@inproceedings{e60129d2dd41476ba4d0521acd85ee49,
title = "FinanViz: Visualizing Emerging Topics in Financial News",
abstract = "The explosion of social media has paved a way for big data in which entrepreneurs use this data to find out potential customers, market demands, individual behavior, thereby to improve existing products, to create new products according to users' need, or to analyze and evaluate financial risks. The challenges of the heterogeneity and fragmentation of data make it difficult for analysts to fully exploit the benefit of deluge information. Available statistical software lacks customization and address unknown research questions. This paper proposes FinanViz, a visual analytics tool for analyzing financial news on social media. The principal aim of FinanViz is to observe the dynamic behavior of terms/words over time along with their proximity to other terms/words. The tool provides an intuitive, interactive exploration of the financial topics and what events are emerging in which we would argue that it will give hints for financial marketers in the decision making process.",
keywords = "Financial news, community detection, coordinated multiple views, dynamic network, social media, word clouds",
author = "Nguyen, {Ngan V.T.} and Nguyen, {Vinh T.} and Vung Pham and Tommy Dang",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; null ; Conference date: 10-12-2018 Through 13-12-2018",
year = "2019",
month = jan,
day = "22",
doi = "10.1109/BigData.2018.8622097",
language = "English",
series = "Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "4698--4704",
editor = "Yang Song and Bing Liu and Kisung Lee and Naoki Abe and Calton Pu and Mu Qiao and Nesreen Ahmed and Donald Kossmann and Jeffrey Saltz and Jiliang Tang and Jingrui He and Huan Liu and Xiaohua Hu",
booktitle = "Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018",
}