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I'm referring to frequency tables such as this one:. To take one example, it lists words like 商 and 业 in the top 500 characters and words like 买 and 卖 in the second 500 characters.

That's true even though 商 业 and 买卖 both loosely mean "business."

Are these relative frequencies valid across the board or does the average person use 买卖 more in speaking rather than writing?

3 Answers 3

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Of course it is. Interjections are far more common in any spoken language compared to its written counterpart. Chinese also consists of many words and phrases that are very formal and rarely spoken.

https://naccl.osu.edu/sites/naccl.osu.edu/files/NACCL-21_Vol._1--Hongyin_Tao--pp._13-27.pdf could be taken as a starting point.

While the ten most common written characters are 的,一,是,不,了,在,人,有,我 and 他, the most spoken ones are 的,是,我,就,不,你,了,那,啊 and 个。

那个 and 啊 stand out in spoken Chinese, as does 你, since written language usually addresses a collective.

嗯 occupies place 2042 in the written frequency list, but position 30 in the spoken. Similar for 吧 and 哦.

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I made a plot (below) of spoken vs. written character frequencies. Note that both the x- and y-axes are logarithmic, and I restrict to characters used 100+ times in both the spoken and written corpora.

spoken characters vs. written characters

The written frequencies (x axis) are from Jun Da (MTSU) which I understand combines fiction and non-fiction written Chinese. The spoken frequencies (y axis) are from the SUBTLEX-CH dataset for movie subtitles.

As you can see, there's a weak correlation (R^2 = 0.64).

Those that appear more commonly in spoken Chinese are indeed especially interjections (e.g. 啊 吧 吗) (as noted by user4452) and very common terms (e.g. 谢 好 很 我). More precisely, they are as follows (left => greater bias towards spoken Chinese):

嗨 呃 嘿 哦 噢 婊 嗯 歉 棒 呦 茱 谢 喔 吗 啊 诶 哇 洙 吧 你 矶 爸 糕 坨 酪 妈 嗑 屁 槟 喂 糟 哔 咪 谎 屎 嘛 氪 蕾 汰 唔 伙 揍 赢 柠 鱿 孬 跆 我 咖 妞 嘘 坞 榄 蛋 么 怎 疯 什 佬 蠢 啡 傻 莓 帮 馅 杉 玩 抱 啤 酗 圾 靓 淇 垃 欢 蹈 匙 铐 钥 橄 错 好

Those that appear more commonly in written Chinese seem to be more formal terms (e.g. 民 政 社 济), some grammar particles (e.g. 地 中 于), and some common surnames (e.g. 刘 陈 赵 徐 宋). More precisely, they are as follows (left => greater bias towards written Chinese):

赵 徐 亦 刘 县 宋 江 仲 郑 译 吴 杨 彭 魏 冯 郭 革 耕 趋 纲 济 贸 企 乾 惟 饲 涛 岂 粮 陵 础 嫂 毅 辟 京 玄 陈 菩 薛 臣 岭 党 湾 倡 愣 昌 央 萧 纷 均 吨 蔡 泛 僧 吾 玲 践 撰 侯 迅 柳 曹 驻 辰 颇 卿 芳 乃 增 耸 梁 茂 

For completeness, here's the whole list (left => greater bias towards spoken Chinese; right => greater bias towards written Chinese):

