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xAI Crypto Sentiment Analysis

xAI 加密货币情绪分析

Real-time cryptocurrency sentiment from Crypto Twitter (CT) using Grok's native X integration.
通过Grok原生X集成获取加密货币推特圈（CT）的实时加密货币情绪数据。

Quick Start

快速开始

python
import os
from openai import OpenAI

client = OpenAI(
    api_key=os.getenv("XAI_API_KEY"),
    base_url="https://api.x.ai/v1"
)

def get_crypto_sentiment(coin: str) -> dict:
    """Get real-time sentiment for a cryptocurrency."""
    response = client.chat.completions.create(
        model="grok-4-1-fast",
        messages=[{
            "role": "user",
            "content": f"""Analyze Crypto Twitter sentiment for {coin}.

            Return JSON:
            {{
                "coin": "{coin}",
                "sentiment": {{
                    "overall": "bullish" | "bearish" | "neutral",
                    "score": -1.0 to 1.0,
                    "confidence": 0.0 to 1.0
                }},
                "fear_greed": "extreme fear" | "fear" | "neutral" | "greed" | "extreme greed",
                "metrics": {{
                    "bullish_percent": 0-100,
                    "bearish_percent": 0-100,
                    "mention_volume": "high" | "medium" | "low",
                    "trend": "increasing" | "stable" | "decreasing"
                }},
                "whale_mentions": {{
                    "detected": true/false,
                    "sentiment": "accumulating" | "distributing" | "neutral",
                    "notable": [...]
                }},
                "narratives": ["narrative1", "narrative2"],
                "fud_alerts": [...],
                "fomo_level": "high" | "medium" | "low" | "none"
            }}"""
        }]
    )
    return response.choices[0].message.content
python
import os
from openai import OpenAI

client = OpenAI(
    api_key=os.getenv("XAI_API_KEY"),
    base_url="https://api.x.ai/v1"
)

def get_crypto_sentiment(coin: str) -> dict:
    """获取加密货币的实时情绪数据。"""
    response = client.chat.completions.create(
        model="grok-4-1-fast",
        messages=[{
            "role": "user",
            "content": f"""分析加密货币推特圈中{coin}的情绪。

            返回JSON格式：
            {{
                "coin": "{coin}",
                "sentiment": {{
                    "overall": "bullish" | "bearish" | "neutral",
                    "score": -1.0 至 1.0,
                    "confidence": 0.0 至 1.0
                }},
                "fear_greed": "extreme fear" | "fear" | "neutral" | "greed" | "extreme greed",
                "metrics": {{
                    "bullish_percent": 0-100,
                    "bearish_percent": 0-100,
                    "mention_volume": "high" | "medium" | "low",
                    "trend": "increasing" | "stable" | "decreasing"
                }},
                "whale_mentions": {{
                    "detected": true/false,
                    "sentiment": "accumulating" | "distributing" | "neutral",
                    "notable": [...]
                }},
                "narratives": ["narrative1", "narrative2"],
                "fud_alerts": [...],
                "fomo_level": "high" | "medium" | "low" | "none"
            }}"""
        }]
    )
    return response.choices[0].message.content

Example

示例

sentiment = get_crypto_sentiment("Bitcoin") print(sentiment)
undefined
sentiment = get_crypto_sentiment("Bitcoin") print(sentiment)
undefined

Crypto Twitter Influencers

加密货币推特圈意见领袖

python
CRYPTO_INFLUENCERS = [
    # Bitcoin Maxis
    "saborskip",
    "michael_saylor",

    # Analysts
    "CryptoCapo_",
    "Pentosh1",
    "ColdBloodShill",

    # News
    "WatcherGuru",
    "whale_alert",

    # DeFi
    "DefiIgnas",
    "Route2FI",

    # Altcoins
    "AltcoinGordon",
    "CryptoKaleo"
]
python
CRYPTO_INFLUENCERS = [
    # Bitcoin 极端支持者
    "saborskip",
    "michael_saylor",

