Fake news pose serious threat to our society nowadays, particularly due to its wide spread through social networks. While human fact checkers cannot handle such tremendous information online in real time, AI technology can be leveraged to automate fake news detection. The first step leading to a sophisticated fake news detection system is the stance detection between statement and body text. In...

The appeal of personae in news is investigated based on social comparison and regulatory focus theory. High-school students (N=252) browsed through online news while selective exposure was unobtrusively logged. Manipulated headlines focused on individuals and varied along three within factors: the positive or negative valence of the headline, the sex of the portrayed individuals, and their econ...

This paper describes our systems submitted to the Fine-Grained Sentiment Analysis on Financial Microblogs and News task (i.e., Task 5) in SemEval-2017. This task includes two subtasks in microblogs and news headline domain respectively. To settle this problem, we extract four types of effective features, including linguistic features, sentiment lexicon features, domain-specific features and wor...

Euphemism can be said as a style of language that becomes better communication tool and avoids important actions or things are sensitive. The use euphemisms is used in to provide information messages usually contain taboos meaningful words, phrases sentences euphemistic expressions. This study aimed an insight into the strategy using order prioritize politeness when speaking general context sit...

The University of Strathclyde participated in TREC BLOG Headline Ranking task only. Our general theme was to explore how the lexical changes in the BLOG corpus can reflect the importance of the articles appearing in the news corpus. Three (3) runs were submitted. For automated run "strath1", our algorithm identified the word unigrams, the frequencies of mentioning of which in the blog corpus in...

This paper describes a supervised solution for detecting the polarity scores of tweets or headline news in the financial domain, submitted to the SemEval 2017 Fine-Grained Sentiment Analysis on Financial Microblogs and News Task. The premise is that it is possible to understand market reaction over a company stock by measuring the positive/negative sentiment contained in the financial tweets an...

In this paper, we present the HybridTrim system which uses a machine learning technique to combine linguistic, statistical and positional information to identify topic labels for headlines in a text. We compare our system with the Topiary system which, in contrast, uses a statistical learning approach to finding topic descriptors for headlines. The Topiary system, developed at the University of...

In this paper we compare two parse-and-trim style headline generation systems. The Topiary system uses a statistical learning approach to finding topic labels for headlines, while our approach, the LexTrim system, identifies key summary words by analysing the lexical cohesion structure of a text. The performance of these systems is evaluated using the ROUGE evaluation suite on the DUC 2004 news...

We present a software tool that employs state-ofthe-art natural language processing (NLP) and machine learning techniques to help newspaper editors compose effective headlines for online publication. The system identifies the most salient keywords in a news article and ranks them based on both their overall popularity and their direct relevance to the article. The system also uses a supervised ...