Studying at the University of Verona
Here you can find information on the organisational aspects of the Programme, lecture timetables, learning activities and useful contact details for your time at the University, from enrolment to graduation.
Study Plan
The Study Plan includes all modules, teaching and learning activities that each student will need to undertake during their time at the University.
Please select your Study Plan based on your enrollment year.
1° Year
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2° Year activated in the A.Y. 2022/2023
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1 module among the following (1st year: Big Data epistemology and Social research; 2nd year: Cybercrime, Data protection in business organizations, Comparative and Transnational Law & Technology)
2 courses among the following (1st year: Business analytics, Digital Marketing and market research; 2nd year: Logistics, Operations & Supply Chain, Digital transformation and IT change, Statistical methods for Business intelligence)
2 courses among the following (1st year: Complex systems and social physics, Discrete Optimization and Decision Making, 2nd year: Statistical models for Data Science, Continuous Optimization for Data Science, Network science and econophysics, Marketing research for agrifood and natural resources)
2 courses among the following (1st year: Data Visualisation, Data Security & Privacy, Statistical learning, Mining Massive Dataset, 2nd year: Machine Learning for Data Science)
Legend | Type of training activity (TTA)
TAF (Type of Educational Activity) All courses and activities are classified into different types of educational activities, indicated by a letter.
Social research (2021/2022)
Teaching code
4S009087
Teacher
Coordinator
Credits
6
Language
English
Scientific Disciplinary Sector (SSD)
SPS/07 - GENERAL SOCIOLOGY
Period
Secondo semestre dal Mar 7, 2022 al Jun 10, 2022.
Learning outcomes
The course aims to offer students an overview of the main paradigms of social research, in order to identify the solutions proposed by these paradigms for ontological, epistemological and methodological questions related to social research. The course is also aimed at providing students with a general framework of the main quantitative and qualitative research techniques, linking them to the specific research questions for which their application is particularly relevant. Finally, the course aims to provide a presentation of the Social Network Analysis (SNA) techniques, in order to train students to the relational analysis of social reality. At the end of the course the student has to show to have acquired the following skills: -ability to identify the most effective social research strategy to deal with a cognitive problem -ability to use, with competence and appropriate language, the techniques of Social Network Analysis (SNA), finalizing them to the operational definition of social reality as a network of relationships and to the identification of the mechanisms that take place in it.
Program
The course will provide students with the ability to learn and apply the qualitative research method, quantitative research techniques and SNA in the field of social research.
The program is divided into the following modules:
Qualitative social research
Quantitative social research
SNA
Big data and social research
Each research method will be dealt with a theoretical and practical point of view. They will be applied to analyse specific empirical research questions.
To gain experience with the practical application of these techniques, students will practice using the software most commonly applied in social research.
The course will combine theoretical lectures, data analysis activities and practice in the interpretation of the outputs obtained.
Bibliography
Examination Methods
The final assessment mark will combine the following three elements:
1) Practical activities of data analysis and interpretation of the outputs (30%)
2) A written assignment dealing with data analysis (min. 2000 words) (30%)
3) Oral examination (40%)