Influencers Among Computer Scientists

In the realm of computer science, the concept of influencers has emerged similarly to how social media figures gain prominence, with significant attention given to authors who produce highly regarded articles. The DBLP computer science bibliography serves as an extensive resource for identifying influential computer scientists through citation analysis. By employing the PageRank algorithm, which assesses influence based on citation frequency and the prominence of citing authors, a network of around half a million authors and nearly 12 million interactions is analyzed. This method, implemented using Memgraph's open-source MAGE project, reveals notable figures in the field, such as Prof. Jure Leskovec, a key contributor to network analysis. The process demonstrates the power of PageRank in evaluating author influence, highlighting both its effectiveness with static data and the challenges posed by dynamic data flows, while suggesting the potential of online algorithms for real-time analysis. The discussion underscores the value of graph analytics for understanding influence dynamics in academic communities and encourages exploration of other algorithms within the MAGE library.