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  "id": "social-proof",
  "name": {
    "zh": "社会认同",
    "en": "Social Proof"
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    "scope": "定义参考以上来源；数字界面示例、选择建议、条件关系及配方由本样例编辑，尚未经用户研究验证。",
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    "sources": [
      {
        "id": "socialproof-influenceatwork",
        "url": "https://www.influenceatwork.com/7-principles-of-persuasion/",
        "title": "Influence at Work · Principles of Persuasion (Robert Cialdini)",
        "checkedAt": "2026-10-20",
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        "id": "socialproof-nngroup",
        "url": "https://www.nngroup.com/articles/social-proof-ux/",
        "title": "Nielsen Norman Group · Social Proof in the User Experience",
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        "url": "https://www.ftc.gov/system/files/ftc_gov/pdf/P214800%20Dark%20Patterns%20Report%209.14.2022%20-%20FINAL.pdf",
        "title": "FTC · Bringing Dark Patterns to Light (Staff Report, September 2022)",
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  "entry": {
    "id": "social-proof",
    "type": "principle",
    "name": {
      "zh": "社会认同",
      "en": "Social Proof"
    },
    "aliases": [
      "Consensus",
      "Informational Social Influence",
      "社会证明",
      "从众效应",
      "社会认同原理"
    ],
    "granularity": "component",
    "intents": [
      "inform",
      "calibrate-trust"
    ],
    "tags": [
      "评价",
      "用户评论",
      "从众",
      "说服",
      "决策"
    ],
    "definition": "人们在不确定该怎么做时，会参照他人的行为与选择来决定自己的行为。界面中常见的形式是评分与评论、「买了这件的人也看了」这类基于他人行为的推荐、使用人数，以及来自真实用户的推荐语。它的价值在于替用户缩小不确定性：别人的经验是一条可用的信息。",
    "boundary": "社会认同本身是一条描述人如何做决定的原理，不是一种欺骗手段：真实、可核实、具有代表性的他人行为与评价，是用户有权看到的有用信息。它与「虚假稀缺」「虚假紧迫感」这类反模式相邻但不相同——问题不在于展示他人的行为，而在于展示的内容是伪造的、未披露利益关系的或不具代表性的，例如编造的「24 人正在浏览」、隐瞒报酬的推荐语。美国联邦贸易委员会把这些归为以「背书（社会认同）」为名的暗黑模式；本词条讨论的是这些反模式所借用的合法原理，判断边界在于底层数据是否真实以及利益关系是否披露，而不在于社会认同信号是否显眼。它也不同于信任校准：后者关心系统自身的信心信号是否匹配真实能力，社会认同关心的是他人的行为如何影响用户的判断。",
    "signature": [
      "界面展示了其他用户的行为、评价或选择",
      "这些信号出现在用户需要做决定、又缺少把握的地方",
      "信号能追溯到真实的底层数据，例如评论有可查看的原文与时间"
    ],
    "when": [
      "用户在多个相近选项之间犹豫，缺少判断依据",
      "产品或内容对用户来说是新的，无法凭自身经验评估",
      "已经积累了真实、足量且具有代表性的用户评价或行为数据"
    ],
    "when_not": [
      "展示的人数、评价或推荐语无法追溯到真实数据",
      "推荐语来自受雇、获赠商品或与公司有关联的人，却没有披露",
      "评价数量太少或明显偏负面，展示出来反而传达「很少有人认可」"
    ],
    "tradeoff": "真实的他人行为与评价能有效降低用户的不确定性，也让好的产品更容易被选中；代价是这份影响力同样会被伪造的信号利用，而且只挑选正面评价、隐去数量与分布时，即使每一条都是真的，整体也可能误导。",
    "comparison": {
      "focus": "用他人的行为与评价降低用户决策的不确定性",
      "mechanism": "在用户犹豫的地方展示真实、可追溯的他人选择",
      "cost": "同样的影响力容易被伪造或挑选性展示利用"
    },
    "sources": [
      {
        "id": "socialproof-influenceatwork",
        "title": "Influence at Work · Principles of Persuasion (Robert Cialdini)",
        "url": "https://www.influenceatwork.com/7-principles-of-persuasion/",
        "claim": "Cialdini 的机构网站在其说服原理中列出社会认同（又称「共识」），并把它表述为：人们尤其在不确定时，会参照他人的行动与行为来决定自己的做法；页面以酒店毛巾重复使用提示卡为例说明这一点。本词条的定义据此转述，界面中的具体做法属编辑判断。",
        "checkedAt": "2026-10-20",
        "archive": {
          "lookupUrl": "https://web.archive.org/web/20261020*/https://www.influenceatwork.com/7-principles-of-persuasion/",
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      {
        "id": "socialproof-nngroup",
        "title": "Nielsen Norman Group · Social Proof in the User Experience",
        "url": "https://www.nngroup.com/articles/social-proof-ux/",
        "claim": "Jen Cardello 于 2014 年 10 月 19 日发表的这篇文章把社会认同描述为人们参照他人行为来指导自身行为的心理现象，列举了评论、基于他人行为的推荐与他人意见等界面形式，指出显示他人认可能消除决策上的不确定，并提醒最大的风险是让人觉得认可的人太少，以及过度使用会让简单的交互变复杂。本词条据此列出界面形式与「评价太少反而有害」的情形。",