    # 分析师
    "CryptoCapo_",
    "Pentosh1",
    "ColdBloodShill",

    # 资讯账号
    "WatcherGuru",
    "whale_alert",

    # DeFi领域
    "DefiIgnas",
    "Route2FI",

    # 山寨币领域
    "AltcoinGordon",
    "CryptoKaleo"
]

Sentiment Functions

情绪分析函数

Bitcoin Market Sentiment

比特币市场情绪分析

python
def bitcoin_sentiment() -> dict:
    """Get comprehensive Bitcoin sentiment analysis."""
    response = client.chat.completions.create(
        model="grok-4-1-fast",
        messages=[{
            "role": "user",
            "content": """Analyze Bitcoin sentiment on Crypto Twitter.

            Return JSON:
            {
                "bitcoin": {
                    "sentiment_score": -1 to 1,
                    "fear_greed_index": 0-100,
                    "fear_greed_label": "...",
                    "trend": "bullish/bearish/consolidating"
                },
                "market_structure": {
                    "support_levels_mentioned": [...],
                    "resistance_levels_mentioned": [...],
                    "key_levels": [...]
                },
                "whale_activity": {
                    "accumulation_signals": true/false,
                    "distribution_signals": true/false,
                    "notable_moves": [...]
                },
                "narratives": {
                    "bullish": [...],
                    "bearish": [...]
                },
                "influencer_consensus": {
                    "bullish_count": n,
                    "bearish_count": n,
                    "key_calls": [...]
                },
                "on_chain_mentions": {
                    "exchange_flows": "inflows/outflows/neutral",
                    "wallet_activity": "..."
                },
                "macro_sentiment": {
                    "correlation_to_stocks": "...",
                    "fed_mentions": "...",
                    "institutional_interest": "..."
                }
            }"""
        }]
    )
    return response.choices[0].message.content
python
def bitcoin_sentiment() -> dict:
    """获取比特币的全面情绪分析结果。"""
    response = client.chat.completions.create(
        model="grok-4-1-fast",
        messages=[{
            "role": "user",
            "content": """分析加密货币推特圈中的比特币情绪。

            返回JSON格式：
            {
                "bitcoin": {
                    "sentiment_score": -1 至 1,
                    "fear_greed_index": 0-100,
                    "fear_greed_label": "...",
                    "trend": "bullish/bearish/consolidating"
                },
                "market_structure": {
                    "support_levels_mentioned": [...],
                    "resistance_levels_mentioned": [...],
                    "key_levels": [...]
                },
                "whale_activity": {
                    "accumulation_signals": true/false,
                    "distribution_signals": true/false,
                    "notable_moves": [...]
                },
                "narratives": {
                    "bullish": [...],
                    "bearish": [...]
                },
                "influencer_consensus": {
                    "bullish_count": n,
                    "bearish_count": n,
                    "key_calls": [...]
                },
                "on_chain_mentions": {
                    "exchange_flows": "inflows/outflows/neutral",
                    "wallet_activity": "..."
                },
                "macro_sentiment": {
                    "correlation_to_stocks": "...",
                    "fed_mentions": "...",
                    "institutional_interest": "..."
                }
            }"""
        }]
    )
    return response.choices[0].message.content

Altcoin Season Detection

山寨币行情周期检测

python
def detect_altseason() -> dict:
    """Detect if altcoin season is emerging."""
    response = client.chat.completions.create(
        model="grok-4-1-fast",
        messages=[{
            "role": "user",
            "content": """Analyze Crypto Twitter for altcoin season signals.

