Vast amounts of media, news and commentary are generated on a daily basis. Headlines and other attention-grabbing content is constantly put on our screens to try to get us to click through. Putting together a good headline is almost as important as the content within an article and there are teams of people dedicated it.
Natural Language Processing (NLP) is a large and growing field focused on the application of machine learning to attain human-level understanding of textual data. Large-scale general language models are an exciting new capability allowing us to add amazing functionality quickly with limited compute and people. Innovation continues with new models and advancements coming in at what seems a weekly basis.
What if we can use NLP to better understand headlines? Can we detect objectivity, sentiment and/or underlying favoritism towards a cause? This article introduces tldrstory, an AI-powered framework for understanding headlines and story text.
tldrstory is a framework for AI-powered understanding of headlines and text content related to stories. tldrstory applies zero-shot labeling over text, which allows dynamically categorizing content. tldrstory is open source and available on GitHub.
#machine-learning #nlp #search #software-development #artificial-intelligence