A Novel Distributed Representation of News (DRNews) for Stock Market Predictions

In this study, a novel Distributed Representation of News (DRNews) model is developed and applied in deep learning-based stock market predictions. With the merit of integrating contextual information and cross-documental knowledge, the DRNews model creates news vectors that describe both the semantic information and potential linkages among news events through an attributed news network. Two stock market prediction tasks, namely the short-term stock movement prediction and stock crises early warning, are implemented in the framework of the attention-based Long Short Term-Memory (LSTM) network. It is suggested that DRNews substantially enhances the results of both tasks comparing with five baselines of news embedding models. Further, the attention mechanism suggests that short-term stock trend and stock market crises both receive influences from daily news with the former demonstrates more critical responses on the information related to the stock market {\em per se}, whilst the latter draws more concerns on the banking sector and economic policies.Comment: 25 page

A Survey on Prediction of Movie’s Box Office Collection Using Social Media

Predicting the box office profits of a movie prior to its world wide release are a significant but also an exigent problem that needs a advanced of Intelligence. Currently, social media has given away its diagnostic strength in a variety of fields, which encourages us to develop social media substance to predict box office profits. The collection of movies in provisions of profit relies on so many features for instance its making studio, type, screenplay superiority, pre release endorsement etc, each of which are usually utilized to approximation their probable achievement at the box office. Nevertheless, the “Wisdom of Crowd” and social media have been accredited as a powerful indication in appreciative customer activities to media. In this survey, we converse the influence of socially created Meta data derived from the social multimedia websites and review the effect of social media on box office collection and success of movies. This survey paper is written for (social networking) investigators who looking for to evaluate prediction of movies using social media. It gives a complete study of social media analytics for social networking, wikis, actually easy syndication feeds, blogs, newsgroups, chat and news feeds etc. Keywords: Social Networking, Social media. Movie’s Box Office, Prediction, Profitability, Sentiment analysi