Studies on Human Behaviour
Welcome to the homepage of the fall 2022 edition of Studies on Human Behaviour, course of the Data Science degree at the University of Trento.

News

Lecture (L9, L10, L11, L12, L15, L16, and L17) Materials updated!

November 15th, 2022 18:00

 

 

Lecture (L5, L6) Materials updated!

October 6th, 2022 11:40

 

 

Calendar updated!

September 30th, 2022 17:30

 

 

Website online!

September 20th, 2022 14:50

 

 

This Course will start on Tuesday September 20th.

September 16th, 2022 14:00

 

 

Last modification: November 15th, 2022 18:00

Instructions

The Fall 2022 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, 2022 till December 13, 2022 with the following schedule:

  • Tuesday, time 14:00 - 16:00 (Classroom 4)

  • Wednesday, time 14:30 - 16:30 (Classroom 11)

 

Always check the official University calendar on Moodle.

 

 

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, 2022 L1 14:00 Course Introduction. I. Bison
Course Introduction. Projects organization. F. Giunchiglia
Slides Course Introduction. Planning a project. M. Chierici
Slides Course Introduction. Technical bits. M. Rodas
21 Sep, 2022 L2 14:30 Theory driven vs. Data driven vs. Knowledge Driven I. Bison
15:30 Theory driven vs. Data driven vs. Knowledge Driven F. Giunchiglia
27 Sep, 2022 L3 14:00 Why Human Behaviour? Why diversity? From a computer science perspective. F. Giunchiglia
28 Sep, 2022 L4 14:30 Why Human Behaviour? Why diversity? From a sociological perspective. I. Bison
Slides Homework How to do a literature review. How to write a research project (1st part). M. Chierici
4 Oct, 2022 L5 14:00 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
5 Oct, 2022 L6 14:30 - Slides, iLog video Methods and tools for data collection. Passive data: smartphones or other devices. M. Rodas
10 Oct, 2022 - - - - - - iLog data collection starts. -
11 Oct, 2022 L7 14:00 - Students Q/A. I. Bison, F. Giunchiglia, M. Chierici, M. Rodas
12 Oct, 2022 L8 14:30 - Groups: project plan discussion. I. Bison, F. Giunchiglia, M. Chierici, M. Rodas
18 Oct, 2022 L9 - - Slides Data Science Pitfalls. M. Chierici
19 Oct, 2022 L10 14:30 - Slides Instruments for data collection. Capture in-the-time data (diachronic and streaming data). M. Rodas
21 Oct, 2022 - - - - - - iLog data collection ends. -
25 Oct, 2022 L11 14:00 Sample design, sampling, and Field Experiment; The timing (frequencies) of data collection. I. Bison
26 Oct, 2022 L12 14:30 Slides L12 Data visualization in biology M. Chierici
01 Nov, 2022 - - - - - - No lecture, holiday. -
2 Nov, 2022 L13 14:00 - Groups: data collection architecture. I. Bison, F. Giunchiglia, M. Chierici, M. Rodas
8 Nov, 2022 L14 14:30 - Groups: data collection architecture. I. Bison, F. Giunchiglia, M. Chierici, M. Rodas
09 Nov, 2022 L15 14:30 Slides The recruitment; Field supervising; Ethical & GDPR aspects. Ronald Chenu Abente Acosta, Ivano Bison
15 Nov, 2022 L17 14:00 Data Cleaning and Methods for Data preparation I. Bison
16 Nov, 2022 L16 14:30 - Slides Data platforms for big data. M. Rodas
17 Nov, 2022 - - - - - - Data from the i-Log data collection experiment is made available to the students. -
22 Nov, 2022 L18 - - Data cleaning and methods for data preparation. F. Giunchiglia
23 Nov, 2022 L19 14:00 Synchronic and Diachronic statistical models. I. Bison
29 Nov, 2022 L20 - - Data Integration Methodology Structure F. Giunchiglia
30 Nov, 2022 L21 14:00 Introduction to network models I. Bison, M. Chierici
6 Dec, 2022 L22 14:30 ? Find regularity, patterns. I. Bison
7 Dec, 2022 L23 14:00 - Final groups presentations I. Bison, F. Giunchiglia, M. Chierici, M. Rodas
13 Dec, 2022 L24 14:00 - Final groups presentations I. Bison, F. Giunchiglia, M. Chierici, M. Rodas

Syllabus

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.

 

 

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, 2022.

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

 

Teachers

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 (http://knowdive.disi.unitn.it/), while activities already scheduled and available now can be found at http://knowdive.disi.unitn.it/work-with-us/. 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 knowdive-positions@disi.unitn.it, 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: https://www.unitn.it/servizi/224/collaborazioni-studenti-150-ore Notice that the deadline for applications for the A.Y 2022-2023 is September 30, 2022