Both traditional finance and behavioral finance theory have reached a consensus that the news media de facto influence stock prices to some extent. There is also evidence that investors are not only subject to the sentiment of related news articles but also the public opinions. The challenge lies on how to quantify such sentimental information to predict the movement of stock market. To measure...

This paper discusses an approach to extracting and viewing relationships between named entities from news articles. It covers the preprocessing, parsing, extraction, filtering, and visualization of this information, starting from online news articles and ending with a visual graph of concepts they contain.

The open-source Global Database of Events, Language, and Tone (GDELT) is the most comprehensive and updated Big Data source of important terms extracted from international news articles . We focus only on GDELT’s Singapore events to better understand the data quality of its news articles, accuracy of its term extraction, and potential for prediction. To test news completeness and validity, we v...

We describe a task-based evaluation to determine whether multi-document summaries measurably improve user performance when using online news browsing systems for directed research. We evaluated the multi-document summaries generated by Newsblaster, a robust news browsing system that clusters online news articles and summarizes multiple articles on each event. Four groups of subjects were asked ...

In light of recent research that has begun to examine the link between textual “big data” and social phenomena such as stock price increases, this chapter takes a novel approach to treating news as big data by proposing the intelligent investment decision-making support model based on opinion mining. In an initial prototype experiment, the researchers first built a stock domain-specific sentime...

News articles are an important source providing information about society. The analysis of news articles helps to measure the social importance of many events and to give an understanding about current interests. In this research, a theoretical framework of text mining enhanced approach is proposed to accommodate short-term variations caused by special events, such as severe weather conditions....

There are huge numbers of documents in digital libraries. How to effectively organize these documents so that humans can easily browse or reference is a challenging task. Existing classification methods and chronological or geographical ordering only provide partial views of the news articles. The relationships among news articles might not be easily grasped. In this paper, we propose a near-du...

Every day, editors rank news articles for placement within their newspapers. In this paper, we investigate how news article ranking can be performed automatically. In particular, we investigate the blogosphere as a prime source of evidence, on the intuition that bloggers, and by extension their blog posts, can indicate interest in one news article or another. Moreover, we propose to model this ...

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