Trend Extraction and Analysis via Large Language Models

In the ever-evolving landscape of data-driven decision making, the ability to accurately extract and analyse trends has become a cornerstone for strategic planning across various domains. The advent of Large Language Models has ushered in a new era of potential in this realm, presenting sophisticated tools that can parse, interpret, and forecast trends from vast repositories of textual data. This paper seeks to explore the application of language models on trend extraction and analysis, highlighting the transformative impact these models have on extracting actionable insights from unstructured data sources. Additionally, ours is the first work towards the creation of a time-based dataset of trends to enable the backtesting of AI algorithms and models on short- and long-term foresight.