C8970 - STRUMENTI DI ANALISI QUANTITATIVA PER IL GIORNALISMO E LA COMUNICAZIONE POLITICA

Learning outcomes

The course aims to provide theoretical and methodological tools for analyzing numerical data and understanding its growing role in the production and distribution of information in the digital age. To this end, students will be equipped with a set of interdisciplinary skills spanning journalism, computer science, and statistics. Upon completion of the course, students will be able to understand the relevant scientific literature, the data, and the analysis techniques used therein, and to analyze databases firsthand using statistical software in order to effectively communicate original empirical findings in the fields of data journalism and political communication.

Course contents

The course offers students an overview of the two fundamental components of any scientific process: research design and data analysis. Particular attention will be paid to the application of quantitative tools to the study of public opinion, media consumption, political communication, electoral campaigns, and institutional communication.

The first part of the course (16 hours) focuses on the topic of science as one of the possible approaches to knowledge, the conceptual foundations of scientific research, the issues inherent in the empirical identification of concepts and the operationalization of the properties to be analyzed, the types of variables, data analysis, and the necessary basics of statistics.

In the second part of the course (24 hours), students will delve into one of the main quantitative research tools: the survey. In this part, attending students will be directly involved in the development of survey instruments, their implementation in the field, and the analysis of the collected results using Microsoft Excel software. Through Excel, students will learn the fundamental procedures for data management, indicator construction, descriptive analysis, table production, graphical representations, and result interpretation.

At the end of the course, students will be able to:

- distinguish between different forms of scientific knowledge production;
- formulate an empirically testable research question;
- translate abstract concepts into observable variables;
- design and evaluate a research questionnaire;
- understand the basics of sampling and survey error;
- use Microsoft Excel to organize, describe, and analyze quantitative data;
- critically interpret tables, graphs, and statistical results;
- communicate empirical findings in writing and orally.

Readings/Bibliography

Peter J. Schulz, Nicola Diviani & Maddalena Fiordelli (2025). Empirical Research in Communication Sciences. Foundations, Methods, and Tools. Rome: Carocci.

Attending students:

- Chapters I-VII and X;
- direct experience with surveys and datasets.

Non-attending students:

 - Chapters I-X;
- additional content analysis and experiments to compensate for the lack of laboratory experience.

 

Recommended readings based on the course content will include:

- One or more chapters from the Data Journalism Handbook;
- Recent articles on political polls and digital communication;
- An annual AGCOM report or Reuters Digital News Report.

Teaching methods

The course adopts a teaching method aimed at providing basic theoretical knowledge, as well as its practical application through learning how to use Microsoft Excel. The course is therefore structured in lectures alternating between classroom teaching and laboratory application of theoretical concepts. Students will be involved by the instructor in class exercises, discussions of their respective research interests, and the collective development of research tools. The data collected by the class will then be used by attending students in a research report that forms the basis of the exam.

Assessment methods

The exam format and syllabus vary depending on whether the student is attending or not attending.

Attending Students

Students intending to take the exam as attending students are required to attend at least 80% of the course lectures. They may take the exam as attending students ONLY during the two midterm tests that will be held during the course.

The midterm test (60 minutes) is based on a mix of multiple-choice and open-ended questions, designed to assess understanding of the basic theoretical and methodological concepts. The grade achieved in this first part of the exam contributes 40% of the final grade.

The final test (120 minutes) consists of a laboratory analysis of the original database collected by the class. Students will be assigned one or more research questions related to the topics covered by the survey. Using Excel, students will produce a short, guided analysis sheet in which they present and interpret empirical evidence from the dataset. The exam requires the creation of specific analytical outputs indicated by the instructor (e.g., frequency tables, pivot tables, and graphical representations) and the preparation of a written commentary describing and interpreting the main findings. Particular emphasis will be placed on the ability to select appropriate analytical tools, correctly interpret data, discuss their limitations, and communicate their meaning clearly and effectively. The grade obtained in this second part of the exam contributes 60% to the final grade.

The final grade is therefore the result of the weighted average obtained in the midterm and final exams. Attending students who fail the exam or decide to refuse the grade may retake the exam at any session, following the procedures for non-attending students, and will be assessed according to the procedures for non-attending students.

Non-attending students

The exam is administered exclusively in written form (120 minutes) and consists of a mix of multiple-choice and open-ended questions, designed to assess understanding of the theoretical, methodological, and statistical concepts covered in the course. The exam includes open-ended calculation questions and requires study of the additional chapters related to content analysis (chapter 8) and experimental methods (chapter 9) to compensate for the lack of laboratory experience.

Teaching tools

PC, Excel, slides, video projector

Office hours

See the website of Diego Garzia