        "checkedAt": "2026-10-20",
        "archive": {
          "lookupUrl": "https://web.archive.org/web/20261020*/https://www.nngroup.com/articles/social-proof-ux/",
          "status": "unconfirmed",
          "checkedAt": "2026-10-20T07:59:47.768Z",
          "error": "save-request-failed"
        }
      },
      {
        "id": "socialproof-ftc-darkpatterns",
        "title": "FTC · Bringing Dark Patterns to Light (Staff Report, September 2022)",
        "url": "https://www.ftc.gov/system/files/ftc_gov/pdf/P214800%20Dark%20Patterns%20Report%209.14.2022%20-%20FINAL.pdf",
        "claim": "美国联邦贸易委员会 2022 年 9 月的员工报告在附录 A（第 21 页）把「背书（又称社会认同）」列为一类暗黑模式，变体包括虚假的他人活动信息（例如「24 位其他用户正在浏览此商品」）、未披露报酬、雇佣或亲属关系或经历不具代表性的消费者推荐语，以及虚假的名人背书；同一表格把虚假的高需求提示（例如「另有 20 位顾客已加入购物车」）归入稀缺一类。本词条据此划定合法原理与其被伪造使用之间的边界。",
        "checkedAt": "2026-10-20",
        "archive": {
          "lookupUrl": "https://web.archive.org/web/20261020*/https://www.ftc.gov/system/files/ftc_gov/pdf/P214800%20Dark%20Patterns%20Report%209.14.2022%20-%20FINAL.pdf",
          "status": "unconfirmed",
          "checkedAt": "2026-10-20T07:59:48.463Z",
          "error": "save-request-failed"
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    ],
    "relations": [
      {
        "target": "false-scarcity",
        "kind": "related",
        "condition": "界面显示「多少人正在浏览或购买」一类的热度数字",
        "reason": "热度数字既是社会认同信号，也被用来制造稀缺印象；数字由真实数据计算得出时属于社会认同，伪造时就落入虚假稀缺。",
        "basis": "editorial"
      },
      {
        "target": "false-urgency",
        "kind": "related",
        "condition": "他人行为信号与倒计时或「即将结束」的提示一起出现",
        "reason": "两者常被叠加在同一处施压；审查时应分别判断人数是否真实、期限是否真实，而不是因为其中一个可疑就否定另一个。",
        "basis": "editorial"
      },
      {
        "target": "disguised-ads",
        "kind": "conflicts_when",
        "condition": "推荐语或评价来自受雇或获赠商品的人，却以普通用户的口吻呈现",
        "reason": "未披露利益关系的背书让推广内容冒充独立意见，这与伪装广告是同一种问题：用户无法分辨自己看到的是信息还是宣传。",
        "basis": "editorial"
      },
      {
        "target": "trust-calibration",
        "kind": "composes_with",
        "condition": "用评价或使用人数来帮助用户判断是否采信",
        "reason": "社会认同信号也是一种信心信号；只挑选正面评价、隐藏数量与分布，会让用户的信任高于产品的真实表现。",
        "basis": "editorial"
      }
    ],
    "rules": [
      {
        "when": "界面展示人数、评分或「正在浏览」一类的他人行为信号",
        "instruction": "只展示由真实底层数据计算得出的数值；不得伪造、虚增或随机生成这些信号。",
        "strength": "must",
        "basis": "editorial"
      },
      {
        "when": "展示推荐语或评价，而作者获得了报酬、免费商品或与公司有关联",
        "instruction": "在推荐语旁边清楚披露这层关系。",
        "strength": "must",
        "basis": "editorial"
      },
      {
        "when": "选择展示哪些评价",
        "instruction": "同时显示评价数量与分布，不要只挑选正面评价，让用户能判断这些意见有多大代表性。",
        "strength": "recommend",
        "basis": "editorial"
      }
    ],
    "principle": {
      "evidenceType": "社会心理学中的说服原理，经 Cialdini 的著作普及；界面中的用法来自可用性研究机构的设计解释与消费者保护机构的执法分类",
      "limit": "本词条不复述具体实验的效应量，不主张社会认同信号一定能提高转化，也不对任何地区的法律合规作出判断；它只说明这一原理是什么、界面中的常见形式，以及合法使用与伪造使用之间的边界。"
    },
    "demo": null,
    "version": "0.1.0",
    "editorialStatus": "drafted",
    "requirements": [],
    "demoCapabilities": [],
    "implementationNote": "本词条尚无可操作示例；插画为编辑示意，用一个虚构的 FIELDNOTES 商品页说明评价与他人行为信号的位置，其中的评分与评论均为虚构占位。应用到产品前仍须确认每个信号都能追溯到真实数据，并检查利益关系是否已披露。",
    "image": {
      "src": "/images/social-proof.webp",
      "alt": "一张示意图：一个虚构的 FIELDNOTES 笔记本商品页，商品图旁边是一组五星评分和一条显示各星级数量的分布条，下方排着三张带圆形头像的评论卡片，内容以灰色占位条表示，其中一张卡片带有一个小小的披露标记；右侧一个石板蓝的推荐区块以小人像图标作标题，列出三件灰色缩略图商品，表示其他顾客也看过的商品。"
    },
    "searchTerms": [
      "ratings",
      "user reviews",
      "conformity",
      "persuasion",
      "decision-making"
    ]
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}