Social media analytics

  • Teaching

    Details

    Faculty Faculty of Science and Medicine
    Domain Computer Science
    Code UE-SIN.08609
    Languages English
    Type of lesson Lecture
    Level Master
    Semester SP-2023

    Schedules and rooms

    Summary schedule Tuesday 14:15 - 17:00, Hebdomadaire (Spring semester)
    Struct. of the schedule 3h par semaine durant 14 semaines
    Contact's hours
    		42

    Teaching

    Responsibles
    • Cudré-Mauroux Philippe
    Teachers
    • Cudré-Mauroux Philippe
    • Khayati Mourad
    Description

    The course will cover techniques and algorithms to analyze the structure of large social networks, and to identify their main properties. We start by introducing the basic concepts of social media analytics. Next, the course will delve into studying the main measures and models used for social media networks and techniques applied to identify communities. Then, the course will cover social media application topics including, diffusion/influence in social networks, crowdsourcing in the web, social recommendation and location-based social media.
    Training objectives

    On successful completion of this course, you will be able to:
    • Analyze a social media network and identity its main properties
    • Understand how to apply clustering techniques to detect communities
    • Apply matrix factorization/decomposition techniques on social media networks
    • How to boost recommendation systems using user social networks
    • Identify the main characteristics of human mobility in social networks and its applications
    Comments

    MSc-CS BENEFRI - (Code Ue: 63091 / Track: T6) The exact date and time of this course as well as the complete course list can be found at http://mcs.unibnf.ch/.

    Course and exam registration on ACADEMIA (not myunifr.ch). Please follow the instructions on https://mcs.unibnf.ch/organization/
    Softskills No
    Off field No
    BeNeFri Yes
    Mobility Yes
    UniPop No
  • Dates and rooms
    Date Hour Type of lesson Place
    21.02.2023 14:15 - 17:00 Cours PER 21, Room C230
    28.02.2023 14:15 - 17:00 Cours PER 21, Room C230
    07.03.2023 14:15 - 17:00 Cours PER 21, Room C230
    14.03.2023 14:15 - 17:00 Cours PER 21, Room C230
    21.03.2023 14:15 - 17:00 Cours PER 21, Room C230
    28.03.2023 14:15 - 17:00 Cours PER 21, Room C230
    04.04.2023 14:15 - 17:00 Cours PER 21, Room C230
    18.04.2023 14:15 - 17:00 Cours PER 21, Room C230
    25.04.2023 14:15 - 17:00 Cours PER 21, Room C230
    02.05.2023 14:15 - 17:00 Cours PER 21, Room C230
    09.05.2023 14:15 - 17:00 Cours PER 21, Room C230
    16.05.2023 14:15 - 17:00 Cours PER 21, Room C230
    23.05.2023 14:15 - 17:00 Cours PER 21, Room C230
    30.05.2023 14:15 - 17:00 Cours PER 21, Room C230
  • Assessments methods

    Written exam

    Assessments methods By rating
  • Assignment
    Valid for the following curricula:
    Additional Courses in Sciences
    Version: ens_compl_sciences
    Paquet indépendant des branches > Specialized courses in Computer Science (Master level)
    Additional programme requirements for PhD studies [PRE-DOC]
    Version: 2020_1/v_01
    Additional programme requirements for PhD studies (Faculty of Science and Medicine) > Specialized courses in Computer Science (Master level)
    Computer Science [3e cycle]
    Version: 2015_1/V_01
    Continuing education > Specialized courses in Computer Science (Master level)
    Computer Science [POST-DOC]
    Version: 2015_1/V_01
    Continuing education > Specialized courses in Computer Science (Master level)
    Digital Neuroscience (Specialised Master) 120 [MA]
    Version: 2023_1/V_01
    sp-MSc in Digital Neuroscience, compulsory courses (practical courses, projects, seminars) > sp-MSc in Digital Neuroscience, compulsory courses (from AS2023 on)
    MSc in Computer science (BeNeFri)
    Version: 2023_1/V_01
    MSc in Computer science (BeNeFri), lectures, seminars and Master thesis > T6: Data Science
    Ma - Accounting and Finance - 120 ECTS
    Version: 2024/SP_V01_DD_Caen
    UniFr courses > Modules "Data Analytics" and "Audit et Fiscalité": min. 2 courses > DAT: Data Analytics
    Ma - Accounting and Finance - 90 ECTS
    Version: 2021/SA_V01 Dès SA-2024
    Course - 72 ECTS > Modules "Data Analytics" and "Audit et Fiscalité": min. 3 courses > DAT: Data Analytics > Elective courses
    Ma - Business Communication : Business Informatics - 90 ECTS
    Version: 2020/SA_V02
    Courses - 60 ECTS > Option Group > Information Management > Cours > Modules management > DAT: Data Analytics
    Courses - 60 ECTS > Option Group > Information Management > Cours > Module Wirtschaftsinformatik > TMD: Technologies and Modelling for Digitalization
    Courses - 60 ECTS > Option Group > Information Management > Cours > Module Informatik > Data Science
    Ma - Business Informatics - 90 ECTS
    Version: 2020/SA-v01
    Classes - min. 45 ECTS > Module IT and IT Management > TMD: Technologies and Modelling for Digitalization
    Classes - min. 45 ECTS > Module IT and IT Management > Data Science
    Classes - min. 45 ECTS > Modules management - max. 15 ECTS > DAT: Data Analytics
    Classes - min. 45 ECTS > Modules IT Management - min. 22 ECTS > TMD: Technologies and Modelling for Digitalization
    Ma - Data Analytics & Economics - 90 ECTS
    Version: 2020/SA-v01
    Courses min 63 ECTS > Mandatory Modules (45 to 63 ECTS) > Module I: Data Analytics (Data)
    Ma - International and European Business - 90 ECTS
    Version: 2021/SA_v01 dès SA-2024
    Courses > Modules > One complete module taken from the following list > DAT Module validation element group > DAT: Data Analytics > Elective courses
    Courses > Modules > Elective courses of the management modules > Elective courses of the management modules > Elective courses for the Master in management
    Ma - Management - 90 ECTS
    Version: 2021/SA_v03 dès SA-2024
    Courses: min. 72 ECTS > Modules - min 54 ECTS > Minimum of 3 modules with a minimum of 18 ECTS and 2 core courses > DAT Module validation element group > DAT: Data Analytics > Elective courses
    Courses: min. 72 ECTS > Modules - min 54 ECTS > Elective courses taken outside a validating module > Elective courses in the management modules > Elective courses for the Master in management
    Ma - Marketing - 90 ECTS
    Version: 2021/V03 dès SA-2024
    Courses - 72 ECTS > Complementary module > DAT Module validation element group > DAT: Data Analytics > Elective courses
    MiMa - Business Informatics - 30 ECTS
    Version: 2020/SA_V01
    Cours > Module Informatik > Data Science
    Cours > Module Wirtschaftsinformatik > TMD: Technologies and Modelling for Digitalization
    Cours > Modules management > DAT: Data Analytics
    MiMa - Data Analytics - 30 ECTS
    Version: 2020/SA-v01
    À choix 9 crédits ECTS > Data Science
    À choix 9 crédits ECTS > TMD: Technologies and Modelling for Digitalization
    MiMa - Gestion d'entreprise - 30 ECTS
    Version: 2021/SA_V01
    Elective courses - 30 ECTS > DAT: Data Analytics