find-anyone
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ChineseFind anyone
查找目标人物
Turn a name into a sourced profile of one specific human. The work is 20% finding
data and 80% proving the data belongs to your subject and not to someone with the
same name. Beginners collect first and disambiguate later; that is how you end up
with a confident, well-cited dossier describing two different people fused into
one. Bind the name to a second selector before you collect anything.
将一个姓名转化为一份针对特定个人的、有来源依据的资料。这项工作的20%是查找数据,80%是证明这些数据属于你的调查对象,而非同名其他人。新手往往先收集数据再进行区分,这会导致最终得到一份看似可靠、引用充分的档案,实则是两个不同的人被混为一谈。在收集任何数据之前,请先将姓名与第二个识别信息绑定。
Step 1 — Authorized scope
步骤1 — 明确授权范围
Write down, before searching: the subject, the objective, what is in bounds, what
is out of bounds, and which jurisdiction's law governs you and the subject. Read
../../ETHICS.md.
Built for: counterparty and investor due diligence, fraud and asset
investigation, journalism, skip tracing and debt recovery, missing persons,
pre-employment integrity checks on senior or fiduciary roles, and personal
self-defense — running yourself to see what an attacker would find.
Out of bounds, always: establishing a private individual's home address, routine
movements, children, medical status, immigration status, or sexuality for any
purpose other than a documented lawful one; anything that puts you in contact
with the subject; and any use a reasonable person would call surveillance. If
your objective is to confront, embarrass, or reach the subject in person, stop.
See also the US employment-and-tenancy restriction in
, which binds a large share of the sources here.
dig-through-data-brokersDone when the scope note exists in the case file, names a lawful objective,
and states an explicit out-of-bounds list.
在开始搜索前,请写下:调查对象、调查目标、调查范围、排除范围,以及约束你和调查对象的司法管辖区法律。阅读../../ETHICS.md。
适用场景:交易对手与投资者尽职调查、欺诈与资产调查、新闻报道、Skip Tracing与债务追偿、失踪人口查找、高级或信托岗位的招聘诚信审查,以及个人自我防护——调查自身信息,了解攻击者能获取到哪些内容。
始终属于排除范围的内容:出于非合法记录目的获取私人个体的家庭住址、日常行踪、子女信息、医疗状况、移民身份或性取向;任何与调查对象直接接触的行为;任何理性人会认定为监视的行为。如果你的目标是当面对峙、羞辱或接触调查对象,请立即停止。另请参阅中的美国雇佣与租赁限制条款,该条款约束了此处的大部分数据源。
dig-through-data-brokers完成标志:案件文件中存在范围说明,明确合法目标,并列出具体的排除范围。
Step 2 — Bind the name to a second selector
步骤2 — 将姓名与第二个识别信息绑定
Never search on a name alone. Pick an anchor and carry it into every query.
| What you hold | First move | Why |
|---|---|---|
| Name + employer | Professional network, company bios, press releases | Employment is the strongest cheap anchor; it dates the person and gives a city |
| Name + city/region | Local records — property, court, voter file where public, local press | Geography prunes namesakes fastest |
| Name + a photo | | A face survives name changes and transliteration |
| Name + email or handle | | Machine-unique selectors; skip disambiguation almost entirely |
| Name + approximate age | Genealogy, obituaries, licensing records | Age bands split same-name clusters cleanly |
| Name only | Stop. Go back to the requester | A bare common name is not an investigable selector |
Common-name subjects need two anchors, not one. Non-Latin-script names need the
native-script spelling plus the transliterations actually used in your sources —
search all of them, because registries, papers, and press each pick a different
romanisation.
Done when you can state a discriminating test — "my subject is the one who
worked at X in Y" — that you will apply to every candidate record.
