University of Warsaw - Central Authentication SystemYou are not logged in | log in
course directory - help

Digital methods of social research

General data

Course ID: 3502-SCC-CMBS2 Erasmus code / ISCED: 14.2 / (0314) Sociology and cultural studies
Course title: Digital methods of social research Name in Polish: Cyfrowe metody badań społecznych
Department: Faculty of Sociology
Course groups: (in Polish) Przedmioty obowiązkowe, socjologia cyfrowa, 1 rok, stacjonarne, drugiego stopnia
ECTS credit allocation (and other scores): 5.00
Language: Polish
Type of course:

obligatory courses

Mode:

Remote learning

Short description:

The aim of the course is to systematically introduce students to the issues of digital sociology methodology and an in-depth discussion of its most important methods on selected examples.

In particular, the classes will be used to familiarize students with the following issues:

• how to use sociology methods for researching the digital world?

• how does digitization broaden the possibilities of sociological methods and what challenges does it involve?

• how to problematise the phenomena of the digital world (problem-driven approach) and in which respect this approach differs, and under which it complements the approach known under the name big data?

• what ethical problems are associated with the digitization of research?

Classes will be divided into five thematic blocks: 1) netography; 2) on-line questionnaire surveys; 3) analysis of registry data; 4) modeling and simulation; 5) sociological experiment.

Full description:

The digitization of the social world is both a chance and a challenge for sociology. On the one hand, it opened new possibilities for data collection, it allowed to develop existing research methods and create new ones. On the other hand, proven methods are not always easily applied to the digital world, there is often lack of knowledge about the representativeness of collected data, there are no clear rules of inference and it is often forgotten that the amount of available data does not directly translate into relevance and adequacy of formulated conclusions.

Compared to other social sciences, sociology is distinguished by methodological pluralism. The phenomenon can be studied from many perspectives and using multiple methods in a systematic, in-depth and critical manner. The methods used in sociology find application in the study of the digital world. The analyzes in this field confirmed the usefulness of ethnographic observation, in-depth case studies, surveys and sociological experiments.

In many cases, however, it is necessary to rethink methodological assumptions and adapt research methods to the digital environment. Among other things, the method of contact with the respondent has changed - it is only sporadically getting data in face-to-face interaction. Data is more and more often analyzed as a record of the researched activity and not as a result of the investigator's activity. They gain authenticity, but require far-reaching machining. The nature of the collected data has changed - they can not always be clearly assigned to a specific unit, and even if it is possible, the researcher usually does not have access to detailed information about a given unit, which significantly hinders multivariate analyzes. The proportion of data types has changed - definitely more data is audio-video, graphic, or is a digital record of the individual's activity on the Internet. It is also not known which population is represented by the collected data, which makes the inference process difficult. Finally, what is most often emphasized in the literature of the subject, although not necessarily the most important, the number of available data has changed - there are a lot of them. Each of the above factors is also an opportunity and a challenge for sociology.

The aim of the course is to systematically introduce students to the issues of digital sociology methodology and an in-depth discussion of its most important methods on selected examples.

In particular, the classes will be used to familiarize students with the following issues:

• how to use sociology methods for researching the digital world?

• how does digitization broaden the possibilities of sociological methods and what challenges does it involve?• how to problematise the phenomena of the digital world (problem-driven approach) and in which respect this approach differs, and under which it complements the approach known under the name big data?

• what ethical problems are associated with the digitization of research?

Individual blocks:

Digital ethnography - appr. 3 meetings 3 hours each

A qualitative method of analyzing content produced by communities that appear in the digital environment, used for both scientific purposes (eg by sociologists) and commercial (eg in marketing). It is based on non-interventional observation of communication between members of organized communities around - most often - a brand or a selected product, or a given problem (eg illness). The aim of the analysis is to identify the key components of the world experienced by the selected community: the meanings shared during communication, the values with which these meanings relate, the emotions they evoke, and cultural patterns of action, such as consumption. During subsequent meetings we will find out what data the digital environment ethnographer is working on, how to prepare the data for analysis and what to look for during the analysis itself. We will perform two empirical tasks, one connected with the analysis of digital cultures of selected brands, and one focused on the interactions with non-human agents (chatbots).

On-line surveys - appr. 3 meetings 3 hours each

Questionnaire surveys are the most developed and theoretically well-grounded method of collecting data used in sociology. Although the surveys, despite the unquestionable limitations of this method, confirmed their usefulness, with the advent of digitization, some people claimed their end - why to draw individuals and ask questions, since it is relatively easy to collect data on many aspects of the behavior of a very large group of people? However, it quickly turned out that in many respects representative surveys constitute an important complement to big data. The transfer of surveys and the process of collecting data for the Internet also significantly changed the method itself.