嗨呃嘿哦噢婊嗯歉棒呦茱谢喔吗啊诶哇洙吧你矶爸糕坨酪妈嗑屁槟喂糟哔咪谎屎嘛氪蕾汰唔伙揍赢柠鱿孬跆我咖妞嘘坞榄蛋么怎疯什佬蠢啡傻莓帮馅杉玩抱啤酗圾靓淇垃欢蹈匙铐钥橄错好鲨让瘾芭哪妍诉酱漂舞饼喜聊绑趴跟厕拯檬砸谁朋嘣笨猜找甜烤豁妮孩晚淘赌誓莉呐做很诞搞祝噩痴烊琳茜俩赛泳莎狗迪餐贝真狱饪拜昨裤知啥呢没杀想蝙妓厌踢铉啦杯磅惹菠陪祷薯酷扔乖蜴茄快烦嗝觉瞧吻诅谅娅爱汀们拿逮踪唱她该警澡友嗷掉爽纽祈飙遛秒尸那肯混给辜吵榈搬癖贱枪婚滚臭辣偷呗告佑雇搭挺听咯别狙兄丢骗喽橙舔蟑弄甩档杰跤救炒钱詹死喝踝寓孕憾飓闭脏袜蒂鳄儿鬼干码看蜥夥捅拍凯像厨去鲍咻刚橘酒疚歌赚娜莱撒椰乔茉耍车麻候聪了扯醺还妆忘铛忏尬尴艾熨浴恋跳踹男碰需嫉太是抓汁演瑞蹩妒萝宝肮鞋裙要会睡呆再崽缉试哥琪道擎走逍蜘打点摔喵痫吓阱骄奶饿扮凶糖弟话盒沃趣醒谈礼毯女隧魅翰扉都醉恤这烂搅乐就篮洗靴炬薇样妹不钟尝渣炫橱扰箱辆陛瞒讣请芥瘀吃瞎嘴跑趟鸡锁疤泡汤希剪回栋椒欠猫戏橇贩姐罐店球扳迈瘸瓜穿买个犯懦衬咱煎叫卡咒鲑把氓怪伤沮果劫托尉恭狂臀害媛芮懂嫌掐傲烫丑纹蹭愉掰带能唯烷圣坏室邀趾事忙停猥拷亲束熬蝠今拳姆离哟里剩叔他炖擅恩幸迎腌逗赎来棕毒票戴蜜犬喋账帅查亮囚捐桶您疼尿季感捡珀垫迷哎怖爵胎怜先搜开卖过黛魔探愚拌兹咙摄街螃弗俱祟嫁得聆兔妻撞娩电篝玛但叛盹份娃浣克厄逛尼录焊麦说芙父瑟戒羞姻休虐殴呀躲床撬瓶见兴踩吸现只猪赂虱剃肋牢剁放拾袋医亵抢卦房哈晕谍虾永盯迟闯稣拽痘选挑担洛蛛侏丈油岌唬够浪弃矩曝抉毁螂悔葬天婆窒厩镯唠骚到耶起有留佣始娶窃牌痕捕侣坐巫熏殡练姬可签薰冠翘衣玷早宠班送漏缸讶味案巾痣意崔逃榨饭庭滩腿锯宵认碟待些霉帕白套仔梦盔烹奖恶记寐匹瑕柜睾住蒜胖子嬉呕菲酮士望怕曼爆择星婴冒溺罪对直岁在貂亨跷博冻次垒拼铲手链骰址楚昵最算等橡萨底恕监许丽准棍奥确卧胶唧蜡午享渍非裸侄髅撑完粉诡证租被偶挡蛤甥奸伴操控恨皂帽戮挖比备骷斯豚赦块号照丹胳捣陌恺巧勺姨努才慷周赶羔宴付愿如信播脐裆魂鼠奇渎聚膏血匿煮哒娱下滑衫助锤猎办舒屉逼疽继失私饵蕉课讨驾镜疹炸西帝小兮保嘲撕思耻松讪久伦超悍绯为音蹲蘑伍邮侮敢生楼拖醋娘戳烘擦每片猴板恐老换瞄症钻熊森谬撼烧绊牛胁泄抛彩脖己蚤疱摩垮黏嗒谋泵阻逞绳拉池泰猾兜芝察馆脱寄剧约豌碎盗简吐膊游诈酥安梯噎剂边险肉芬丝镖墨浆脑冰护钓葵也明圈苹废赃蝴马豆鄙堕问切枕幻静哭钝渴的叨绝密疵吉膛砍劲情辱上毙差家崩漫陨咬靠释官辈挣癫常痊奎溜磨名母尔难绅节柯止诺淋多碾替遇秘蟹钳膝受稍伊搏东缠钉涯藏词蹊谣心蝎僵忆骑接续迹嚏濑悼呼棺坎须字祸淤坠眠谜帐塔瞌因恙菜缝痒掺校服慢篷夫婪拥何删廊画蛙秀间辛顿痞已假敲否钞肤欺以牙粪特刮狸悚活兰计堡裹窍丸惧剔倦场塌装萄人塞贺滤涂挚埋索紧逊夹顺茬一孤哼肥题架舌肠前旦妙键旅鸽堵拇噪脆轮绷冕呵虑躺阉时远拒瘟菇顾激息奋拆椅钮邻聋定宾抽锈巴允正后液胃所吊伎佳姿苯排乓裔敞脾晒塑站赡儡暴火挂雳更米邦薪诠铃从彼检腕琴消沾髦喷胸着卢杆狄当曲药勒插应烛扇珊客圭夸讽肚愧葡扫瑰乳介闻敦注关皮尺怨填尽尊怀兽危库忍豪刀颚解净粘勾件郡姗病蛮桩骨蹦除呜葱结傀寸耽笑锚箫唆弹盎园频镇佩敏憋亡然贿肾淹杂拨棘整鱼睁头堂雷咋姑倒勇累羹相砰阿谱痛敬桑它侦琼蜂毕摆嗓癌埃乱误瘤茸嚼暑藐呛咔背熄疗屠角撇靶歇寻惜丫器纸淫灯邪岔荐鸟肺刺单悯威厅槽罩摧暖闹牺冷冥写疑瘪镑霍戈出且狼绎叉训榜霹虫堆酋管罗挽拘巅清美灵肌测贾诽颗爹参花追诱懒忌惨犀黑扭奏脚瓦掩笔齿璃识嘻经师拐队扣狮庇押派路狩惩赏颜肖膀求玻悲答珍童绪纱扎宰烬厉透桌睛汽故变洁败收墓尾狡募苔惊婶惦顶貌捎梭缪视任维总自佐屋趁鲁坦嗜德憎布摸夜末苛廉谊枭必另借仓挪热估陷烟瘩牵蛇仇浇刷蓝饰勋遗墅退辩唤褶焕阁郁面模击辞置瞳碳溅吹陋破揭磕加根修亚墙遍盖全睹牧讲影疙牲夷身绰丁蒙实狠肪律诚少线和梳卑招辙朗系叮伯养袭终运发耀熟睫郎痪折韦喉赋色炉首赐局崭几船刻啃贼划滋漆包触胺盘闲评叽阑近铎员惑掘贴昏匪犹气躁输命拧勃夏随痉用荣处射茨庆扒读慈铅堪碗脉朵磺巡诊纳唇攒艰莫位负寞鹰饮鹉格鼾栅玫