永远不要仅通过姓名进行搜索。选择一个锚点,并将其应用到每一次查询中。
| 你已掌握的信息 | 首要操作 | 原因 |
|---|---|---|
| 姓名 + 雇主 | 专业网络、公司简介、新闻稿 | 雇佣信息是最有效的低成本锚点;它能确定调查对象的任职时间和所在城市 |
| 姓名 + 城市/地区 | 本地记录——产权、法院、公开的选民档案、本地媒体 | 地理位置能最快筛选出同名人员 |
| 姓名 + 照片 | | 面部特征不受姓名变更和音译的影响 |
| 姓名 + 邮箱或账号 | | 机器唯一识别符;几乎无需进行区分 |
| 姓名 + 大致年龄 | 家谱、讣告、许可记录 | 年龄区间能清晰划分同名人群 |
| 仅姓名 | 停止操作。返回请求方 | 单一常见姓名不具备可调查性 |
常见姓名的调查对象需要两个锚点,而非一个。非拉丁字母姓名需使用原生拼写加上你数据源中实际使用的音译形式——搜索所有形式,因为注册机构、论文和媒体各自会选择不同的罗马化拼写。
完成标志:你可以明确一个鉴别测试标准——“我的调查对象是曾在X公司Y城市任职的人”——并将其应用到每一条候选记录中。
Step 3 — Order of operations
步骤3 — 操作顺序
Cheapest, highest-yield, lowest-noise first. Do not start with data brokers; they
will hand you plausible wrong answers before you have a way to reject them.
- Structured professional record. Professional networks, employer team pages and bios, press releases, conference programmes and speaker pages. Self-published, so accurate about role and affiliation and unreliable about achievement.
- Published output. Bylines, papers, patents, standards contributions. Use
with
google-like-a-spyand exact-phrase operators. Papers carry an institutional affiliation and often an ORCID, which exists specifically to solve name ambiguity; patents carry an inventor city and an assignee company.site: - Regulated-role registers. Licensing and professional boards publish name, licence number, jurisdiction, status, and often disciplinary history. If your subject claims a regulated role, this both confirms and dates it.
- Corporate record. for directorships and shareholdings. The officer-name pivot is the highest-yield single step for anyone with business involvement.
who-really-owns-it - Public legal and property records. Court dockets, judgments, insolvency, and land registers — where and only where public in that jurisdiction.
- Social and behavioural. to enumerate accounts, then
hunt-a-handle. Deliberately late: noisiest layer, easiest to misattribute.pattern-of-life-from-socials - Aggregators. , last, and only for leads you then confirm against a layer above.
dig-through-data-brokers - Historical. for removed bios and old team pages — often the richest single source, because people scrub current pages and forget the archive.
read-deleted-pages
Full source catalogue with what each one can and cannot prove:
reference/source-catalogue.md.
Done when each layer has been worked or explicitly recorded as
not-applicable, with a reason.
先从成本最低、收益最高、噪音最少的数据源开始。不要从数据经纪商入手;在你还没有办法甄别错误信息时,他们会提供看似合理的错误答案。
- 结构化职业记录。专业网络、雇主团队页面和简介、新闻稿、会议议程和演讲者页面。这类内容由个人自行发布,因此关于职位和所属机构的信息准确,但关于成就的信息不可靠。
- 公开成果。署名文章、论文、专利、标准贡献。使用配合
google-like-a-spy和精确短语运算符进行搜索。论文会标注所属机构,通常还带有ORCID(该标识符专门用于解决姓名歧义问题);专利会标注发明人所在城市和受让公司。site: - 受监管岗位注册记录。许可和专业委员会会公开姓名、许可证号、司法管辖区、状态,通常还包括纪律处分记录。如果你的调查对象声称拥有受监管岗位,这类记录既能确认该岗位,也能确定任职时间。
- 企业记录。使用查询董事职位和股权信息。对于涉及商业活动的调查对象,通过高管姓名进行关联是最高效的单一步骤。
who-really-owns-it - 公共法律与产权记录。法院案卷、判决、破产记录和土地登记簿——仅在该司法管辖区公开的情况下查询。
- 社交与行为信息。使用枚举账号,随后执行
hunt-a-handle。特意放在后期处理:这一层噪音最大,最容易误判归属。pattern-of-life-from-socials - 聚合数据源。最后使用,且仅用于获取线索,随后需通过上层数据源进行核实。
dig-through-data-brokers - 历史记录。使用获取已删除的简介和旧团队页面——这往往是最丰富的单一数据源,因为人们会清理当前页面,但会忘记存档内容。
read-deleted-pages
完整数据源目录,包含每个数据源能证明和不能证明的内容:reference/source-catalogue.md。
完成标志:每一层数据源都已处理,或已明确记录为不适用并说明原因。
Step 4 — Record provenance as you collect
步骤4 — 收集时记录来源
Every claim gets, at capture time: the claim, the source URL, the access date, a
saved copy or archive snapshot, and which anchor let you attribute it to your
subject. Reconstructing citations at the end always fails — the page will have
changed, and you will no longer remember why you believed record 14 was the
right person.
