News can contain information which may provide an indication of the future direction of a share or stock market index. The possibility of predicting future stock market prices has attracted an increasing numbers of industry practitioners and academic researchers to this area of investigation. Popular approaches have relied upon either: models constructed from manually selected training or manua...

In this paper, we give an overview for the shared task at the CCF Conference on Natural Language Processing & Chinese Computing (NLPCC 2017): Chinese News Headline Categorization. The dataset of this shared task consists 18 classes, 12,000 short texts along with corresponded labels for each class. The dataset and example code can be accessed at https://github.com/FudanNLP/ nlpcc2017_news_headli...

This paper reports ongoing experiments towards exploiting the use of images to provide additional context for statistical machine translation (SMT). We investigate whether this contextual information can be helpful in targeting two well-known challenges in machine translation: ambiguity (incorrect translation of words that have multiple senses) and out-of-vocabulary words (words left untranslat...

We describe our efforts to generate a large (100,000 instance) corpus of textual entailment pairs from the lead paragraph and headline of news articles. We manually inspected a small set of news stories in order to locate the most productive source of entailments, then built an annotation interface for rapid manual evaluation of further exemplars. With this training data we built an SVM-based d...

D annual expenditures on public relations exceeding $19.42 billion, U.S. businesses lack practical guidance about the effectiveness of publicity in mass media. Here, we assemble a rich and novel data set to gauge the impact of news reports on consumer sign-ups with the U.S. Do Not Call (DNC) Registry. Using multiple identification strategies, we found robust evidence that news reports increased...

Information presented in news articles can be misleading without being blatantly false. Experiment 1 examined the effects of misleading headlines that emphasize secondary content rather than the article's primary gist. We investigated how headlines affect readers' processing of factual news articles and opinion pieces, using both direct memory measures and more indirect reasoning measures. Expe...

Twitter is becoming an ever more popular platform for discovering and sharing information about current events, both personal and global. The scale and diversity of messages makes the discovery and analysis of breaking news very challenging. Nonetheless, journalists and other news consumers are increasingly relying on tools to help them make sense of Twitter. Here, we describe a fully-automated...