Introduction to Social Science Computing (SSC) Course Overview PDF

Faculty of Economics and Political Science The Department of Socio-computing Applications of Social Science Computing in Modern Information Societies 1 Introduction to Social Science Computing (SSC) 1 a...

Faculty of Economics and Political Science The Department of Socio-computing Applications of Social Science Computing in Modern Information Societies 1 Introduction to Social Science Computing (SSC) 1 and course overview 1  Important notes - All lectures’ materials will be available on Thinqi and any additional information will be announced through lectures/sections. - Do not use previous terms’ material, as updates are done in the content. - Office hours: Mon, Wed 11:00-12:00 (Staff room-2nd floor the same lectures’ building). - Email’s messages are welcomed only for urgent issues, otherwise, contacting me should be during the lectures’ and /or office hours. - Attending both lectures and sections is crucial as there will be pop-up quizzes in both. 2  outline 1- Social Science Computing (SSC). Types of models. SSC new computational models. 2- Course objective and content. 3  1- Social Science Computing (SSC) 4  Faculty of Economics and Political Science Economics Statistics Political Science Socio-computing Public Administration 5  What does SSC mean to you?? Social Science Computing 6  Social sciences Social sciences concerned of studying the societies, the individual behaviour, and the interactions between the individuals in these societies. Example of social sciences are: ✓ Economics ✓History ✓Political science 7 ✓Sociology  Computational science Computational is a methodology that allow the study of various phenomena, by application of computational and numerical techniques to solve large and complex problems. Why using computational and numerical techniques ??????? Computer 8  Computational science Computational science builds models (a representation of system using general rules and concepts) that allow to: better understand; make predictions; of the phenomena be ready to any changes that may occur. 9  Computational science Computational science is not computer science. Computer science is a branch of science that includes all aspects of a computer system including computer software and hardware. Computational science is about the use of computer by applying computational and numerical techniques, for example, by modeling and simulating of the real world. 10  Social Sciences Computing (SSC) chemistry Biology physics Logic Statistics Natural Mathematics Sciences Formal Political Sciences Science History Economics Computer Science Computational Social Sociology Science SSC Sciences Psychology SSC is interdisciplinary field at the intersection of the social sciences, and computational science. 11 Types of models: 1- Conceptual model 12 Types of models: 1- Conceptual model Example1 Heat from the Sun causes water on Earth (in oceans, lakes etc) to evaporate (turn from liquid into gas) and rise into the sky. This water vapor collects in the sky in the form of clouds. Water falls from the sky in the form of rain, snow etc, this process is13 called precipitation. Types of models: 2- Mathematical model It is a description of a system using mathematical concepts and language. 14  Exercise Develop a conceptual model to summarize the phases of human life. 15 Types of models: 3-Physical model It is a smaller or larger physical copy of an object. You can touch and see, the object may be small (an atom) or large (Solar System). 16 Types of models: 4- Computational model It is the application of computers to advance science. Example: Social simulation (System Dynamics Models, Queueing Models, Agent-Based Models, ………) 17  Social Sciences Computing: new computational models Social Management Social data Social Networks Information System science Simulation Analysis (SNA) (MIS) 18  Social Sciences Computing: Self reading new computational models Social data science Social data science: Social data science uses programming skills and statistical tools to work with social data. 19  Social Sciences Computing: Self reading new computational models Social Simulation Social simulation: Is the application of computer-based methods and technologies to replicate human social behavior in various environments and scenarios. Researchers design the program to model a social situation and then observe the behavior of individuals when the program runs. 20  Self Social Sciences Computing: reading new computational models Social Networks Analysis (SNA) Social network analysis (SNA) is the measuring of relationships and flows between people, groups, computers, and other connected entities. In SNA, the nodes in the network are the people and groups while the links show relationships or flows between the nodes. 21  Self Social Sciences Computing: reading new computational models Management Information System( MIS) Management Information System (MIS): is a computer-based system that provides managers with the tools to efficiently manage departments within an organization. 22 23  Complexity of social phenomena Social phenomena are complex ones. They are difficult to predict and treat using the traditional methods of analysis. 24  Complexity of social phenomena Complex social phenomena are characterised by ▪ multidirectional connections of the elements within a system and between a system and its environment. ▪ accelerated diffusion of phenomena, behaviours and cultural feature. 25  Complexity of social phenomena Computational social science enables us to handle complex phenomena and to invent models that reflect the diversity and complexity of the society. 26  2- Course objective and content 27  Course objective The objective of this introductory course is to give an introduction for the information systems through addresses the main concepts of computer and information systems. Why “ Information systems”?? Next lecture 28  Course objective This introduction is to be done by covering the following topics: 29  Course content Part 1: An introduction to Social Science Computing. Part 2 : An introduction to information systems. Part 3: Information Technology Concepts: - Hardware and Mobile Devices. - Software and Mobile Applications. - Database Systems and Big Data. - Networks and Cloud Computing. May not be Part 4: Specialized Information Systems: covered - Electronic and Mobile Commerce. - Electronic Governance. 30  Course information Course material: Main: Lectures notes, Lab notes and some textbooks (next slide). Grading: – Final term exam: 50 marks. – Mid term exam: 20 marks. – Classwork (30 marks): 10 marks (Lab’s quizzes), 20 marks (Lecture’s quizzes, pop-up quizzes, attendance). - Lecture’s quizzes:15 marks. - Attendance (Lecture and lab ) through pop-up quizzes :5 marks. Success: 60 and above. Contact information: Office: room 63 -old building-third floor. Email: [email protected] 31 References: Ralph M. Stair and George W. Reynolds, “Principles of Information Systems”, thirteenth edition, 2018. R. Kelly Rainer Jr., Brad Prince and Casey Cegielski, “Introduction to Information Systems ,Supporting and Transforming Business”, Fifth Edition, 2014. 32  Thanks 33