Successful collaboration begins with a shared language, hence the need for a glossary. This joint effort of contributors from several teams ensures, on the one hand, terminological and conceptual coherence across not only our theoretical approaches, but also the qualitative case studies and quantitative research conducted in OPPORTUNITIES. On the other hand, our glossary facilitates communication between the academic side of the project and the fieldwork conducted by NGOs, uniting our teams working from Austria, Belgium, France, Germany, Ghana, Italy, Mauritania, the Netherlands, Portugal, Romania and Senegal.

For more information about the Structure and Objectives of the Glossary, click here...)

Social Network Analysis involves the representation of individuals and how they relate to each other. Preceding the age of the Internet, this involved the use of sociograms, whereby the application of methods like in-depth interviews were used to identify ties between individuals. Social network analysis involves a methodological challenge. A method needs to be found to identify relationships between individuals. This methodological challenge has disappeared in the use of Twitter data, as foreseen OPPORTUNITIES, because Twitter data contain information on who follows whom and who retweets messages from others. Hence the nodes of activity will be identified and potential filter bubbles can be identified, especially when there is a large amount of tweeting and retweeting going on between certain individuals.

⇢ see also Filter bubble

Category: A

Work Package: 2, 4, 5

[DC / LH / SM]