            Return JSON:
            {
                "altseason_status": "active" | "emerging" | "not present",
                "confidence": 0 to 1,
                "signals": {
                    "btc_dominance_sentiment": "...",
                    "altcoin_volume": "high/medium/low",
                    "rotation_patterns": "...",
                    "new_narratives": [...]
                },
                "hot_sectors": [
                    {"sector": "...", "sentiment": ..., "top_coins": [...]}
                ],
                "coins_trending": [
                    {"coin": "...", "sentiment": ..., "catalyst": "..."}
                ],
                "risk_level": "high/medium/low",
                "recommendation": "..."
            }"""
        }]
    )
    return response.choices[0].message.content
python
def detect_altseason() -> dict:
    """检测山寨币行情周期是否到来。"""
    response = client.chat.completions.create(
        model="grok-4-1-fast",
        messages=[{
            "role": "user",
            "content": """分析加密货币推特圈中的山寨币行情周期信号。

            返回JSON格式：
            {
                "altseason_status": "active" | "emerging" | "not present",
                "confidence": 0 至 1,
                "signals": {
                    "btc_dominance_sentiment": "...",
                    "altcoin_volume": "high/medium/low",
                    "rotation_patterns": "...",
                    "new_narratives": [...]
                },
                "hot_sectors": [
                    {"sector": "...", "sentiment": ..., "top_coins": [...]}
                ],
                "coins_trending": [
                    {"coin": "...", "sentiment": ..., "catalyst": "..."}
                ],
                "risk_level": "high/medium/low",
                "recommendation": "..."
            }"""
        }]
    )
    return response.choices[0].message.content

Token Sentiment Analysis

代币情绪分析

python
def analyze_token(token: str, chain: str = None) -> dict:
    """Analyze sentiment for a specific token."""
    chain_context = f" on {chain}" if chain else ""

    response = client.chat.completions.create(
        model="grok-4-1-fast",
        messages=[{
            "role": "user",
            "content": f"""Analyze Crypto Twitter sentiment for {token}{chain_context}.

            Return JSON:
            {{
                "token": "{token}",
                "chain": "{chain or 'unknown'}",
                "sentiment": {{
                    "score": -1 to 1,
                    "label": "...",
                    "volume": "high/medium/low"
                }},
                "community_health": {{
                    "engagement": "high/medium/low",
                    "holder_sentiment": "...",
                    "developer_activity_mentions": "..."
                }},
                "narratives": [...],
                "catalysts": {{
                    "upcoming": [...],
                    "recent": [...]
                }},
                "risks": {{
                    "fud_topics": [...],
                    "concerns_raised": [...],
                    "rug_risk_mentions": true/false
                }},
                "influencer_mentions": [...],
                "comparison_to_competitors": "..."
            }}"""
        }]
    )
    return response.choices[0].message.content
python
def analyze_token(token: str, chain: str = None) -> dict:
    """分析特定代币的情绪。"""
    chain_context = f" 在{chain}链上" if chain else ""

    response = client.chat.completions.create(
        model="grok-4-1-fast",
        messages=[{
            "role": "user",
            "content": f"""分析加密货币推特圈中{token}{chain_context}的情绪。

            返回JSON格式：
            {{
                "token": "{token}",
                "chain": "{chain or 'unknown'}",
                "sentiment": {{
                    "score": -1 至 1,
                    "label": "...",
                    "volume": "high/medium/low"
                }},
                "community_health": {{
                    "engagement": "high/medium/low",
                    "holder_sentiment": "...",
                    "developer_activity_mentions": "..."
                }},
                "narratives": [...],
                "catalysts": {{
                    "upcoming": [...],
                    "recent": [...]
                }},
                "risks": {{
                    "fud_topics": [...],
                    "concerns_raised": [...],
                    "rug_risk_mentions": true/false
                }},
                "influencer_mentions": [...],
                "comparison_to_competitors": "..."
            }}"""
        }]
    )
    return response.choices[0].message.content

DeFi Protocol Sentiment

DeFi协议情绪分析

python
def defi_protocol_sentiment(protocol: str) -> dict:
    """Analyze sentiment for a DeFi protocol."""
    response = client.chat.completions.create(
        model="grok-4-1-fast",
        messages=[{
            "role": "user",
            "content": f"""Analyze Crypto Twitter sentiment for {protocol} DeFi protocol.

