital ethnography, social network analysis, machine learning;
- evaluative research in the social sciences: theoretical approaches and application paths;
- the methods for presenting the results.
Extended Syllabus In relation to the cognitive objectives to be achieved and previously illustrated, the course will be divided into four modules:
1. introduction to social research. The first module will address the basic themes of the social research methodology, analyzing the main epistemological perspectives at the base of the debate on the knowability of social reality. In particular, the currents originated from the positivist matrix and the main methodological approaches deriving from constructivism will be taken into consideration. In this first part of the program the different methodological perspectives will be compared in relation to the modalities of the research, the relationship between the scholar and the object of study, the logic and phases of the research, the detection techniques, the nature and the analysis of the data, as well as the presentation of the results.
2. methods and techniques. Once this introductory part has been exhausted, the second module will examine some of the main research techniques used in the social sciences such as:
- the sample survey.
This detection procedure is characterized by the invariance of the interrogation stimulus to a selected sample of the population. In the program the research design will be analyzed, the operation of the concepts in variables, the construction of the questionnaire and the formulation of the questions, the sampling techniques, the methods of administration, the organization of the survey and the collected data, the different types error;
- techniques for the operation of complex concepts.
In particular, the usability and structure of the following scales will be examined in detail: the Likert scale, the Guttman scalogram, the semantic differential, the sociometric test;
- participant observation.
Among the "qualitative" techniques the participant observation together with the qualitative interview is certainly one of the ways to collect information more used not only in anthropology but also in sociology. During the lessons the main operational concepts are provided to successfully conduct a participant observation and to analyze the qualitative material collected;
- detection through interrogation.
The different types of interviews will be presented, from the structured interview to the free interview, the biographical interview, the focus groups. and how to conduct them.
3. Social data science. The third module focuses on the study of data science research tools and techniques for the study of social phenomena in the digital space. In particular, from a theoretical point of view, the basic theories of internet studies will be illustrated. From a methodological point of view, on the other hand, the intention is to define the phases of the empirical research process in the digital space without neglecting the ethical and deontological issues relating to the management of personal data.
Finally, the various qualitative and quantitative computational analysis techniques will be explored, including web surveys; online focus groups; online qualitative interviews; observation; web scraping; social network analysis; automatic text analysis.
Recommended Bibliography Kozinets R.V. (2015) Netnography: Redefined, Sage.
Gerring J. (2011) Social Science Methodology: A Unified Framework, Cambridge University Press.
Alvarez M. (2016) Computational Social Science: Discovery and Prediction, Cambridge University Press.
Methods of Provision
Teaching Methods The course will consist of lectures of a theoretical nature and laboratory activities of an applicative nature. Attendance to teaching activities is not mandatory, however it is strongly recommended.
Evaluation methods Verification of learning:
The exam includes a test structured into open and/or closed questions.
Contacts/More Information E-mail: mara.maretti@unich.it
Students will be received after the lectures. Appointments can be fixed by e-mail