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TrajectoryVis: a visual approach to explore movement trajectories.
Fadloun, Samiha; Morakeb, Yacine; Cuenca, Erick; Choutri, Kheireddine.
  • Fadloun S; Laboratoire des Méthodes de Conception de Systèmes (LMCS), Ecole nationale Supérieure d'Informatique (ESI), BP 68M -16 270, Oued Smar, Alger, Algérie.
  • Morakeb Y; Laboratoire des Méthodes de Conception de Systèmes (LMCS), Ecole nationale Supérieure d'Informatique (ESI), BP 68M -16 270, Oued Smar, Alger, Algérie.
  • Cuenca E; Yachay Tech University, Urcuquí, Ecuador.
  • Choutri K; Aeronautical Sciences Laboratory, Aeronautical and Spatial Studies Institute University Blida 1, Blida, Algeria.
Soc Netw Anal Min ; 12(1): 53, 2022.
Article in English | MEDLINE | ID: covidwho-1930588
ABSTRACT
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.
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Full text: Available Collection: International databases Database: MEDLINE Language: English Journal: Soc Netw Anal Min Year: 2022 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Language: English Journal: Soc Netw Anal Min Year: 2022 Document Type: Article