Can shifts in human language help us accurately identify and anticipate the future of company innovation?
In recent years, there’s been great interest in applying Natural Language Processing techniques to the study of earning calls. While early applications were intended mainly to save human labor by automatically skimming earning transcripts, new applications have progressed towards augmenting analyst reading capacities.
Effective use of natural language processing allows analysts to "read" earnings reports in new ways by statistically extracting indicators that may not be immediately apparent using human intuition.
In our latest AlphaSense Visionaries report, researcher Peli Greitzer (Harvard PhD, Einstein Institute of Mathematics) shares his theory on how Natural Language Processing (NLP) could be used to study sentiment as an indicator for tracking company ideas and innovation before it happens.
Click on the link below to download the paper: