@inproceedings{35f4aa2605344d71a7260c7b3c01d4e6,
title = "IoTViz: Visualizing emerging topics in the internet of things",
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.",
keywords = "Internet of Things, IoT, coordinated multiple views, hacker news, social media, word clouds.",
author = "Vung Pham and Nguyen, {Vinh T.} and Tommy Dang",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 IEEE International Conference on Big Data, Big Data 2018 ; Conference date: 10-12-2018 Through 13-12-2018",
year = "2018",
month = jul,
day = "2",
doi = "10.1109/BigData.2018.8622375",
language = "English",
series = "Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "4569--4576",
editor = "Naoki Abe and Huan Liu and Calton Pu and Xiaohua Hu and Nesreen Ahmed and Mu Qiao and Yang Song and Donald Kossmann and Bing Liu and Kisung Lee and Jiliang Tang and Jingrui He and Jeffrey Saltz",
booktitle = "Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018",
}