Our paper aims to assist researchers interested in generating new data and conducting field
experiments to devise strategies for collaborating with startups and online platforms such as …

We empirically show that the salience distortions of past fundamental information
significantly predict financial analysts' future realized forecast errors in both Chinese and US …

We investigate whether disagreement on StockTwits provides firm-specific information.
Using supervised machine learning approaches and a novel dataset, we predict investors' …

In this thesis, I examine the role of investor-oriented social media platforms in the financial
markets. This thesis comprises three standalone yet interconnected chapters in the field of …

We investigate whether disagreement on StockTwits provides firm-specific information.
Using supervised machine learning approaches and a novel dataset, we predict investors' …

This study examines the role of expectations management in explaining why firms with high
dispersion in analyst forecasts experience relatively low future stock returns. We first …

We examine the impact of non-severe depression on crowdsourced financial judgments
using earnings forecasts from Estimize. Our findings reveal that an increase in the proportion …