Digital Methods


Winter Term 2021/2022

Course Objectives and Content:

The course will provide an introduction to linear mixed-effects models (LMMs) in R. It will start by discussing the linear model. An important topic in LMMs are contrasts, which provide the way to encode hypotheses about factors in linear (mixed effects) models. Therefore, the course will provide a detailed discussion of contrast coding, and will introduce a powerful way to encode any linear hypotheses about factors into contrasts by using the generalised matrix inverse, which can be easily implemented using the R package hypr. The course will also cover the coding of covariates (i.e., continuous predictor variables). Based on the knowledge about contrasts, the second day will provide an introduction to the LMM, it will discuss fixed effects and variance components, and how they can be estimated in R using the lmer function. Moreover, we will treat the important question of how variance components and correlation parameters can be selected to achieve parsimonious LMMs. In case there is interest and enough time, we can moreover discuss power analyses for LMMs using the design R package.

The full information can be found in the Syllabus.



Prof. Dr. Daniel Schad

Daniel Schad is University Professor for quantitativ methods at the Health and Medical University Potsdam. His three main interests are in methods, in lower- and higher-level processes in reading, and in computational psychiary / decision-making.





Winter Term 2020/2021

Course Objectives and Content:

The course aims to provide participants with a theoretical and methodological toolkit enabling them to understand our digital consumer societies. The course contains a social-sciences informed discussion of algorithms, datafication & platformization as well as epistemological discussions on the use of digital data for doing consumer research. Furthermore, it will link the theoretical part with practical work with creative digital methods. This includes data collection and analysis using a combination of quantitative (network analysis with Gephi, automated content analysis with KH Coder) and qualitative interpretive methods (visual content analysis, semiotic, and discourse analysis). It will be a online combination of Lecture, Discussion, hands-on exercises.

The reading list can be found in the Syllabus. 





Prof. Dr. Joonas Rokka

Joonas Rokka is Professor of Marketing and the Director of Lifestyle Research Center at the EM Lyon Buisinnes School. His research is on branding, consumer experience, lifestyle, digital media, and creative visual research.





Massimo Airoldi, PhD
Assistant Professor
EM Lyon Business School

Massimo AIROLDI is Assistant Professor of Digital Marketing and holds a PhD in Sociology and Methodology from the University of Milan. His main research interests are: digital research methods, consumer behaviour, social media platforms and Big Data. He also is an active member of the Lifestyle Research Centre.




Syllabus 2020/2021

Winter Term 2019/2020

Course Objectives and Content:

This course is designed to enable students to situate Digital Methods historically and epistemologically. Furthermore, students will acquire the ability to practically use digital methods and to critically evaluate its ethical implications.

The course opens with a discussion of how to repurpose digital "methods of the medium" for social and cultural scholarly research, including its limitations, critiques and ethics. Subsequently participants are trained in using digital methods in hands-on sessions. How to use crawlers for dynamic URL sampling and issue network mapping? How to employ scrapers to create a bias or partisanship diagnostic instrument? We also consider how to deploy online platforms for social research. How to transform Wikipedia from an online encyclopedia to a device for cross-cultural memory studies? How to make use of social media so as to profile the preferences and tastes of politicians’ friends, and also locate most engaged with content? How to make use of Twitter analytics to debanalize tweets, and provide compelling accounts of events on the ground? Finally, the course turns to the question of employing web data and metrics as societal indices more generally.


Richard Rogers

Prof. Dr. Richard Rogers

Richard Rogers is University Professor and holds the Chair in New Media & Digital Culture at the University of Amsterdam. He is also Director of the Govcom.org Foundation (Amsterdam) and the Digital Methods Initiative.



Reading List:

Digital Methods - Rogers

Richard Rogers (2013): Digital Methods

In Digital Methods, Richard Rogers proposes a methodological outlook for social and cultural scholarly research on the Web that seeks to move Internet research beyond the study of online culture. It is not a toolkit for Internet research, or operating instructions for a software package; it deals with broader questions. How can we study social media to learn something about society rather than about social media use? Rogers proposes repurposing Web-native techniques for research into cultural change and societal conditions. We can learn to reapply such “methods of the medium” as crawling and crowd sourcing, PageRank and similar algorithms, tag clouds and other visualizations; we can learn how they handle hits, likes, tags, date stamps, and other Web-native objects. By “thinking along” with devices and the objects they handle, digital research methods can follow the evolving methods of the medium.


Doing Digital Methods - Rogers

Richard Rogers (2019): Doing Digital Methods

Teaching the concrete methods needed to use digital devices, search engines and social media platforms to study some of the most urgent social issues of our time, this is the essential guide to the state of the art in researching the natively digital. With explanation of context and techniques and a rich set of case studies, Richard Rogers teaches you how to:

· Build a URL list to discover internet censorship
· Transform Google into a research machine to detect source bias
· Make Twitter API outputs comprehensible and tell stories
· Research Instagram to locate ‘hashtag publics’
· Extract and fruitfully analyze Facebook posts, images and video



Syllabus 2019/2020


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