Model information space dynamics over social networks by combining heterogeneous data representations
SHORT DESCRIPTION
The goal of the project is to develop a prototype, based on existing data sources and tools, aimed at understanding how the information space configures and evolves in social media, for example during a large scale event. The focus is on understanding how different data sources and representations (such as textual, metadata, network, and multimedia) can be integrated to better understand social media data and their dynamics. Possible applications are advanced classification tasks, such as thread and user classification for benign or malign behaviours, and the study of network characteristics and dynamics, such as homophily and content shifts. Proposed based on the Crowd4SDG project.
PROPOSERS
Barbara Pernici, Carlo Bono (DEIB)
name.lastaname@polimi.it
REQUIRED COMPETENCES
Python
Preferred, not mandatory: Data wrangling and analysis, Machine Learning, Data visualization
Results from the multisciplinary project last year
Olimpia Rivera, Juan Felipe Calderon, Paul Planchon, Barbara Pernici, Evaluating the impact of floods on gender equality from social media evidence, 2nd AISWN International Research Workshop on Women IS and Grand Challenges @ICIS, Dec. 2021 link