As part of the first two meetings, we will look at the issues that determine the strength of the survey: representativeness and the problem of measurement. The next two classes will be devoted to discussing selected examples of combining survey research with big data. We will consider what the complementarity of these tests is and what problems may be associated with combining them. The third block will be devoted to discussing examples of carrying out surveys in the digital environment. In particular, we will look at the issue of non-representativeness of on-line research and selected examples of representative on-line research.

Analysis of registration data - appr. 2 meetings 3 hours each

In recent years, along with the development of IT, there has been a rapid development of social research based on information from administrative registers. Proper preparation for conducting such research requires a good knowledge of the specifics of their methodology. During the course, students will learn about the structure (substantive content and organization) of administrative registers, the issue of creating indicators based on these registers, analytical capabilities based on data derived from them, legal and administrative restrictions on analytical work based on registers, including with mechanisms that protect the privacy of respondents covered by such analyzes.

In addition, the participants will get acquainted with the results of the most important recent research carried out using the registration data in Poland and abroad. As part of the course, they will be able to confront the methodological problems in the project "Integrated Analytical Platform" being launched, in which the University of Warsaw and the Warsaw School of Economics are academic partners of the Ministry of Digital Affairs.

Modelling and simulations (including social network analysis) - appr. 3 meetings 3 hours each

The development of technology, in addition to new ways of obtaining and analyzing data in an automated way, also brought a completely new tool for analyzing social phenomena and processes - it is about modeling and simulations. Within this branch of social research, formal models of certain processes are created, on the basis of which simulations are carried out, the analysis of which allows a better understanding of a given process and its determinants (eg cognitive processes, collective actions, social impact). Under this approach, one looks at society as a system of interacting elements, so that its dynamics leads to new properties at the aggregate level. The goal of the course / module is the introduction to modeling of social processes. Based on selected examples of the application of modeling and simulation, the main principles of this test method will be presented. It is worth adding that this module will also introduce basic concepts and concepts related to the analysis of social networks.

Topics covered: Models, modeling, simulations ; dynamics - concepts typical of dynamic analysis; preferences, strategies; modelling interactions (game theory); simulations in a spatially structured population (cellular automata); simulations in a structured population - (social network analysis)

Sociological experiments - about 8h

Digital methods allow for unprecedented control of variables in the studied population. They also allow very careful selection of stimuli and a greater variety of stimuli and patterns of experiments. A large sample gives the opportunity to use more advanced segmentation, which translates into the possibility of controlling the experimental process rarely found in traditional social sciences.

Topics discussed: 1. Based on data obtained from commercial partners, general principles of experimental schemes (eg BLI), ways of creating stimulus scenarios and issues related to control groups will be presented. 2. The methods of including experimental protocols for mixed researches (eg in the form of BBD as an extension of traditional focus) will be shown. 3. Experimental methods in designing user experience and human-computer interaction. 4. New trends in experimental research and meeting with practitioners.

Bibliography:

Salganik, M. (2017). Bit by Bit: Social Research in the Digital Age. Princeton: Princeton University Press.

Literature for individual blocks:

1) digital ethnography:

Boellstorff, T., B. Nardi, C. Pearce and T.L. Taylor (2012). Ethnography and Virtual Worlds. A Handbook of Method. Princeton: Princeton University Press.

Frömming, S. Köhn, S. Fox and M. Terry (eds.) (2017). Digital Environments Ethnographic Perspectives across Global Online and Offline Spaces, Bielefeld: transcript Verlag

Jemielniak, D. (2013). Virtual wild life. Netography of Wikipedia, the largest project co-created by people. Warsaw: Poltext

2) on-line questionnaire surveys:

Callegaro, Mario, Katja Lozar Manfreda, and Vasja Vehovar. Web Survey Methodology. Sage Publications Ltd, 2015.

Dillman, Don, Jolene Smyth, and Leah Christian. Internet, Mail, and Mixed-mode Surveys. New York: Wiley, 2009.

Groves, R.M., Fowler, F.J., Jr., Couper, M.P., Lepkowski, J.M., Singer, E., and

Tourangeau, R., Survey Methodology. New York: John Wiley, 2004.

Toepoel, Vera. Doing Surveys Online. Sage Publications Ltd, 2015.

3) analysis of registry data:

Jasiński, M., Bożykowski, M., Chłoń-Domińczak, A., Zając, T., Żołtak, M. (2017). Who gets a job after graduation? Factors affecting the early career employment of higher education graduates in Poland. Education, 143 (4), 17-30. https://doi.org/10.24131/3724.170402

Jasiński, M., Bożykowski, M., Zając, T., Styczeń, M., Izdebski, A. (2015). More precisely, more reliable, cheaper. Research based on public registers as an opportunity for social research in Poland. Sociological Studies, 1 (216), 45-72.

