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 2025-11-14 — cumulative data.个体自述具备特征X的比率为多少？ 自2025年7月8日起，本研究以每日频次对小型美国成年人随机样本开展调研。受访者需回答大量形如「今日<标记符（signifier）>是否可描述你自身？」的问题。 本仓库中的ipseity-daily-aggregated.csv文件收录了截至2025年7月28日的汇总调研结果，各字段说明如下： 标记符（signifier）：用于描述的单词、短语或表情符号 肯定应答数（yes_count）：累计所有调研中选择「是」的受访者总人数 否定应答数（no_count）：累计所有调研中选择「否」的受访者总人数 万人群患病率（prevalence_per_10k）：每10000名美国成年人中预计给出肯定应答的人数估算值，计算方式为 yes_count / (yes_count + no_count) × 10000 最早观测日期（earliest_obs_date）：该标记符首次展示给受访者的日期。标记符从长列表中随机选取，系统会不定期新增、删除标记符，或调整其采样优先级。 最晚观测日期（latest_obs_date）：该标记符最近一次展示给受访者的日期（距当前时间最近的一次）。 本数据集版本创建于2025年11月14日，包含累计调研数据。