Sentiment Shift Detector

Identify stocks where blogger sentiment has changed significantly.

Triggers

• "情绪变化最大的股票"

• "谁转向了"

• "sentiment shift"

• "who changed their mind"

• "态度转变"

• /sentiment-shift

Instructions

When the user wants to find sentiment shifts, follow these steps:

Get Multi-Day Summaries Call get_daily_summary for recent dates (today, yesterday, a few days ago) to compare sentiment over time.

Identify Changed Tickers Compare the summaries to find:

• Stocks that moved from bullish to bearish

• Stocks that moved from bearish to bullish

• Stocks with increased/decreased mentions

Get Detailed Sentiment For tickers with notable changes, call get_ticker_sentiment to understand who changed their view.

Search for Explanations Call search_viewpoints for changed tickers to find the reasoning behind sentiment shifts.

Present Results Format the output as:

情绪转变追踪 🔄

转向看涨 📈

TICKER1

• 变化: 看跌 → 看涨
• 时间: X天前开始转变
• 关键转变博主: 博主A, 博主B
• 转变原因: [摘要为什么改变看法]
• 代表观点: "[具体观点]" — 博主A

转向看跌 📉

TICKER2

• 变化: 看涨 → 看跌
• 时间: X天前开始转变
• 关键转变博主: 博主C
• 转变原因: [摘要为什么改变看法]
• 代表观点: "[具体观点]" — 博主C

热度变化 🌡️

分析

[总结市场情绪变化的整体趋势]

Tool Sequence

• get_daily_summary(date=today)

• get_daily_summary(date=yesterday)
• get_daily_summary(date=3_days_ago) → Compare over time

• Identify tickers with changed sentiment

• get_ticker_sentiment(changed_ticker) → For each changed ticker

• search_viewpoints(changed_ticker) → Find reasoning

• Compile shift analysis

Notes

• Sentiment shifts can be leading indicators

• A blogger changing their view is often more significant than new bloggers joining

• Track both direction changes and intensity changes

• Include context for why shifts happened (news, earnings, etc.)