Detecting and Tracking The Real-time Hot Topics: A Study on Computational Neuroscience
This work addresses the need for timely topic tracking in computational neuroscience, but it is incremental as it builds on a previous method.
The study tackled the problem of detecting and tracking real-time hot topics in computational neuroscience by analyzing weekly updated article usage data from Web of Science, revealing that hot topics include key technologies like 'fmri' and 'eeg'.
In this study, following the idea of our previous paper (Wang, et al., 2013a), we improve the method to detect and track hot topics in a specific field by using the real-time article usage data. With the "usage count" data provided by Web of Science, we take the field of computational neuroscience as an example to make analysis. About 10 thousand articles in the field of Computational Neuroscience are queried in Web of Science, when the records, including the usage count data of each paper, have been harvested and updated weekly from October 19, 2015 to March 21, 2016. The hot topics are defined by the most frequently used keywords aggregated from the articles. The analysis reveals that hot topics in Computational Neuroscience are related to the key technologies, like "fmri", "eeg", "erp", etc. Furthermore, using the weekly updated data, we track the dynamical changes of the topics. The characteristic of immediacy of usage data makes it possible to track the "heat" of hot topics timely and dynamically.