Studies on Human Behaviour
Welcome to the homepage of the fall 2021 edition of Studies on Human Behaviour, course of the Data Science degree at the University of Trento.




Calendar and presentation links updated!

November 21st, 2021 22:00


Data Collection available to the participants!

November 12th, 2021 11:00


Calendar and presentation links updated!

November 1st, 2021 22:00


Website online!

September 15th, 2021 23:41



This class will start on Monday September 20th.

September 19th, 2021 16:30





Last modification: December 3th, 2021 10:20


The Fall 2021 Edition of the course Studies on Human Behaviour is delivered in the classrooms. We will also provide some complementary asynchonous material


The idea behind this course is that the students do most of the work during the course duration (up to December) because we believe this should yield considerably better results.




Studying human behaviour involves the analysis of real data about people. Data collection is then a crucial part of the whole process. For this reason, the students of the course will be taught and asked to collect data from their own smartphones via an application developed by the Knowdive group, ideally over a period of 2 weeks. Such data is the one that the students will analyse to generate insights for the final examination. In the calendar you can find the dates of the data collection and when the data will be made avilable (dates can still change). More details will be provided by the professors during the first lessons.


Calendar and Material

The course runs from September 20, 2021 till December 13, 2021 with the following schedule:

  • Mondays, time 11:15 - 13:00 (Classroom 10)

  • Wednesday, time 14:15 - 16:00 (Classroom 11)


Always check the official University calendar on Moodle.



Interactive sessions are recorded and made available on the Internet for reference and support to other students. If you do not wish to be recorded, you can organize a meeting with one of the professors.



You might want to read the Instructions to understand how to take the course.


Notice also the titles and structure of the lessons yet to be delivered might change slightly . The rule of the thumb is: if there are links with materials, things won’t change; if there are no links to the materials, titles and content are just suggestions.


Date Id Modality Starts at Zoom Recordings Material Content of Lesson Professor(s)
20 Sep, 2021 L1 11:15 Slides Course Introduction. I. Bison
Slides Course Introduction. Projects organization. F. Giunchiglia
Slides Course Introduction. Planning a project. M. Chierici
Slides Course Introduction. Technical bits. M. Rodas
22 Sep, 2021 L2 14:15 Theory driven vs. Data driven vs. Knowledge Driven I. Bison
15:00 Theory driven vs. Data driven vs. Knowledge Driven F. Giunchiglia
27 Sep, 2021 L3 - - Why Human Behaviour? Why diversity? From a computer science perspective. F. Giunchiglia
29 Sep, 2021 L4 14:15 Why Human Behaviour? Why diversity? From a sociological perspective. I. Bison
Slides How to do a literature review. How to write a research project (1st part). M. Chierici
4 Oct, 2021 L5 11:15 Active data: Questionnaire for synchronic and diachronic data & Type of social data. I. Bison
Slides How to write a research project 2nd Part. M. Chierici
11 Oct, 2021 L6 14:15 - Slides, i-Log video Methods and tools for data collection. Passive data: smartphones or other devices. M. Rodas
13 Oct, 2021 - - - - - - iLog data collection starts. -
13 Oct, 2021 L8 14:15 - Groups: project plan discussion. I. Bison, F. Giunchiglia, M. Chierici, M. Rodas
18 Oct, 2021 L9 - - Slides Data Science Pitfalls. M. Chierici
20 Oct, 2021 L10 14:15 - Slides, Material Instruments for data collection. Capture in-the-time data (diachronic and streaming data). M. Rodas
25 Oct, 2021 L11 11:15 Sample design, sampling, and Field Experiment. I. Bison
27 Oct, 2021 - - - - - - iLog data collection ends. -
27 Oct, 2021 L12 14:15 Sample design, sampling, and Field Experiment; The timing (frequencies) of data collection. I. Bison
3 Nov, 2021 L13 11:15 - Groups: data collection architecture. I. Bison, F. Giunchiglia, M. Chierici, M. Rodas
8 Nov, 2021 L14 14:15 - Groups: data collection architecture. I. Bison, F. Giunchiglia, M. Chierici, M. Rodas
10 Nov, 2021 L15 14:15 The recruitment; Field supervising; Ethical & GDPR aspects. Ronald Chenu Abente Acosta, Ivano Bison
15 Nov, 2021 L16 11:15 - Slides Data platforms for big data. M. Rodas
17 Nov, 2021 L17 14:15 Slides, Material Data visualization in biology. M. Chierici
17 Nov, 2021 - - - - - - Data from the i-Log data collection experiment is made available to the students. (Done!) -
22 Nov, 2021 L18 - - Slides Data cleaning and methods for data preparation. F. Giunchiglia
24 Nov, 2021 L19 11:15 Synchronic and Diachronic statistical models. I. Bison
29 Nov, 2021 L20 - - Slides Data Integration Methodology Structure F. Giunchiglia
01 Dic, 2021 L21 11:15 Slides, Materials Networks and differential network analysis I. Bison, M. Chierici
6 Dec, 2021 L22 14:15 ? Network models. I. Bison
8 Dec, 2021 L23 11:15 - Final groups presentations I. Bison, F. Giunchiglia, M. Chierici, M. Rodas
13 Dec, 2021 L24 11:15 - Final groups presentations I. Bison, F. Giunchiglia, M. Chierici, M. Rodas


Course Objectives and Outcomes

The aim of this course is to study the behaviour of people. The course is data intensive and hands on. It covers all the phases from experiment design, data collection, data preparation and data analysis. After a brief theoretical introduction, the course will consist of running real world experiments, on large amounts of data. The exam will consist of presenting the results of the experiment in a public presentation. This inter-disciplinary course bridges competences in sociology, ethics and computer science.


General Description



Suggested Readings

People interested in knowing more details about what we do in this course can refer to these books:

Mainly about Data Science:

  • Bishop, Christopher M. Pattern recognition and machine learning. springer, 2006.

  • Grus, Joel. Data science from scratch: first principles with python. O'Reilly Media, 2019.

  • VanderPlas, Jake. Python data science handbook: Essential tools for working with data. O'Reilly Media, 2016.


Mainly about systems and frameworks for Big Data:

  • Carpenter, Jeff, and Eben Hewitt. Cassandra: the definitive guide: distributed data at web scale. O'Reilly Media, 2021.

  • Chambers, Bill, and Matei Zaharia. Spark: The definitive guide: Big data processing made simple. O'Reilly Media, 2018.



Prof. Ivano Bison

Prof. Fausto Giunchiglia

Dr. Marcelo Rodas Britez

Dr. Marco Chierici

Examination and Grading

The examination consists in the preparation of a written paper that will be presented at the end of the course in December.


The slots when the paper has to be presented are highlithed in the calendar.


IMPORTANT: You must register to ESSE3 in order to take part to the written exam. The registration (mandatory) concludes the exam.


Collaboration Opportunities

Multiple positions are available as 150h and internships. They should be considered as the first part of a research project and thesis with the Knowdive group. The general activities of the group are listed on the website (, while activities already scheduled and available now can be found at The 150h activities have variable length and are strictly related to software development: for this reason, knowledge of software development with at least onr programming language is a must. All the activities can also be carried on in a remote fashion.


Anyone interested in these opportunities can send an email to, providing already information about preferences in terms of topics or activities (if known). For 150h activities it is important to provide information about known programming languages with the corresponding level, a value in the range [1 - 5] where 1= basic knowledge, 5= advanced knowledge.

The applications to the “150 ore” program can be done at the link: Notice that the deadline for applications for the A.Y 2021-2022 is September 30, 2021