10.5281/zenodo.5796271
https://zenodo.org/records/5796271
oai:zenodo.org:5796271
Kristóf Gyódi
Kristóf Gyódi
0000-0003-2999-8444
University of Warsaw
Łukasz Nawaro
Łukasz Nawaro
0000-0003-1995-4894
University of Warsaw
Michał Paliński
Michał Paliński
0000-0002-0075-3585
University of Warsaw
Intermediary topic modelling analysis results: Mapping the tech world using text mining methods
Zenodo
2021
Human-centric, future, technology, data-driven, policy, collective intelligence, news
2021-12-21
10.5281/zenodo.5796270
https://zenodo.org/communities/ngi_forward
https://zenodo.org/communities/eu
Creative Commons Attribution 4.0 International
This study presents an innovative methodology for analysing technology news using various text mining methods. News articles provide a rich source of information to track promising emerging technologies, relevant social challenges or policy issues. Our goal is to support the Next Generation Internet initiative by providing data-science tools to map and analyse the developments of the tech word.
Based on more than 200 000 articles from major media outlets, we are going to identify widely discussed topics, focusing on emerging technologies and policy issues and dive deeper in selected areas and highlight key focal points of recent developments.
To meet these goals, a number of machine learning techniques are combined. The major steps can be summarised as follows:
● 17 general umbrella topics are explored
● 5 topics are selected for further analysis
● Deep dives are presented with 2D interactive maps
More specifically, the topics selected for the deep dives are:
1. AI and Robots
2. Policy (sums up 3 relevant areas)
3. Media
4. Business
5. Cybersecurity
With the Policy topic grouping together 3 areas: Social media crisis, Privacy and 5G.
European Commission
10.13039/501100000780
825652
NGI FORWARD