Welcome to the Internet!

The history of the internet, as well as computational methods to study the internet from a humanities and social sciences perspective.
Welcome to the internet!
Have a look around.
Anything that brain of yours can think of can be found.
We’ve got mountains of content!
Some better, some worse.
If none of it’s of interest to you, you’d be the first.

These are the opening words of the song ‘Welcome to the Internet!’ by Bo Burnham, a product of several decades worth of internet culture.
But what is the internet even? Where did it come from? And how can we critically study its impact on our lives?

This minor is aimed at students outside of ESHCC who are interested in a humanities and social sciences perspective on the internet and research in an environment of mass online data.
The minor takes a two-pronged approach. On the one hand, it aims to develop a deeper understanding of the history of the internet and a critical attitude towards online sources. On the other hand, it introduces hands-on computational skills to help students carry out research on this topic. Key methods that will be taught are text mining and network analysis.
Students approach the hands-on computational question by using the data science language R. This serves a double purpose. By letting students use programming software directly, the minor not only provides students with marketable skills that are in high demand. It also motivates them to develop the independent attitude that is necessary to approach computational research.

Module 1: Welcome to (Critical Histories of) the Internet (1960-2060)
At the end of the course, students can:

• Provide an overview of key milestones in the history of the internet from the 1960s to the present

• Demonstrate differences and inequalities in the dissemination of the internet through time and across the globe since the 1960s

• Demonstrate via historical case studies how the internet is located at the intersection between technology and cultural expression

• Critically analyze online sources, past and present

• Critically evaluate the particularities of their own internet user profiles in a global perspective

Module 2: Text Analysis for Internet Studies
At the end of the course, students can:

• Understand and write basic code in the data science language R

• Understand basic approaches for computational text analysis, and recognize advantages, complications, and limitations

• Understand text analysis methods such as frequency analysis, topic modeling and sentiment analysis

• Obtain (scrape) online textual data from platforms such as social media sites and LexisNexis

• Learn how to analyze, visualize and interpret your own textual data in R

• Apply theories, text analysis concepts and methods to a group research project

Module 3: Network Analysis and Visualizations for Internet Studies
At the end of the course, students can:

• Provide an overview of main theories and concepts on social networks
• Classify and distinguish basic concepts and measures of social network analysis
• Scrape networks from webpages and social media platforms
• Analyze network data by creating visualizations and executing network metrics in R and Gephi
• Interpret and report network visualizations and metrics
• Apply theories, concepts and methods of social network analysis to an independent research project

Prior knowledge :
No prior knowledge is required for this minor. Students who have no prior experience with programming but who would like to develop a further understanding of how it can be used for humanities and social sciences scholarship are actively encouraged to enroll for this minor.

Attendance:
The minor adheres to the attendance policy adopted by the Erasmus School of History, Culture and Communication, as stated in the Teaching and Examination Regulation (TER) (see article 3.5 – Attendance and participation requirements).
Attendance of and active participation in seminars is mandatory. This means that a student can only complete a course, after the student has met the attendance and participation requirements of the mandatory classes. Examiners can decide to apply a form of leniency if they have consulted with the student advisor and extenuating circumstances apply.

Teaching Method
For each of the modules, students will attend weekly seminar sessions .

Teaching Material
Throughout the minor, the following teaching materials will be used:

• Literature : handbook (see module description above for further information)
• Literature : miscellaneous readings shared during class (available for free)
• Software : R / RStudio, Gephi (open source computing language, integrated development environment, open source network visualization tool)

Method of examination
Module 1: Welcome to (Critical Histories of) the Internet (1960-2060)

• Research paper
• Written exam

Module 2: Text Analysis for Internet Studies

• Work-in-progress reflections
• Paper assignment
• Group project
• Group project peer evaluation

Module 3: Network Analysis and Visualizations for Internet Studies

• Weekly in-class multiple choice and lab assignments
• Presentation
• Research report

Composition of final grade
Module 1: Welcome to (Critical Histories of) the Internet (1960-2060)

• Research paper (50% of final grade) (I)
• Written exam (50% of final grade) (I)

Module 2: Programming and Text Analysis for Internet Studies

• Work-in-progress reflections (10%) (I)
• Paper assignment (50%) (I)
• Group project (30%) (G)
• Group project peer evaluation (10%) (I)

Module 3: Network Analysis and Visualizations for Internet Studies

• Weekly in-class multiple choice and lab assignments (20% of final grade) (I)
• Presentation (30% of final grade) (G)

Research report (50% of final grade) (I

https://www.eur.nl/onderwijs/minoren