S-Score
Contents
Unraveling S-Score: A Guide to Social Media Sentiment Analysis in Investing
Understanding S-Score
Introduced in 2013 by NYSE Technologies and Social Market Analytics (SMA), the S-Score revolutionized how investors gauge market sentiment through social media. Specifically tailored for the financial sector, the S-Score offers a numerical representation of consumer and investor sentiment regarding a company, stock, ETF, sector, or index, derived from social media chatter.
The S-Score Ecosystem
Accompanying the S-Score are a suite of metrics known as S-Factors, including S-Mean, S-Delta, S-Volatility, S-Buzz, and S-Dispersion. By analyzing the volume, change, and dispersion of social media commentary, these metrics collectively provide insights into market sentiment, empowering traders, portfolio managers, and risk analysts.
Measuring Social Sentiment
SMA's proprietary processing engine comprises three components: extractor, evaluator, and calculator. Leveraging Twitter and GNIP microblogging data, the extractor continuously gathers social media commentary on SMA-covered stocks. Subsequently, the evaluator analyzes each tweet for financial market relevance and the sentiment of the user, while the calculator assigns sentiment scores based on timing and weighting algorithms.
Utilizing S-Score
Investors leverage S-Scores to inform their trading decisions, as changes in sentiment often correlate with stock price movements. Research indicates that stocks with S-Scores exceeding +2 consistently outperform the S&P 500, while those below -2 tend to underperform. SMA extends its coverage to cryptocurrencies, expanding the applicability of the S-Score as an analytical tool for evaluating various investment opportunities.