NERDS’ summer sheneanigans continue at ASONAM, in the beautiful and sunny Calabria. Lucio La Cava and Alessia Galdeman held a tutorial on Mining, Modeling, and Analyzing Decentralized Social Media. Alessia Antelmi organized the HyperSci workshop on Theory and Applications of Hypernetwork Science. Luigi Arminio and Daniele De Vinco presented at the PhD Forum. Luca Aiello fulfilled his duties as the conference Program Chair. Luigi won the prize for the best PhD forum contribution!
A tactical squad of 6 NERDS attended this year’s IC2S2 in Philly, and presented 9 works:
We are grateful to the organizers for the great event, and we look forward to IC2S2 coming back to scandinavia in 2025!
A new NERDS co-authored paper is out open-access in the Journal of Spatial Information Science (JOSIS): A shape-based heuristic for the detection of urban block artifacts in street networks, by Martin Fleischmann & Anastassia Vybornova.
a) Bridge, Amsterdam; b) Roundabout, Abidjan; c) Intersection, Kabul; d) Motorway, Vienna. Polygons classified as face artifacts are shown in red, and the OSM street network (without service roads) is shown in black. Face artifacts are polygons enclosed by street network geometries (in the case of OSM, lane centerlines) that do not represent morphological urban blocks, but instead are a result of detailed transportation-focused mapping of the streetscape. Map data (c) OpenStreetMap contributors (c) CARTO
We propose a cheap computational heuristic for the identification of ‘face artifacts’, i.e., geometries that are enclosed by transportation edges but do not represent urban blocks. Sounds cryptic? Just check out the picture – the artifacts (in red) might be painfully familiar to anyone who has worked with street network data. Our proposed heuristic, implemented open-source in momepy, is the first step towards a fully automated street network simplification workflow. Next steps coming up – stay tuned!
This week, Arianna and Anders are representing NERDS at ICWSM in Buffalo, NY, with two freshly-published papers.
Arianna and Anders participated to the first editions of the Computational Social Science Summer School in Como, presenting their work on the COCOONS project. Arianna, Daniele, and external collaborator Maddalena Torricelli also attended the WebSci conference in Stuttgard, presenting an analysis of climate action communication on TikTok [paper], the use of hypergraphs to model opinion dynamics in large-scale social media [poster], and the role of interfaces in shaping human creativity during the interaction with generative AI tools [paper].
Arianna smashed it at ComplexNetworks’23 and delivered the best plenary lightning for the work “Finding Hidden Swingers in the 2022 Italian Elections Twitter Discourse”. The work is the result of a collaboration with Alessia Antelmi and Lucio La Cava, two dear friends of NERDS who visited us earlier this year. Well done, Arianna and team!
NERDS welcomes a new member: Anders Giovanni Møller. Starting today, Anders will be a PhD student working with Luca Aiello on the COCOONS project at the intersection between NLP and complex systems. Anders can boast a long tenure at ITU, and last week he got his Master’s degree in Data Science. He was selected for a keynote address to the whole 2023 cohort of ITU MSc graduates during the graduation ceremony — a very moving and inspiring speech! Welcome, Anders!
Iraklis Moutidis joins NERDS today as a postdoctoral researcher. He will work with Luca Aiello on the COCOONS project. Iraklis got his PhD in Computer Science from the University of Exeter (UK) and he works at the intersection of Machine Learning and Social Network Analysis. Welcome, Iraklis!
We are thrilled to welcome Arianna Pera to NERDS!
Arianna will be a PhD student for 3 years, working with Luca Aiello on the Carlsbergfondet project COCOONS on fostering collective cooperation in online social media to tackle societal dilemmas. Arianna recently got her MSc in Data Science from Università degli Studi di Milano-Bicocca. She will work at the intersection of Network Science and Natural Language Processing. Welcome, Arianna!
Multidimensional tie strength and economic development, by L.M. Aiello, S. Joglekar, and D. Quercia, published in Scientific Reports
For decades, Granovetter’s tie strength has been quantified using the frequency of interaction. Yet, frequency does not reflect Granovetter’s initial conception of strength, which is a mix of social dimensions including exchnage of knowledge and provision of support. We used Natural Language Processing to quantify whether text messages convey expressions of knowledge or support, and applied it to a large conversation network from of Reddit users resident in the United States. Borrowing a classic experimental setup, we tested whether the diversity of social connections of Reddit users resident in a specific US state would correlate with the economic opportunities in that state (estimated with GDP per capita). We found that the combination of diversity calculated on the knowledge and support networks correlates much more strongly with GDP than diversity calculated on a network weighted with interaction frequency (R2=0.62 vs. R2=0.30). We also found that the two types of ties differ in their geographical span. Knowledge ties are long-distance (i.e., connecting people living in far-away states), support ties are mostly created among people living close by. Read more in this blogpost.