Islander: A Real-Time News Monitoring and Analysis System
Chao-Wei Huang, Kai-Chou Yang, Zi-Yuan Chen, Hao-Chien Cheng, Po-Yu, Wu, Yu-Yang Huang, Chung-Kai Hsieh, Geng-Zhi Wildsky Fann, Ting-Yin Cheng,, Ethan Tu, Yun-Nung Chen
TL;DR
Islander is a real-time online system that monitors, analyzes, and presents trending news topics from multiple sources, using quality metrics to help users access accurate and diverse news content efficiently.
Contribution
The paper introduces Islander, a novel system that automatically estimates news quality and provides real-time trending topic analysis from multiple sources.
Findings
Effective algorithms for news quality estimation.
Real-time trending topic visualization.
Publicly accessible web interface.
Abstract
With thousands of news articles from hundreds of sources distributed and shared every day, news consumption and information acquisition have been increasingly difficult for readers. Additionally, the content of news articles is becoming catchy or even inciting to attract readership, harming the accuracy of news reporting. We present Islander, an online news analyzing system. The system allows users to browse trending topics with articles from multiple sources and perspectives. We define several metrics as proxies for news quality, and develop algorithms for automatic estimation. The quality estimation results are delivered through a web interface to newsreaders for easy access to news and information. The website is publicly available at https://islander.cc/
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Taxonomy
TopicsWeb Data Mining and Analysis · Text and Document Classification Technologies · Advanced Text Analysis Techniques