Ipseity Daily Data

At what rate do individuals say they are X? Begining on 2025-07-08, I surveyed a small random sample of American adults on a daily cadence. They responded to many items of the form: Does <signifier> describe you today? The file ipseity-daily-aggregated.csv in this repository contains the aggregated results through 2025-07-28. The columns are as follows: signifier - a word, phrase or emoji yes_count - the number of respondents who answered yes (aggregated all-time). no_count - the number of respondents who answered no (aggregated all-time). prevalence_per_10k - an estimate of the prevalence per 10,000. If we were to survey 10,000 American adults, how many would we expect to respond yes to this signifier? The number is calculated as yes_count / (yes_count + no_count) * 10,000. earliest_obs_date - this date represents the first time this particular signifier was ever displayed to a respondent. Signifiers are chosen with stochasticity from a long list; new signifiers are sometimes added, old signifiers are sometimes deleted, and a signifier may be moved higher or lower in priority for sampling. latest_obs_date - the date closest to the present date on which signifier was most recently presented to a respondent. Version created on 2025-11-29 — cumulative data.个体声称自身契合X的比例是多少？ 本数据集自2025年7月8日起，按每日频次对小型美国成年人随机样本开展调研。受访者需完成多组形如「<signifier（标识词）>是否契合今日的你？」的问题。 本仓库中的`ipseity-daily-aggregated.csv`文件包含截至2025年7月28日的聚合调研结果。各字段说明如下： 1. signifier（标识词）：可指代单词、短语或表情符号 2. yes_count（肯定应答数）：累计选择"是"的受访者总人数 3. no_count（否定应答数）：累计选择"否"的受访者总人数 4. prevalence_per_10k（万分之流行率）：每10000名美国成年人中预计给出肯定应答的人数估算值。其计算方式为：yes_count / (yes_count + no_count) × 10000，即若对10000名美国成年人开展调研，预计将有多少人对该标识词给出肯定答复。 5. earliest_obs_date（首次观测日期）：该标识词首次展示给受访者的日期。标识词从长列表中随机选取，会随调研进程新增、删除或调整采样优先级。 6. latest_obs_date（末次观测日期）：该标识词最近一次展示给受访者的、距离当前日期最近的日期。 本数据集版本创建于2025年11月29日，包含累计调研数据。