A systematic approach, multi-source information integration, and logical reasoning are needed, with the core focus on extracting valuable insights from fragmented information. Here are the specific steps and key points:
- Clarify the analysis objectives
Focus on core issues: Determine the purpose of the analysis (e.g., assessing risks, predicting behaviors, uncovering backgrounds).
Define the scope: Clearly specify the time period, geographic area, social relationships, etc., that need to be covered.
- Multi-dimensional information collection
(1) Open-source intelligence (OSINT)
Social media: Analyze dynamics, friend relationships, and interest tags on platforms like WeChat, Douyin, Facebook, Twitter, LinkedIn.
Public records: Look for company registrations, court records, patents, real estate transactions, etc. (e.g., Tianyancha, Qichacha).
News and online traces: Use advanced search on Yandex (using commands like quotes, site:, filetype:, etc.) to uncover related information.
Geolocation data: Analyze activity trajectories through map markers and photo metadata (EXIF).
(2) Non-public intelligence
Database queries: Use commercial databases (e.g., LexisNexis) to obtain sensitive information such as financial and criminal records.
Interpersonal network penetration: Obtain information indirectly through informants and associates (must be legal and compliant).
(3) Technical means assistance
Metadata analysis: Check the creation time and modification records of documents and images.
- Information verification and noise reduction
Cross-validation: Verify the same information using multiple independent sources (e.g., comparing social media with public records).
Credibility grading: Mark the reliability of information (e.g., "high credibility - official documents," "low credibility - anonymous tips").
Eliminate interference information: Exclude irrelevant data or deliberately misleading content (e.g., fake accounts).
- Build an analysis framework
(1) Personal profile
Basic profile: Name, age, occupation, educational background, financial status.
Behavior patterns: Regular daily activities, consumption habits, abnormal behaviors (e.g., sudden large transfers).
Psychological characteristics: Infer personality through statements and social content (e.g., radical/conservative, risk preference).
(2) Social network analysis
Relationship map: Use tools (e.g., Maltego, Gephi) to map contact networks and identify core nodes (e.g., relatives, partners).
Influence assessment: Analyze their role in the social circle (e.g., leader, intermediary).
(3) Motivation and intent inference
Speech analysis: Extract keywords and emotional tendencies (e.g., NLP tools analyzing social media text).
Behavior correlation: Compare recent actions with historical patterns to identify anomalies (e.g., sudden concealment of whereabouts).
- Risk assessment and prediction
Threat assessment: Determine potential risks (e.g., tendencies toward violence, history of fraud).
Behavior modeling: Predict future actions based on historical data (e.g., "may go to location X in the next week").
Scenario simulation: Design "if-then" scenarios (e.g., "if the funding chain breaks, may take action Y").
- Output and action recommendations
Structured report: Use charts to display relationship networks, timelines, and risk levels.
Decision support: Provide actionable recommendations (e.g., "enhance monitoring," "contact key associates").
- Continuous dynamic updates
Real-time monitoring: Set keyword alerts (e.g., Google Alerts) to track the latest developments.
Iterative analysis: Adjust original conclusions based on new information (e.g., revise risk assessment after discovering hidden assets).
Key tools and techniques
OSINT tools: SpiderFoot, Shodan (IoT device tracking), Mitaka (browser plugin).
Data analysis: Python (Pandas, NetworkX libraries), Tableau for visualization.
Counter-surveillance techniques: Identify false information, counter social media disguises.
Legal and ethical boundaries
Compliance: Ensure information acquisition complies with laws such as the Personal Information Protection Law.
Privacy protection: Avoid excessive digging into sensitive information unrelated to the target (e.g., medical records).
Ethical boundaries: Use only for legal purposes (e.g., corporate risk control, judicial investigations), prohibiting abuse.
Case demonstration
Scenario: Analyze potential weaknesses of a commercial competitor.
Steps:
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Collect their public speeches, company financial reports, and patent layouts.
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Analyze the departure dynamics of core team members through LinkedIn.
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Discover their recent frequent contact with bankruptcy reorganization lawyers, inferring funding chain risks.
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Predict potential asset sell-offs and recommend early acquisition of key resources.
Summary
The essence of intelligence analysis is "connecting fragments to restore the truth," requiring a combination of logical reasoning, technical tools, and domain knowledge, while strictly adhering to legal and ethical boundaries. For personal analysis, the diversity of information sources and the rigor of logical closure are key to success.