IoTViz: Visualizing emerging topics in the internet of things

Vung Pham, Vinh T. Nguyen, Tommy Dang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

The »Internet of Things» is changing the way companies operate and consumers behave. Therefore, it is essential to capture trends in »Internet of Things». This paper proposes IoTViz, a visual analytics tool for analyzing »Internet of Things» news on social media. The principal aim of IoTViz is to observe the dynamic behavior of topics along with their proximity to other dimensions such as user comments and ratings in multiple coordinated views. IoTViz provides an interactive exploration of the IoT topics and supports of a range of interactive features, such as linking and filtering, allowing users to narrow down events of interest quickly. It is interesting to filter and visualize IoT news regarding the individual organization, e.g., user opinions/ratings regarding a company or its products.

Original languageEnglish
Title of host publicationProceedings - 2018 IEEE International Conference on Big Data, Big Data 2018
EditorsYang Song, Bing Liu, Kisung Lee, Naoki Abe, Calton Pu, Mu Qiao, Nesreen Ahmed, Donald Kossmann, Jeffrey Saltz, Jiliang Tang, Jingrui He, Huan Liu, Xiaohua Hu
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4569-4576
Number of pages8
ISBN (Electronic)9781538650356
DOIs
StatePublished - Jan 22 2019
Event2018 IEEE International Conference on Big Data, Big Data 2018 - Seattle, United States
Duration: Dec 10 2018Dec 13 2018

Publication series

NameProceedings - 2018 IEEE International Conference on Big Data, Big Data 2018

Conference

Conference2018 IEEE International Conference on Big Data, Big Data 2018
CountryUnited States
CitySeattle
Period12/10/1812/13/18

Keywords

  • Internet of Things
  • IoT
  • coordinated multiple views
  • hacker news
  • social media
  • word clouds.

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