伊利诺伊社会态度聚合语料库 (ISAAC)：一个用于大规模分析社会群体话语的开放工具与可复现流程

arXiv cs.CL 论文
corpus social-analysis reddit open-source pipeline nlp research

摘要

我们介绍 ISAAC，一个包含超过5.27亿条英文 Reddit 帖子的开放语料库，用于分析社会群体话语，并具有多步骤的标注和分析流程。它支持跨类别比较和公众态度的时序追踪，可通过网络应用和编程接口访问。

arXiv:2609.27059v1 Announce Type: new Abstract: We introduce the Illinois Social Attitudes Aggregate Corpus (ISAAC), an open, modular, and accessible corpus of 527 million+ English-language Reddit posts selected for relevance to six key social group distinctions based on race, sexuality, age, ability, body weight, and skin tone, covering the 17-year period from 2007 to 2023. A multi-step, human-audited filtering pipeline was used to keep irrelevant content in the curated dataset below 10%, both overall and for each social group distinction. Each post was then algorithmically annotated with the user's estimated home region, along with a suite of validated off-the-shelf and custom semantic labels including moralization, sentiment, emotion, and linguistic generalization. We confirm the validity of the resulting corpus through convergent evidence linking ISAAC to macro-level societal trends, such as online search behavior, temporal spikes during major societal events (both nationally and regionally), and long-term shifts in public attitudes. By offering a unified, public infrastructure, ISAAC eliminates research fragmentation and enables seamless replication while supporting diverse empirical workflows at scale. Specifically, ISAAC allows investigators to perform cross-category comparisons, conduct high-precision tracking of long-term temporal shifts in social group discourse, and map spatial variation onto localized public opinion and policy outcomes. ISAAC's fully public, modular pipeline facilitates easy extension of the corpus to new platforms, languages, and social categories. To accommodate various research needs, ISAAC is accessible both without coding through a point-and-click website and labeler web-apps, and programmatically via an SQL playground, a Python package, and HuggingFace.
查看原文
查看缓存全文

缓存时间: 2026/09/24 09:13 

# The Illinois Social Attitudes Aggregate Corpus (ISAAC): An Open Tool and Reproducible Pipeline for Analyzing Social Group Discourse at Scale
Source: [https://arxiv.org/abs/2609.27059](https://arxiv.org/abs/2609.27059)
[View PDF](https://arxiv.org/pdf/2609.27059)

> Abstract:We introduce the Illinois Social Attitudes Aggregate Corpus \(ISAAC\), an open, modular, and accessible corpus of 527 million\+ English\-language Reddit posts selected for relevance to six key social group distinctions based on race, sexuality, age, ability, body weight, and skin tone, covering the 17\-year period from 2007 to 2023\. A multi\-step, human\-audited filtering pipeline was used to keep irrelevant content in the curated dataset below 10%, both overall and for each social group distinction\. Each post was then algorithmically annotated with the user's estimated home region, along with a suite of validated off\-the\-shelf and custom semantic labels including moralization, sentiment, emotion, and linguistic generalization\. We confirm the validity of the resulting corpus through convergent evidence linking ISAAC to macro\-level societal trends, such as online search behavior, temporal spikes during major societal events \(both nationally and regionally\), and long\-term shifts in public attitudes\. By offering a unified, public infrastructure, ISAAC eliminates research fragmentation and enables seamless replication while supporting diverse empirical workflows at scale\. Specifically, ISAAC allows investigators to perform cross\-category comparisons, conduct high\-precision tracking of long\-term temporal shifts in social group discourse, and map spatial variation onto localized public opinion and policy outcomes\. ISAAC's fully public, modular pipeline facilitates easy extension of the corpus to new platforms, languages, and social categories\. To accommodate various research needs, ISAAC is accessible both without coding through a point\-and\-click website and labeler web\-apps, and programmatically via an SQL playground, a Python package, and HuggingFace\.

## Submission history

From: Babak Hemmatian \[[view email](https://arxiv.org/show-email/78ba128c/2609.27059)\] **\[v1\]**Tue, 22 Sep 2026 20:59:57 UTC \(2,720 KB\)

相似文章

ACAT：一个用于高效基于方面情感数据集标注的协作平台

arXiv cs.CL

ACAT 是一个基于 Web 的协作标注平台，支持四种基于方面的情感分析（ABSA）工作流，其核心特性是在导出时自动运行 ETL 流水线以计算标注者间一致性（IAA）指标，从而直接生成可用于训练的数据集。该平台在 1,002 条餐厅评论上完成了验证，标注中位耗时为 31.58 秒，原始 IAA 最高达 0.86。

循环中的声音：绘制参与式人工智能图谱

arXiv cs.AI

本文提出了一个可复现的协议，用于构建参与式人工智能项目的开放存储库和交互式地图集，分析了131条记录以揭示地理和生命周期模式，并提出了一个默认参与式人工智能基础设施的框架。