            Return JSON:
            {{
                "protocol": "{protocol}",
                "sentiment": {{
                    "score": -1 to 1,
                    "trend": "improving/declining/stable"
                }},
                "tvl_sentiment": "growing/stable/declining concern",
                "security_mentions": {{
                    "concerns": [...],
                    "audits_mentioned": [...],
                    "exploit_risk_perception": "high/medium/low"
                }},
                "yield_sentiment": "attractive/fair/unattractive",
                "community_growth": "...",
                "governance_sentiment": "...",
                "competitors_mentioned": [...]
            }}"""
        }]
    )
    return response.choices[0].message.content
python
def defi_protocol_sentiment(protocol: str) -> dict:
    """分析DeFi协议的情绪。"""
    response = client.chat.completions.create(
        model="grok-4-1-fast",
        messages=[{
            "role": "user",
            "content": f"""分析加密货币推特圈中{protocol} DeFi协议的情绪。

            返回JSON格式：
            {{
                "protocol": "{protocol}",
                "sentiment": {{
                    "score": -1 至 1,
                    "trend": "improving/declining/stable"
                }},
                "tvl_sentiment": "growing/stable/declining concern",
                "security_mentions": {{
                    "concerns": [...],
                    "audits_mentioned": [...],
                    "exploit_risk_perception": "high/medium/low"
                }},
                "yield_sentiment": "attractive/fair/unattractive",
                "community_growth": "...",
                "governance_sentiment": "...",
                "competitors_mentioned": [...]
            }}"""
        }]
    )
    return response.choices[0].message.content

NFT Market Sentiment

NFT市场情绪分析

python
def nft_sentiment(collection: str = None) -> dict:
    """Analyze NFT market sentiment."""
    target = f"the {collection} collection" if collection else "the NFT market"

    response = client.chat.completions.create(
        model="grok-4-1-fast",
        messages=[{
            "role": "user",
            "content": f"""Analyze Crypto Twitter sentiment for {target}.

            Return JSON:
            {{
                "target": "{collection or 'NFT Market'}",
                "sentiment": {{
                    "score": -1 to 1,
                    "market_phase": "bull/bear/recovery/mania"
                }},
                "volume_sentiment": "high/medium/low",
                "floor_price_sentiment": "stable/rising/falling concern",
                "trending_collections": [...],
                "whale_activity": {{
                    "notable_buys": [...],
                    "notable_sales": [...]
                }},
                "narratives": [...],
                "mint_sentiment": "hot/cooling/cold"
            }}"""
        }]
    )
    return response.choices[0].message.content
python
def nft_sentiment(collection: str = None) -> dict:
    """分析NFT市场的情绪。"""
    target = f"{collection}系列" if collection else "NFT市场"

    response = client.chat.completions.create(
        model="grok-4-1-fast",
        messages=[{
            "role": "user",
            "content": f"""分析加密货币推特圈中{target}的情绪。

            返回JSON格式：
            {{
                "target": "{collection or 'NFT Market'}",
                "sentiment": {{
                    "score": -1 至 1,
                    "market_phase": "bull/bear/recovery/mania"
                }},
                "volume_sentiment": "high/medium/low",
                "floor_price_sentiment": "stable/rising/falling concern",
                "trending_collections": [...],
                "whale_activity": {{
                    "notable_buys": [...],
                    "notable_sales": [...]
                }},
                "narratives": [...],
                "mint_sentiment": "hot/cooling/cold"
            }}"""
        }]
    )
    return response.choices[0].message.content

Whale Alert Monitoring

巨鲸警报监控

python
def monitor_whale_alerts() -> dict:
    """Monitor whale activity mentions on CT."""
    response = client.chat.completions.create(
        model="grok-4-1-fast",
        messages=[{
            "role": "user",
            "content": """Search Crypto Twitter for recent whale alerts and large transactions.

            Focus on @whale_alert and similar accounts.

