Transportation equity is an interdisciplinary agenda that requires both transportation and social inputs. Traditionally, transportation equity information are sources from public libraries, conferences, televisions, social media, among other. Artificial intelligence (AI) tools including advanced language models such as ChatGPT are becoming favorite information sources. However, their credibility has not been well explored. This study explored the content and usefulness of ChatGPT-generated information related to transportation equity. It utilized 152 papers retrieved through the Web of Science (WoS) repository. The prompt was crafted for ChatGPT to provide an abstract given the title of the paper. The ChatGPT-based abstracts were then compared to human-written abstracts using statistical tools and unsupervised text mining. The results indicate that a weak similarity between ChatGPT and human-written abstracts. On average, the human-written abstracts and ChatGPT generated abstracts were about 58% similar, with a maximum and minimum of 97% and 1.4%, respectively. The keywords from the abstracts of papers with over the mean similarity score were more likely to be similar whereas those from below the average score were less likely to be similar. Themes with high similarity scores include access, public transit, and policy, among others. Further, clear differences in the key pattern of clusters for high and low similarity score abstracts was observed. Contrarily, the findings from collocated keywords were inconclusive. The study findings suggest that ChatGPT has the potential to be a source of transportation equity information. However, currently, a great amount of attention is needed before a user can utilize materials from ChatGPT
翻译:交通公平是一个需要交通及社会学两个学科知识的跨学科议题。传统上,交通公平信息来源于公共图书馆、会议、电视、社交媒体等。人工智能(AI)工具包括高级语言模型如 ChatGPT 成为了越来越喜欢的信息来源。然而,它们的可信度尚未得到充分的探索。本研究探讨了 ChatGPT 生成的与交通公平相关的信息的内容和实用性。研究使用了从 Web of Science(WoS)存储库检索到的152篇文章。针对每篇论文的标题,设计了一个提示语,以便 ChatGPT 提供摘要。 ChatGPT 生成的摘要与人工撰写的摘要进行了对比,使用了统计工具和无监督文本挖掘。结果表明,ChatGPT 与人工撰写的摘要之间存在较弱的相似性。平均而言,人工撰写的摘要和 ChatGPT 生成的摘要相似度约为58%,最高和最低分别为97%和1.4%。相似度得分超过平均值的论文摘要中的关键词更可能相似,而低于平均得分的摘要中的关键词不太可能相似。高度相似的主题包括获取、公共交通和政策等。此外,高和低相似得分摘要的关键词集聚模式存在明显的差异。相反,聚集关键词的研究结果并不明确。研究结果表明,ChatGPT 具有成为交通公平信息来源的潜力。然而,目前,在用户可以利用 ChatGPT 材料之前,需要更大的关注。