Artificial intelligence is being applied in a wide variety of areas and has generated a lot of attention over the past few years. Keeping up to date with the advances in this broad field is challenging because of the sheer volume of scientific output. This blog post provides an interactive overview of the most impactful recent AI research through a combination of text mining and network analysis.
Data and Search Strategy
The data used for this analysis was collected using The Lens, a free and open website which serves and integrates scholarly and patent data. The search strategy was quite straightforward: we focused on scientific publications which mention “artificial intelligence”, its subdomains “machine learning” or “deep learning” or the term “neural network” in their titles, with a publication date in 2018. The initial dataset consisted of 7139 documents. To focus on the most impactful articles, the data was then filtered to only include articles with 2 or more citations. This leads to a final dataset of 3676 articles.
The number of citations received by an article can be seen as a key indicator of its overall impact. All articles in the filtered dataset have gathered citations already, despite their relatively short publication lifespans. In this analysis, we see these articles as constituting the ‘state of the art’ in AI research based on the impact they’ve had within a short time frame.