            Return JSON:
            {
                "timestamp": "...",
                "recent_whale_moves": [
                    {
                        "coin": "...",
                        "amount_usd": "...",
                        "direction": "exchange_inflow/exchange_outflow/wallet_transfer",
                        "interpretation": "bullish/bearish/neutral",
                        "source": "..."
                    }
                ],
                "exchange_flow_summary": {
                    "net_flow": "inflows/outflows/balanced",
                    "interpretation": "..."
                },
                "accumulation_signals": [...],
                "distribution_signals": [...],
                "notable_wallet_activity": [...]
            }"""
        }]
    )
    return response.choices[0].message.content
python
def monitor_whale_alerts() -> dict:
    """监控CT上的巨鲸活动提及内容。"""
    response = client.chat.completions.create(
        model="grok-4-1-fast",
        messages=[{
            "role": "user",
            "content": """搜索加密货币推特圈中的近期巨鲸警报和大额交易信息。

            重点关注@whale_alert及类似账号。

            返回JSON格式：
            {
                "timestamp": "...",
                "recent_whale_moves": [
                    {
                        "coin": "...",
                        "amount_usd": "...",
                        "direction": "exchange_inflow/exchange_outflow/wallet_transfer",
                        "interpretation": "bullish/bearish/neutral",
                        "source": "..."
                    }
                ],
                "exchange_flow_summary": {
                    "net_flow": "inflows/outflows/balanced",
                    "interpretation": "..."
                },
                "accumulation_signals": [...],
                "distribution_signals": [...],
                "notable_wallet_activity": [...]
            }"""
        }]
    )
    return response.choices[0].message.content

FOMO/FUD Detection

FOMO/FUD检测

python
def detect_fomo_fud(coin: str) -> dict:
    """Detect FOMO or FUD patterns for a cryptocurrency."""
    response = client.chat.completions.create(
        model="grok-4-1-fast",
        messages=[{
            "role": "user",
            "content": f"""Analyze Crypto Twitter for FOMO and FUD signals around {coin}.

            Return JSON:
            {{
                "coin": "{coin}",
                "fomo_analysis": {{
                    "level": "extreme/high/moderate/low/none",
                    "triggers": [...],
                    "warning_signs": [...],
                    "sustainability": "likely/unlikely"
                }},
                "fud_analysis": {{
                    "level": "extreme/high/moderate/low/none",
                    "sources": [...],
                    "legitimacy": "valid concerns/coordinated/mixed",
                    "topics": [...]
                }},
                "manipulation_signals": {{
                    "detected": true/false,
                    "type": "pump/dump/coordinated/organic",
                    "evidence": [...]
                }},
                "contrarian_signal": {{
                    "extreme_fear": true/false,
                    "extreme_greed": true/false,
                    "actionable": "..."
                }}
            }}"""
        }]
    )
    return response.choices[0].message.content
python
def detect_fomo_fud(coin: str) -> dict:
    """检测加密货币的FOMO或FUD模式。"""
    response = client.chat.completions.create(
        model="grok-4-1-fast",
        messages=[{
            "role": "user",
            "content": f"""分析加密货币推特圈中围绕{coin}的FOMO和FUD信号。

            返回JSON格式：
            {{
                "coin": "{coin}",
                "fomo_analysis": {{
                    "level": "extreme/high/moderate/low/none",
                    "triggers": [...],
                    "warning_signs": [...],
                    "sustainability": "likely/unlikely"
                }},
                "fud_analysis": {{
                    "level": "extreme/high/moderate/low/none",
                    "sources": [...],
                    "legitimacy": "valid concerns/coordinated/mixed",
                    "topics": [...]
                }},
                "manipulation_signals": {{
                    "detected": true/false,
                    "type": "pump/dump/coordinated/organic",
                    "evidence": [...]
                }},
                "contrarian_signal": {{
                    "extreme_fear": true/false,
                    "extreme_greed": true/false,
                    "actionable": "..."
                }}
            }}"""
        }]
    )
    return response.choices[0].message.content

Crypto Market Dashboard

加密货币市场仪表盘

python
def crypto_market_dashboard() -> dict:
    """Get overall crypto market sentiment dashboard."""
    response = client.chat.completions.create(
        model="grok-4-1-fast",
        messages=[{
            "role": "user",
            "content": """Create a comprehensive Crypto Twitter market dashboard.

