Agneessens has published on a variety of topics related to social networks, including measures of centrality, statistical models, ego-networks and social support, two-mode networks, negative ties, multilevel networks and issues related to data collection. He has also applied social network analysis to understand the antecedents and consequences of interactions among employees, especially within teams.
Together with Martin Everett, he was a guest editor for a special issue on “Advances in Two-mode Social Network Analysis” in the journal Social Networks. Together with Nick Harrigan and Joe Labianca, he guest-edited a special issue on “‘Negative and Signed Tie Networks”’.
He has taught numerous introductory and advanced social network courses and workshops over the last 15 years. Together with Steve Borgatti, Martin Everett and Jeff Johnson, he co-authored the book Analyzing Social Networks with R (Sage, 2022).
You can visit his university webpage here.
You can visit his personal webpage here.
Introduction to Social Network Analysis
The field of social network analysis consists of a vocabulary of theoretical and mathematical concepts for investigating network phenomena, along with a distinctive data model and set of methodologies for collecting and analyzing network data. This course provides an overview...View Details