Corroboration standard: two independent sources per claim. Independent means
different origin, not different website. Three brokers agreeing is one source,
because they buy from each other. A company bio and a press release from the same
communications team is one source. A registry filing and a bylined news article
are two.
Done when every claim in the case file carries a source, a date, and an
attribution basis.
在获取每条信息时,需同时记录:信息内容、来源URL、访问日期、保存副本或存档快照,以及用于将该信息归属到调查对象的锚点。在最后阶段重建引用必然会失败——页面可能已更改,你也会忘记为何认定第14条记录属于正确的调查对象。
核实标准:每条信息需有两个独立来源。独立指来源不同,而非网站不同。三家经纪商的一致信息仅算一个来源,因为它们互相采购数据。同一通讯团队发布的公司简介和新闻稿仅算一个来源。注册文件和署名新闻文章则是两个独立来源。
完成标志:案件文件中的每条信息都带有来源、日期和归属依据。
Step 5 — Back out when it is a different person
步骤5 — 发现错误归属时及时回溯
Actively hunt the disconfirming detail. Signals you have crossed onto a namesake:
an age or graduation year off your band by more than a few years; a location with
no plausible bridge to a known one; a career discontinuity requiring two
full-time roles at once; a middle initial that conflicts rather than merely being
absent; a relatives cluster sharing no member with the one you already had.
Do not quietly drop the record. Split the file: maintain a candidate set, and
record for each candidate what would confirm or eliminate it. Fusing two people
destroys the whole product, and it is invisible in the finished brief unless you
tracked candidates explicitly.
Done when every collected record is assigned to a named candidate, and the
non-subject candidates are documented rather than deleted.
主动寻找能否定归属的细节。表明你已误判到同名人员的信号:年龄或毕业年份与你的区间相差超过几年;所在地点与已知地点无合理关联;职业经历存在断层,需同时担任两份全职工作;中间名首字母存在冲突(而非仅仅缺失);亲属群体与你已掌握的群体无重叠成员。
不要悄悄丢弃该记录。拆分文件:维护候选集,并记录每个候选对象的确认或排除条件。将两个人的信息混为一谈会毁掉整个调查成果,且在最终报告中无法察觉,除非你明确跟踪了候选对象。
完成标志:每条收集到的记录都已分配给指定候选对象,非调查对象的候选对象已被记录而非删除。
Step 6 — Family and associate structure
步骤6 — 家庭与关联人员结构
Only when the objective requires it. Obituaries name survivors with relationships
and cities and are the most efficient family-structure source there is; genealogy
and civil-registration indexes give births, marriages, and deaths where published;
co-directorships and co-authorship give professional associates. Treat relatives
as context for disambiguation, not as targets — pivoting a full investigation
onto an uninvolved family member is out of bounds.
Done when relationships used in the brief are sourced, and no uninvolved
third party has been profiled.
仅在调查目标需要时进行此步骤。讣告会列出幸存者的关系和所在城市,是获取家庭结构最高效的数据源;家谱和民事登记索引会提供公开的出生、婚姻和死亡信息;共同董事身份和共同署名会提供职业关联人员信息。将亲属视为区分调查对象的背景信息,而非调查目标——将完整调查转向无关家庭成员属于排除范围。
完成标志:报告中使用的关系信息均有来源,且未对无关第三方进行资料构建。
Step 7 — Report
步骤7 — 撰写报告
Hand off to . Separate confirmed facts from inference,
state the disambiguation basis up front, list the candidates you eliminated, and
cut anything collected that the objective does not need.
write-the-intel-briefDone when the brief states its confidence grade per claim and its
disambiguation basis, and the surplus collection has been deleted.
