TopicTracker: A Platform for Topic Trajectory Identification and Visualisation

TL;DR

TopicTracker is an R-based platform that visualizes the evolution and relationships of topics over time, integrating topic profiles and evolution strength data for comprehensive analysis.

Contribution

It introduces a software platform that combines multiple facets of topic evolution into a unified visualization tool, addressing the lack of usable software for topic trajectory analysis.

Findings

Provides a visual platform for topic evolution analysis

Integrates multiple facets of topic dynamics

Available as open-source R software

Abstract

Topic trajectory information provides crucial insight into the dynamics of topics and their evolutionary relationships over a given time. Also, this information can help to improve our understanding on how new topics have emerged or formed through a sequential or interrelated events of emergence, modification and integration of prior topics. Nevertheless, the implementation of the existing methods for topic trajectory identification is rarely available as usable software. In this paper, we present TopicTracker, a platform for topic trajectory identification and visualisation. The key of Topic Tracker is that it can represent the three facets of information together, given two kinds of input: a time-stamped topic profile consisting of the set of the underlying topics over time, and the evolution strength matrix among them: evolutionary pathways of dynamic topics, evolution states of the topics, and topic importance. TopicTracker is a publicly available software implemented using the R software.