Related papers: Says who? Automatic Text-Based Content Analysis of…
Modern technological era has reshaped traditional lifestyle in several domains. The medium of publishing news and events has become faster with the advancement of Information Technology. IT has also been flooded with immense amounts of…
News Articles provides crucial information about various events happening in the society but they unfortunately come with different kind of biases. These biases can significantly distort public opinion and trust in the media, making it…
We provide a literature review about Automatic Text Summarization (ATS) systems. We consider a citation-based approach. We start with some popular and well-known papers that we have in hand about each topic we want to cover and we have…
The paper proposes a method of financial time series forecasting taking into account the semantics of news. For the semantic analysis of financial news the sampling of negative and positive words in economic sense was formed based on…
We first adopt a human-guided machine learning framework to develop a new dataset for hyperpartisan news title detection with 2,200 manually labeled and 1.8 million machine-labeled titles that were posted from 2014 to the present by nine…
The World Wide Web provides unrivalled access to information globally, including factual news reporting and commentary. However, state actors and commercial players increasingly spread biased (distorted) or fake (non-factual) information to…
We present the Newspaper Bias Dataset (NewB), a text corpus of more than 200,000 sentences from eleven news sources regarding Donald Trump. While previous datasets have labeled sentences as either liberal or conservative, NewB covers the…
Automated frame analysis of political communication is a popular task in computational social science that is used to study how authors select aspects of a topic to frame its reception. So far, such studies have been narrow, in that they…
News articles tend to be increasingly misleading nowadays, preventing readers from making subjective judgments towards certain events. While some machine learning approaches have been proposed to detect misleading news, most of them are…
The volume of news content has increased significantly in recent years and systems to process and deliver this information in an automated fashion at scale are becoming increasingly prevalent. One critical component that is required in such…
The development of Internet technology has led to a rapid increase in news information. Filtering out valuable content from complex information has become an urgentproblem that needs to be solved. In view of the shortcomings of traditional…
News articles both shape and reflect public opinion across the political spectrum. Analyzing them for social bias can thus provide valuable insights, such as prevailing stereotypes in society and the media, which are often adopted by NLP…
Natural Language Processing is booming with its applications in the real world, one of which is Text Summarization for large texts including news articles. This research paper provides an extensive comparative evaluation of extractive and…
We present NewsQA, a challenging machine comprehension dataset of over 100,000 human-generated question-answer pairs. Crowdworkers supply questions and answers based on a set of over 10,000 news articles from CNN, with answers consisting of…
This paper seeks to address the classification of misinformation in news articles using a Long Short Term Memory Recurrent Neural Network. Articles were taken from 2018; a year that was filled with reporters writing about President Donald…
Video Question Answering methods focus on commonsense reasoning and visual cognition of objects or persons and their interactions over time. Current VideoQA approaches ignore the textual information present in the video. Instead, we argue…
In this paper, we tackle the complex task of analyzing televised debates, with a focus on a prime time news debate show from India. Previous methods, which often relied solely on text, fall short in capturing the multimodal essence of these…
The goal of this research was to find a way to extend the capabilities of computers through the processing of language in a more human way, and present applications which demonstrate the power of this method. This research presents a novel…
The ability to automatically identify industry sector coverage in articles on legal developments, or any kind of news articles for that matter, can bring plentiful of benefits both to the readers and the content creators themselves. By…
News captioning task aims to generate sentences by describing named entities or concrete events for an image with its news article. Existing methods have achieved remarkable results by relying on the large-scale pre-trained models, which…