@inproceedings{7ab61fdd1e2140c2a633e5ad89de1792,
title = "Hotspots of news articles: Joint mining of news text & social media to discover controversial points in news",
abstract = "We propose and study a novel problem of mining news text and social media jointly to discover controversial points in news, which enables many applications such as highlighting controversial points in news articles for readers, revealing controversies in news and their trends over time, and quantifying the controversy of a news source. We design a controversy scoring function to discover the most controversial sentences in a news article by leveraging relevant comments in Twitter and comments on news web sites to assess the controversy of opinions about an issue mentioned in the news article. Multiple scoring strategies based on sentiment analysis and linguistic cues are proposed and studied. Experimental results show that the proposed algorithms can effectively discover controversial parts in news articles.",
author = "Ismini Lourentzou and Graham Dyer and Abhishek Sharma and Chengxiang Zhai",
note = "Funding Information: This work is supported in part by the National Science Foundation under grant number CNS-1027965 and by the National Institute of Health under grant number 1R56AI11450101A1. Publisher Copyright: {\textcopyright} 2015 IEEE.; 3rd IEEE International Conference on Big Data, IEEE Big Data 2015 ; Conference date: 29-10-2015 Through 01-11-2015",
year = "2015",
month = dec,
day = "22",
doi = "10.1109/BigData.2015.7364132",
language = "English (US)",
series = "Proceedings - 2015 IEEE International Conference on Big Data, IEEE Big Data 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2948--2950",
editor = "Feng Luo and Kemafor Ogan and Zaki, {Mohammed J.} and Laura Haas and Ooi, {Beng Chin} and Vipin Kumar and Sudarsan Rachuri and Saumyadipta Pyne and Howard Ho and Xiaohua Hu and Shipeng Yu and Hsiao, {Morris Hui-I} and Jian Li",
booktitle = "Proceedings - 2015 IEEE International Conference on Big Data, IEEE Big Data 2015",
address = "United States",
}