Machines of Knowledge
Volledige vakbeschrijving
This course introduces students to the transformation of the World Wide Web from an information space with a limited number of content creators to a complex network of dynamic knowledge sites to which all users can contribute. These changes in how content is generated, shared, and delivered come with new economic, ethical and legal challenges.
On the theoretical level, this course enables students to discuss these challenges from (data) feminist, postcolonial and public spheres perspectives. In terms of methods, the course introduces students to the basic of computational text analysis (“distant reading”). Students learn how to collect their own text corpus from the web and how to analyse it with text analysis software that highlights word frequencies, word co-occurences and narrative trends.
We explore different data sets to critically reflect on how users interact online, how trending topics arise, and how digital communities are formed.
Doelstellingen van dit vak
By the end of this course, students will be able to problematize the curation, analysis and preservation of web-based content and to assess the role of World Wide Web in the production of knowledge. Students will be able to harvest digital data and to analyse them using distant reading and data visualisations. They will also learn how to apply three important theoretical frameworks. The technical skills acquired in this course prepare students for further studies and research, but are equally useful for professional careers in the media and (social media) marketing.
Aanbevolen literatuur
- D’Ignazio, C. and Klein, L. (2020). Data Feminism. MIT Press.
- Fuchs, C., Hofkirchner, W., Schafranek, M., Raffl, C., Sandoval, M., & Bichler, R. (2010). Theoretical foundations of the web: cognition, communication, and co-operation. Towards an understanding of Web 1.0, 2.0, 3.0. Future Internet, 2(1), 41-59.
- Michael A. Peters & Tina Besley (2019) Digital archives in the cloud: Collective memory, institutional histories and the politics of information, Educational Philosophy and Theory, 51:10, 1020-1029.
- Mirowski, P. (2018). The future (s) of open science. Social studies of science, 48(2), 171-203.
- Sinclair, S. and Rockwell, S. (2016). Text Analysis and Visualization: Making Meaning Count, In S. Schreibman, R. Siemens, and J. Unsworth (Eds.) A New Companion to the Digital Humanities (pp. 274–90). Wiley Blackwell.
- Tong, J. (2015). The formation of an agonistic public sphere: Emotions, the Internet and news media in China. China Information, 29(3), 333–351.
- See the course book for required and recommended reading.