Inria Project Lab iCODA – Page 3 – Knowledge-mediated Content and Data Analytics

iCODA, where data and content meets knowledge for journalism!

One of today’s major issues in data science is the design of algorithms that allow analysts to efficiently infer useful information and knowledge by collaboratively inspecting heterogeneous information sources, from structured data to unstructured content. Taking data journalism as an emblematic use-case, the goal of the project is to develop the scientific and technological foundations for knowledge-mediated user-in-the-loop collaborative data analytics on heterogenous information sources, and to demonstrate the effectiveness of the approach in realistic, high-visibility use-cases. The project stands at the crossroad of multiple research fields—content analysis, data management, knowledge representation, visualization—that span multiple Inria themes, and counts on a club of major press partners to define usage scenarios, provide data and demonstrate achievements.

iCODA members involved in the Sprint DataPol event!

Members of the iCODA consortium got involved in the Sprint DataPol organized at Science Po Paris on December 2017.This event gathered journalists, computer scientists, designers and experts in political science over 3 days around the study of large pools of data produced during the last presidential elections in France: political programs, web sites of the main candidates, countless tweets from and about the candidates were made available and analyzed by a number of teams, each investigating a different angle. AFP, Les Décodeurs du Monde and Inria’s Linkmedia research team jointly took part in a use-case studying the propagation of fake news in social networks to gain insight on the mechanisms required to track and debunk fake news. A quick overview of the main findings was published by Adrien Sénécat on the Decodex blog.