转交至流程。区分已确认事实与推断内容,在开头说明区分依据,列出已排除的候选对象,并删除所有与调查目标无关的收集内容。
write-the-intel-brief完成标志:报告中每条信息都标注了置信度等级和区分依据,且已删除多余的收集内容。
Where this goes wrong
常见失误
- Name collision is under-estimated. Even an unusual name is often shared within one family — juniors, seniors, and cousins named for the same grandparent live in one city and appear in the same records.
- Aggregators launder each other's errors. A wrong middle initial or a merged household entered once propagates everywhere and then looks corroborated.
- Self-published bios are aspirational. Titles inflate, dates round, degrees get upgraded. Confirm credentials at the issuing institution or register.
- Absence of record is not absence of fact. A sparse footprint may mean a private person, a non-English footprint, a recent immigrant, or closed registries. It is not evidence of concealment.
- Photo matching is over-trusted. The same headshot on two profiles proves the profiles share an image, not a person — scrapers, stock photos, and impersonation accounts all reuse images. Confirm with a second selector.
- Name changes break continuity. Marriage, transliteration, pseudonyms, and legal changes split one trail into two, and older records under a prior name will not link themselves.
- You may be looking at a synthetic identity. Fraud cases produce subjects whose tidy, recent, shallow footprint is manufactured. A profile with no pre-existing history is itself a finding.
- 低估姓名冲突。即使是不常见的姓名,也常出现在同一个家庭中——晚辈、长辈和同名堂表亲可能住在同一城市,并出现在相同记录中。
- 聚合数据源互相传播错误。一次输入的错误中间名或合并家庭信息会传播到所有数据源,随后看似已被核实。
- 自行发布的简介存在夸大。头衔被拔高,日期被四舍五入,学位被升级。需在颁发机构或注册处核实资质。
- 无记录不代表无事实。信息足迹稀疏可能意味着调查对象是私人个体、使用非英语平台、近期移民,或相关注册处未公开信息。这不能作为隐瞒行为的证据。
- 过度信任照片匹配。两个资料使用同一张头像仅能证明它们共享一张图片,而非同一人——爬虫、库存照片和冒名账户都会重复使用图片。需通过第二个识别信息进行确认。
- 姓名变更导致线索断裂。婚姻、音译、化名和合法姓名变更会将一条线索拆分为两条,且旧姓名下的记录不会自动关联。
- 你可能在调查一个合成身份。欺诈案件中的调查对象,其整洁、近期、浅显的信息足迹是伪造的。无过往历史的资料本身就是一项发现。
Confidence grading
置信度等级
- Confirmed — two independent sources, at least one primary (a registry filing, a court record, a licensing board entry, an institutional page), that agree on the claim and on a shared discriminating anchor.
- Probable — one primary source, or two secondary sources with an anchor match, and no contradicting record found.
- Unconfirmed — single secondary source, aggregator-only, or anchor match that relies solely on name plus a broad region. Report it as a lead.
- Rejected — assigned to a different candidate. Keep it in the file with the reason.
Grade the identity attribution separately from the claim. A court record can
be entirely genuine and still not be your subject's.
- 已确认 — 两个独立来源,至少一个为原始来源(注册文件、法院记录、许可委员会条目、机构页面),且在信息内容和共享鉴别锚点上达成一致。
- 大概率 — 一个原始来源,或两个带有锚点匹配的次级来源,且未发现矛盾记录。
- 未确认 — 单一次级来源、仅来自聚合数据源,或仅依赖姓名加宽泛区域的锚点匹配。作为线索报告。
- 已排除 — 已分配给其他候选对象。保留在文件中并说明原因。
对身份归属和信息内容分别进行评级。一份法院记录可能完全真实,但仍不属于你的调查对象。
Worked example
示例案例
Objective: pre-investment diligence on "Marcus Rowntree", named as CTO of a
vendor, anchor = the employer.
