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.
|Title of host publication||Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018|
|Editors||Yang 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|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Number of pages||8|
|State||Published - Jan 22 2019|
|Event||2018 IEEE International Conference on Big Data, Big Data 2018 - Seattle, United States|
Duration: Dec 10 2018 → Dec 13 2018
|Name||Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018|
|Conference||2018 IEEE International Conference on Big Data, Big Data 2018|
|Period||12/10/18 → 12/13/18|
- Internet of Things
- coordinated multiple views
- hacker news
- social media
- word clouds.