斐赖拦栏痹捉乒昂交隔福梨隐决爷幕持轨伪机肛黎簧爬彗搐独坟泣暂贞精费蚁脸胆颅幽残无蝇芯困投桃臂冲守筋割亥露窥辫考习工荧沙催新闸咨免伞熔重货硬舱灌腥遥龟唾欣表哮普兆坚张朴抹宿凳簿挨行启誉驴调万绒奢高锻淑稽半豹绍驼饶闷州两愤燃拭棚剖进氧封压笛孽滴段座厢遵赞闪唉胡染溃捏承鼻玺舅挛驯晨户易歹钢狐驶窗惯窖责忠肢零复指吼况钩挤绞筹踏跪酿馈胜凌弥碍恢湿氮尖坪樱语窝袱杜壮避法腓披徽蚂乎徒赠媒幢矮丧雄葛谤蔬某短轻羊吞审栓咎飞啧惺壳大健议居登肿适熙荒爪通彻仪默瘫蹋斧图雅沐糊霜康眼髓蔼急脂移逝吮曾入茧鸭桔奈嚷鹦越耐嘎惕作句荡卫噬卸泼帚梅羁显力腔第螺梵波毫鹅长涕氯柔目讯概奄绕渺暗筛阪食鹿公香职询成针温磁筒英台秃利哨瑜门蒸凑挠拴腻落编旁霸支夺禽笆秽胰归雪抚稚弱报罚惫藤苦神帖预转遮郝妄翩肘腺鉴或象弊殃满慌慰容倍怒甚喻又订附哄嗅诀野联摊千轿料咏提光者灰焦撤蔓娼伟凭撮捍鲸嘀龄禁罕巷掌浑动分醇足墩瞬喘缆竭恼衅囱判衷荷合金翻厮智沼捞驭脓典妥裂左获竞励验柏咆至仰洒虔煽颠杠袒而焰瀑乘口流钠罢柬畅拣歪嘟达标滥囊描吝薄拔戚值辑盛袖坑卷粗柿配汗集晓摘水窟言骼帆妇悠风嘉鼓弯捆琢颁握俊羡引濒殿姜晃隆糙连舵界漠茶令递屏饥院强艳外歧鞠散乞烙方物骆期改灾畏揪印肩炳氛之锅伽升临泥刑本棋悬茎辐雏盼韧骸饱脊壁慨韵噜闺哀侈右壶攸咳访瘦耳洽善补教坤珠崎灭抑谐侥喳摇历盲尤品理违蝶将途刹酸功柄原型弘菌援竟殉砖迫传阴册赔司障银未鸦潜僻疏吠艘城献符叭琐硝疲桥毛世纪旧棵添碧眨褪莽举乌盐斑猩剥往洞杖腐笼雕赫同辅硫畜空嫖呱按术帘莲慕体甲艺悉级喇疮优肇极枫漱硅後寡速袍尘谨敷疫组仅酬筝腾辨贵示造芒志震条喊偿挫咕胞郊匕兑截岛状礁悦嘱嫩畸颈缩徘穆契团嗡异侬断萤甭偏并凿蚊步箭刃榴汉俄取股枚妨申缚据粥却双隶澄抬众嚎翅红专帜纠细树瞩斗百年翁亏穴性仆卜屑络木学藉雨旺其鸥裁燥姥倾栗覆纯防稳寇向浸伏网声篱勤史聘书绩蚀景此销污反授便念庞虚绿基贪返淆严肝欲匠谦掏捷六昧环耿欧芽搁舷旋三部惭膜巢吱巨粹绽遭盆衔墟雀铺储携杏睬草佛缘式炼航充咦林逻鲜幅紊围沦抗价执逸惰勿竖徊俏种掷凉宁舍豫械讼恰宇宣协馨褐突侵铝涉蓬谓距扛缺姓席柴存内孵扼拙董降锡氨类耗铁泉劳沫厦祖裴苟晋沛焚妖度仗推款穷晶富夭属腰肆地奉蓄统览棉数串碌眩潮劣争径翔椎嗽抖渗论武轴凰态五狒嚣致冈沟驱副伶酶翠项雾既材海盟互宙衰供售深效缅锋详瓣恳软甘蔽殊宜栽惠平伺奴贤绵科汇慎务躬低韩浦婿幼似挥番患损治淌古冤抄仍逆纤躯仁伸碱溢仿顽埔诬枉咚元宫购圆哑宽弦具程挟际良创觅懊潘署微淳井召植华腹响嗦咸桨灼坝矫寂般邸懈屈啪浅融宅量于攀腊谷四主稿竿崇区叠灿幌权氢絮忧层旗延愁俘谴跃浓稀镶观龙仑眷丛疾乡渡月群沸劝卵扑肃阳浮逢孔浏寝减沉俗循跨晰抵虽檐载裘纵王尚苍石夕菊冬侧八溯瓷族蹄烈驳核战析攻紫筑岗恒督称弓凹呻制虎艇扶嵌商究代呈泪擒忒苏迭境咧骂朽庸揉扁搂丙氏吩苗丘妃序初颊浩碑日牡婉设洲贷赤昔版中岩睦素二萎愈领粒赴尹慧厂阀侍旷揣括矿市奔茫凡盾源颂涅土诫齐蔑捧绸共鞭框祭遣坊掀陶舟横俯毋君唐额著财滔崖营仙导卓端揽硕廷溪猛寿虹页织劈稻绘颤委范春涨斩丰魁侠飘皱锦债振溶列涡势衡皇钙咐垂虏则质枯余广朱昆啼乏村淡币建僚贬即喀亿盏阵由滨炭泌使展驰扬七鹤敛彰朝烁跌甸柱技晤规涩山窘娥贡峰固文依卒岸鸣映颖傅澳迄黄铸兼洋悄雌培胀贫泽役廓泻征化砂斥与矛窜较泊矢咽河篇锐立秋含厚域及眉铭各义措暇羽逐娇育彬勉寺怯魄渠塘凸削梗限诗业敌煤俺章凝资壤券湖兵焉炎占诵旭采拟予研策纬缓南履堤哩轰率茅铜匆藻阅例拱润施斤茵府斜绣十嘶忽亭形匈陀稼军喧辉滞栖综勘叶述峡繁略厘丐拓衍翼国坛吟媚隙骇若阔坡迁谭玉田剑庄孙猿儒省煞届沿膨傍陆昭宛拢御伐於青芦鼎宪渊枢悟煌惶迦庙秩哗枝皆瞪孝渔掠哲晴港谕舰孟殖凤宗祥裕钦旨狭贯炮李涌寒拂窄涵缴批亩盈寨构津积社诸旱阶峻产叙竹汪邓桂渐川政燕刊云株扩籍甫益骤汝税民九北怡遂姊宏函凄乙促辖洪叹农吁禅岳媳茂梁耸增乃芳卿颇辰驻曹柳迅侯撰践玲吾僧泛蔡吨均纷萧央昌愣倡湾党岭臣薛菩陈玄京辟毅嫂础陵粮岂涛饲惟乾企贸济纲趋耕革郭冯魏彭杨吴译郑仲江宋县刘亦徐赵
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    Very interesting! Thank you for putting this together.
    – Olle Linge
    Commented May 4, 2020 at 8:05
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The site listed doesn't give a lot of information on what exactly the corpus is, but as the paper is from 2010, we can assume that there isn't quite as much bias towards social media posts as there would be if such a study occurred today. That's important because social media tends to be "written" in a register that's much more in line with the spoken register of a language compared to traditional written media.

As such, this phenomenon is not unique to Chinese, but can be noticed throughout pretty much any language with a large corpus of written media. Much like a news article in English would likely use the word "purchase" more often, whereas spoken English would tend towards "buy/bought," it would be natural for a similar situation to occur in Chinese. This would result in a different frequency distribution for characters in written Chinese as opposed to spoken Chinese.

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  • It would be awesome to see a frequency list based on spoken chinese. Commented Nov 25, 2015 at 1:57
  • @EnricoBrasil: My guess is that the way to do it would be tape record a lot of conversations, and transcribe them. Maybe "programs" such as newscasts would be intermediate between the written and spoken languages, but even movies may tell a different story.
    – Tom Au
    Commented Nov 25, 2015 at 3:11

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