- Company team page gives role and a headshot. Archive it — vendor sites churn.
- Exact-phrase search on name plus company surfaces two conference talks with the same headshot and a stated prior employer. Anchor now two-deep.
- Officer search in on the surname returns four directorships. Three list a birth month and year matching the conference bio's implied age band; one is in a different country with a birth year eleven years off — split off as candidate B, documented, not used.
who-really-owns-it - Dead end: an aggregator profile ties the name to a bankruptcy. The listed middle initial conflicts and the city has no bridge to any known location. Assigned to a third candidate; the bankruptcy does not enter the brief.
- Prior employer claim fails to corroborate — no press, no archived team page, no filing. Graded unconfirmed and flagged as a diligence question, which is itself the useful finding.
目标:对供应商CTO“Marcus Rowntree”进行投资前尽职调查,锚点 = 雇主。
- 公司团队页面提供了职位和头像。存档该页面——供应商网站经常更新。
- 使用姓名加公司的精确短语搜索,找到两场带有同一张头像的会议演讲,以及一个明确的前雇主。现在锚点有两个。
- 在中搜索姓氏,返回四个董事职位。其中三个列出的出生年月与会议简介中的年龄区间匹配;一个位于不同国家,出生年份相差11年——拆分为候选对象B,进行记录,不纳入报告。
who-really-owns-it - 死胡同:某聚合数据源资料将该姓名与一起破产案关联。列出的中间名首字母存在冲突,且所在城市与已知地点无关联。分配给第三个候选对象;破产信息不纳入报告。
- 前雇主信息未得到核实——无新闻报道、无存档团队页面、无相关文件。评级为未确认,并标记为尽职调查问题,这本身就是一项有用的发现。
Pivots
关联流程
| Selector produced | Feed into |
|---|---|
| Username or display name | |
| Email address | |
| Phone number | |
| Photograph | |
| Photo with a location question | |
| Company name or registry number | |
| Personal or vanity domain | |
| Confirmed social accounts | |
| Address, relatives, prior cities | |
| Deleted bio or old profile | |
| Finished evidence set | |
| 生成的识别符 | 传入流程 |
|---|---|
| 用户名或显示名 | |
| 邮箱地址 | |
| 电话号码 | |
| 照片 | |
| 带有位置疑问的照片 | |
| 公司名称或注册号 | |
| 个人或Vanity域名 | |
| 已确认的社交账号 | |
| 地址、亲属、曾居住城市 | |
| 已删除的简介或旧资料 | |
| 完整证据集 | |
Legal notes
法律说明
In the EU and UK, profiling a living person is processing personal data: you need
a lawful basis, and journalism, legal claims, and legitimate interests are
distinct bases with distinct limits. The subject may hold access and erasure
rights against you. In the US, using aggregator data for employment, tenancy,
insurance, or credit decisions outside a regulated consumer reporting agency is a
compliance violation however public the data feels — see
. Driver and vehicle records are restricted-purpose in
many jurisdictions. If your research is adverse and might reach proceedings,
capture evidence so it survives challenge: timestamped, hashed, archived.
dig-through-data-brokersFor self-defense, run this workflow on yourself, use the opt-out guidance in
, and use so the
searching itself does not create new exposure.
dig-through-data-brokersinvestigate-without-getting-made在欧盟和英国,对在世人员进行资料构建属于处理个人数据:你需要合法依据,而新闻报道、法律主张和合法利益是不同的依据,各有不同限制。调查对象可能对你享有访问权和删除权。在美国,将聚合数据源用于雇佣、租赁、保险或信贷决策(且未通过受监管的消费者报告机构)属于合规违规,无论数据看似多么公开——请参阅。在许多司法管辖区,驾驶员和车辆记录仅限特定用途。如果你的调查具有对抗性且可能进入诉讼程序,请留存证据以便应对质疑:带时间戳、哈希值、存档的证据。
dig-through-data-brokers对于自我防护,请针对自身执行此工作流,使用中的退出指导,并使用,确保搜索行为不会产生新的信息暴露风险。
dig-through-data-brokersinvestigate-without-getting-made