TrajectoryVis: a visual approach to explore movement trajectories

Social networks are a dominant data source for sharing, participation, and exchanging information. For example, Twitter is a microblogging site that enables users to express opinions by transmitting brief messages (i.e., Tweets). Tweets can be used to extract information on users' movements or trajectories over time. Information visualization (InfoVis) is helpful to understand, analyze, and make decisions about these trajectories. To better understand and compare existing visual encoding methods in InfoVis, we propose TrajectoryVis, a generic trajectory visualization tool to represent social network datasets (e.g., Twitter). Individual and aggregated trajectories can be visualized using different visual coding approaches. Our approach is assessed using a user and a COVID-19 case study to prove its effectiveness.

Automated summary

Social networks play a prominent role in sharing, participation, and information exchange. To better understand and compare visual encoding methods in information visualization, the researchers propose TrajectoryVis, a versatile tool for visualizing social network data such as Twitter. The tool allows for the visualization of individual and aggregated trajectories using various visual coding approaches. The effectiveness of the approach is demonstrated through a user study and a COVID-19 case study.