Wallgren, A., Wallgren, B. (2007). Register-based Statistics. Administrative Data for Statistical Purposes. Chichester: John Wiley & Sons (selected fragments).

Zając, T., Jasiński, M., Bożykowski, M. (2017). Does It Pay To Be A STEM Graduate? Evidence from the Polish Graduate Tracking System. Center for Studies in Higher Education, 1-9.

Zając, T., Jasiński, M., Bożykowski, M. (2018). Early Careers of Tertiary Graduates in Poland: Employability, Earnings, and Differences between Public and Private Higher Education. Polish Sociological Review, 2, 187-208. https://doi.org/10.26412/psr202.03

4) modelling and simulations:

Baczko-Dombi, A. and Komendant-Brodowska, A. (2013). The theory of rational choice - integration of social sciences. Application of the James Coleman diagram in the analysis of social phenomena. In: P. Ścigaj, and B. Krauz-Mozer (ed.), Research and methodological approaches in science about politics (pp. 339-348). Krakow: Academic Bookstore.

Cioffi-Revilla, C. (2014). Introduction to computational social science. Principles and applications. London, UK: Springer-Verlag (or other work of Cioffi-Revilli)

Jackson, M. O. (2010). Social and economic networks. Princeton university press. (Excerpts)

Learning outcomes: (in Polish)

K_W02 posiada pogłębioną wiedzę na temat wybranych metod i technik badań cyfrowych, ich ograniczeń, specyfiki i obszarów zastosowania

K_W03 posiada pogłębioną wiedzę na temat najważniejszych międzynarodowych i krajowych badań socjologicznych odnoszących się do socjologii cyfrowej

K_W05 rozumie funkcjonujące w świecie cyfrowym mechanizmy i źródła danych, jakie można wykorzystywać albo wygenerować

K_W09 posiada pogłębioną wiedzę o więziach społecznych w środowisku cyfrowym

K_W11 posiada pogłębioną wiedzę o technologiach informacyjnych i algorytmach jako narzędziach odpowiedzialnych za transmisję norm i reguł w społeczeństwie

K_W13 posiada pogłębioną wiedzę na temat praktycznych aspektów prowadzenia projektów badawczych i społecznych związanych z tematyką cyfrowości

K_U01 potrafi samodzielnie zaplanować i prowadzić badania społeczne z zastosowaniem nowoczesnych narzędzi przystosowanych lub stworzonych specjalnie na potrzeby świata cyfrowego

K_U02 potrafi analizować dane ilościowe i jakościowe o charakterze cyfrowym

K_U07 potrafi wyszukiwać, gromadzić i przygotować do analizy za pomocą wybranych narzędzi dane dotyczące określonych zjawisk społecznych

K_K01 jest świadom dylematów etycznych związanych z wykorzystaniem danych cyfrowych

K_K03 potrafi krytycznie selekcjonować dane cyfrowe umożliwiające opracowanie wybranego problemu badawczego

Assessment methods and assessment criteria: (in Polish)

Zajęcia są zaliczane na podstawie punktacji. Maksymalnie można otrzymać 50 pkt.

Skala ocen:

2 - od 0 do 26 pkt.,

3 - od 27 do 35 pkt.,

4 - od 36 do 43 pkt.,

5 - od 44 do 50 pkt.

Każdy z 5 bloków zajęć będzie oceniany oddzielnie. Za każdy blok można otrzymać maksymalnie 10 pkt. Zasady przydziału punktów w ramach danego bloku oraz zasady zaliczenia poprawkowego przedstawią osoby prowadzące.

Nieobecności podlegające usprawiedliwieniu: 2

Przedmiot roczny. Do godzin przeznaczonych na zajęcia w sali (60h) należy doliczyć czas konieczny do przygotowania się do każdych zajęć (czytanie lektur, sporządzanie notatek, prowadzenie analiz) – średnio 5h oraz czas konieczny do przygotowania się do zaliczeń z poszczególnych bloków – 50h

Classes in period "Summer semester 2020/21" (past)

Time span: 2021-02-22 - 2021-06-13
Choosen plan division:


magnify
see course schedule
Type of class: Seminar, 30 hours, 38 places more information
Coordinators: Marek Bożykowski, Mikołaj Jasiński, Maja Sawicka
Group instructors: Marek Bożykowski, Mikołaj Jasiński, Maja Sawicka, Marcin Zaród
Students list: (inaccessible to you)
Examination: Course - Examination
Seminar - Examination
Course descriptions are protected by copyright.
Copyright by University of Warsaw.