arbiter
JournalsPricingAccount

Dumb money? Social network attention herding, sentiment, and markets

Chengcheng Huang & Pauline Shum

The Journal of Finance and Data Science2025https://doi.org/10.1016/j.jfds.2025.100169article
ABDC B
Weight
0.37

What the paper says

Wallstreetbets (WSB) is the perfect echo chamber to study retail investor behaviour and markets. We introduce a direct measure of individual stock attention and the concept of forum-wide attention herding. We fine-tune a large language model to classify investor sentiment. We find that WSB sentiment is inversely related to the VIX. In general, more individual stock attention leads to more stock purchases, and sentiment is a contrarian predictor of future returns. However, when attention herds on a stock with high user engagement, trades peak but there is no reversal in returns. Finally, our monthly attention herding portfolio generates sizable alphas.

1 citation

Open paper page →

Cite this paper

https://doi.org/https://doi.org/10.1016/j.jfds.2025.100169

Or copy a formatted citation

@article{chengcheng2025,
  title        = {{Dumb money? Social network attention herding, sentiment, and markets}},
  author       = {Chengcheng Huang & Pauline Shum},
  journal      = {The Journal of Finance and Data Science},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1016/j.jfds.2025.100169},
}

Paste directly into BibTeX, Zotero, or your reference manager.

Flag this paper

Dumb money? Social network attention herding, sentiment, and markets

Flags are reviewed by the Arbiter methodology team within 5 business days.

Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.