‘Echo chambers’ work covered on LeMonde


Kiran, Gianmarco, Aris and I attended the Web Conference in Lyon last week, where we presented our tutorial (link) on polarization on social media, as well as our recent, large-scale study on echo chamber on Twitter (link).
The tutorial was a particularly good opportunity to present a large number of works from the related literature of various disciplines and discuss with the audience. Part of the discussion was reported on Lemonde by William Audureau, who covered the conference for the newspaper.

Link to the Le Monde article: here (in French).
Link to tutorial material: here.
Link to Aalto press release: here.
Link to University of Helsinki‘s post: here.

Best Student Paper award at WSDM

We just heard that our paper on “Balancing Opposing Views to Reduce Controversy” (available on the ACM Digital Library) was nominated for best paper at WSDM 2017.


Update: Cornell received the best paper award – and our paper the best student paper award, with Kiran as first author.

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.


Back from Pisa

Last week I had the opportunity to travel to Pisa and attend the kick-off meeting of SoBigData, a project funded by the Horizon 2020 program of the EU. Aalto participates with two partners in the project – Santo Fortunato from the Complex Networks group and Aris Gionis from the Data Mining Group (to whom I owe my participation).

The consortium consists of many academic partners (from University of Pisa, ETHZ, CNR, TUDelft, Fraunhofer, Sheffield, IMT Lucca, King’s College London, Scuola Normale Superiore — and Aalto). Quite predictably, part of the project will be devoted to research in social data mining and related areas. What’s interesting, however, is that the largest part of the project will be devoted to integrating existing local research infrastructure (e.g. at national level) into a unified European ecosystem. The goal of the project is to build infrastructure to facilitate the sharing of datasets and research findings among European scientists.


Interesting fact about Pisa: with about 90,000 residents, it also hosts about 40,000 students – it’s a big college town.