Using Text Features to Predict the Great Stock Market Crash of 1929
Predicting financial crises is notoriously difficult. This is primarily a consequence of the infrequency of such events and the instability of relationships between financial variables. However, it is also related to the contagious nature of financial crises: if one bank expects another to liquidate its holdings... Read more
Performing IMDb Sentiment Analysis with GloVe Embeddings
The GloVe model came out in 2014, a year after the Word2Vec paper came out. The GloVe and Word2Vec models are similar as the embeddings generated for a word are determined by the words that occur around it. However, these context words occur with different frequencies. Some of these context... Read more
Gauging the State of the Economy with News Narrative and Sentiment
Advances in natural language processing have allowed us to quantify the intuitive yet elusive notion of sentiment expressed in text and to test its predictive power in relation to changes in social systems. Studies in cognitive sciences as well as economics have found that unsettling narrative... Read more
Why You Should Be Using Sentiment Analysis for Social Media and Decision Making
Data might be supreme, but your customers are more than just data points. When they’re affected by your product, good or bad, you need to know to move forward or to pivot. Sentiment analysis has come a long way since the early days and can now... Read more
Sentiment Analysis in R Made Simple
Sentiment analysis is located at the heart of natural language processing, text mining/analytics, and computational linguistics. It refers to any measurement technique by which subjective information is extracted from textual documents. In other words, it extracts the polarity of the expressed sentiment in a range spanning... Read more