The Ebb and Flow of Controversial Debates on Social Media

Northern Bytes

By Kiran Garimella and Michael Mathioudakis

Our recent paper titled ‘The Effect of Collective Attention on Controversial Debates on Social Media’ (arXiv link) won the best student paper award at the 9th ACM Web Science conference held in Troy, New York.

The paper studies the evolution of long-lived controversial debates on Twitter – i.e., discussions on topics such as ‘gun control’ or ‘abortion’, that reveal a split of opinion between people who support different sides of the argument.

The main goal of this work is to study dynamic aspects of controversial debates — in particular: (i) whether controversy around the debates has increased over time; and (ii) whether controversy increases or decreases when major associated events occur.


The dataset consists of an 1% sample of Twitter of all tweets generated between September 2011 and September 2016, as published by Twitter and stored on the Internet Archive (

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At PyCon Finland

Yesterday, I attended PyCon Finland as a speaker. Kiran and I gave a talk on using networkx to visualize interactions on Twitter. The talk was aimed at beginner / intermediate-level programmers and we described, essentially, how we produced the plots that appear in our work¹ on polarization on social media.

The Jupyter notebook for our slides is here.

Update: The video of our talk is posted on YouTube.

In a parallel session, Clemens also presented coding material from his masters thesis on text classification.

¹Garimella K, De Francisci Morales G, Gionis A, Mathioudakis M., Quantifying controversy in social media. InProceedings of the Ninth ACM International Conference on Web Search and Data Mining 2016 Feb 8 (pp. 33-42). ACM.