Dorothy Ruderman is the Head of Data Partnerships at StockTwits, where she leads all initiatives around StockTwits’ enterprise data access. She oversees the development of partnerships with asset managers, trading products, analytics and signal companies, as well as over 50 research universities, helping to leverage StockTwits data within the investment decision-making process. Previously she led partnerships at inSided and Kustomer focusing on B2B and B2C partnerships of intelligent community vendors. With over 5 years in social media and social data products, Dorothy has an integral understanding of the social data landscape as well as the products and providers in the space. She is based out of the New York City headquarters, and holds a degree in economics from Lehigh University.
Social Trading – Developing Signals from Social Sentiment
StockTwits is the largest independent social network setup for investors and traders to talk about investing. In addition to covering 8,300 stocks per year, the network also discusses 1,500+ alternative assets, including FX, futures, fixed income, privative companies, ETFs/indexes, and cryptoassets. With a dataset that stretches back to 2009, the network becomes a rich dataset for both quantitative investing as well as model development. In this talk, we will discuss the methodology behind developing an NLP-based social signal, as well as some of the academic studies run in parallel with this research. We will also discuss some of the ways in which it is being deployed in markets today.