            Return JSON:
            {
                "timestamp": "...",
                "market_sentiment": {
                    "overall": -1 to 1,
                    "fear_greed": 0-100,
                    "trend": "bullish/bearish/neutral"
                },
                "bitcoin": {
                    "sentiment": ...,
                    "key_levels": [...]
                },
                "ethereum": {
                    "sentiment": ...,
                    "key_topics": [...]
                },
                "top_trending_coins": [
                    {"coin": "...", "sentiment": ..., "reason": "..."}
                ],
                "sector_performance": [
                    {"sector": "L1/L2/DeFi/NFT/Meme", "sentiment": ...}
                ],
                "hot_narratives": [...],
                "risk_alerts": [...],
                "whale_summary": "...",
                "recommended_focus": [...]
            }"""
        }]
    )
    return response.choices[0].message.content
python
def crypto_market_dashboard() -> dict:
    """获取加密货币市场的综合情绪仪表盘。"""
    response = client.chat.completions.create(
        model="grok-4-1-fast",
        messages=[{
            "role": "user",
            "content": """创建加密货币推特圈的综合市场情绪仪表盘。

            返回JSON格式：
            {
                "timestamp": "...",
                "market_sentiment": {
                    "overall": -1 至 1,
                    "fear_greed": 0-100,
                    "trend": "bullish/bearish/neutral"
                },
                "bitcoin": {
                    "sentiment": ...,
                    "key_levels": [...]
                },
                "ethereum": {
                    "sentiment": ...,
                    "key_topics": [...]
                },
                "top_trending_coins": [
                    {"coin": "...", "sentiment": ..., "reason": "..."}
                ],
                "sector_performance": [
                    {"sector": "L1/L2/DeFi/NFT/Meme", "sentiment": ...}
                ],
                "hot_narratives": [...],
                "risk_alerts": [...],
                "whale_summary": "...",
                "recommended_focus": [...]
            }"""
        }]
    )
    return response.choices[0].message.content

Best Practices

最佳实践

1. Crypto-Specific Considerations

1. 加密货币领域专属注意事项

  • CT is highly volatile - sentiment can shift quickly
  • Bot activity is prevalent - look for organic signals
  • Influencer manipulation is common - verify across sources
  • CT的情绪波动极大，情绪可能快速转变
  • 机器人活动盛行，需关注有机信号
  • 意见领袖操纵行为常见，需跨来源验证

2. Timing Matters

2. 时机至关重要

  • US/EU overlap often sees highest activity
  • Asian session can have different sentiment
  • Weekend sentiment differs from weekdays
  • 欧美时段重叠期通常活跃度最高
  • 亚洲时段的情绪可能有所不同
  • 周末情绪与工作日存在差异

3. Filter for Quality

3. 筛选优质内容

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Focus on accounts with history, not fresh accounts pumping

关注有历史积累的账号，而非新注册的喊单账号

"Focus on accounts older than 6 months with consistent posting history"
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"Focus on accounts older than 6 months with consistent posting history"
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4. Watch for Coordinated Activity

4. 警惕协同活动

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Detect potential pump and dump schemes

检测潜在的拉高出货骗局

"Flag any coordinated posting patterns or sudden volume spikes from new accounts"
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"Flag any coordinated posting patterns or sudden volume spikes from new accounts"
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Related Skills

相关技能

  • xai-stock-sentiment
    - Stock analysis
  • xai-x-search
    - Raw X search
  • xai-sentiment
    - General sentiment
  • xai-financial-integration
    - Price data integration
  • xai-stock-sentiment
    - 股票分析
  • xai-x-search
    - 原生X搜索
  • xai-sentiment
    - 通用情绪分析
  • xai-financial-integration
    - 价格数据集成

References

参考资料