Do Emotions Expressed Online Correlate with Actual Changes in Decision-Making?: The Case of Stock Day Traders.
Where this comes from
- Record sourced from PubMed, PMID 26765539.
- Also identified by DOI 10.1371/journal.pone.0144945 and PMC identifier 4713085.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
Emotions are increasingly inferred linguistically from online data with a goal of predicting off-line behavior. Yet, it is unknown whether emotions inferred linguistically from online communications correlate with actual changes in off-line activity. We analyzed all 886,000 trading decisions and 1,234,822 instant messages of 30 professional day traders over a continuous 2 year period. Linguistically inferring the traders' emotional states from instant messages, we find that emotions expressed in online communications reflect the same distributions of emotions found in controlled experiments done on traders. Further, we find that expressed online emotions predict the profitability of actual trading behavior. Relative to their baselines, traders who expressed little emotion or traders that expressed high levels of emotion made relatively unprofitable trades. Conversely, traders expressing moderate levels of emotional activation made relatively profitable trades.
Medical subject headings
- Decision Making
- Emotions
- Internet