Ujah Otobo I, Olaore Pelumi, Nnorom Onome C, Ogbu Chukwuemeka E, Kirby Russell S
College of Public Health, University of South Florida, Tampa, FL, United States.
Department of Community Medicine, Jos University Teaching Hospital, Jos, Nigeria.
Front Glob Womens Health. 2023 May 4;4:1149441. doi: 10.3389/fgwh.2023.1149441. eCollection 2023.
The decision of the US Supreme Court to repeal sparked significant media attention. Although primarily related to abortion, opinions are divided about how this decision would impact disparities, especially for Black, Indigenous, and people of color. We used advanced natural language processing (NLP) techniques to examine ethno-racial contents in Twitter discourses related to the overturn of .
We screened approximately 3 million tweets posted to discussions and identified unique tweets in English-language that had mentions related to race, ethnicity, and racism posted between June 24 and July 10, 2022. We performed lexicon-based sentiment analysis to identify sentiment polarity and the emotions expressed in the Twitter discourse and conducted structural topic modeling to identify and examine latent themes.
Of the tweets retrieved, 0.7% (= 23,044) had mentions related to race, ethnicity, and racism. The overall sentiment polarity was negative (mean = -0.41, SD = 1.48). Approximately 60.0% (= 12,092) expressed negative sentiments, while 39.0% (= 81,45) expressed positive sentiments, and 3.0% (= 619) expressed neutral sentiments. There were 20 latent themes which emerged from the topic model. The predominant topics in the discourses were related to "racial resentment" (topic 2, 11.3%), "human rights" (topic 2, 7.9%), and "socioeconomic disadvantage" (topic 16, 7.4%).
Our study demonstrates wide ranging ethno-racial concerns following the reversal of and supports the need for active surveillance of racial and ethnic disparities in abortion access in the post- era.
美国最高法院推翻（某项裁决）的决定引发了媒体的广泛关注。尽管该决定主要与堕胎相关，但对于这一决定将如何影响差异，尤其是对黑人、原住民和有色人种的差异，人们看法不一。我们使用先进的自然语言处理（NLP）技术来研究与（某项裁决）推翻相关的推特话语中的种族内容。
我们筛选了发布到（相关）讨论中的约300万条推文，并识别出2022年6月24日至7月10日期间发布的、包含与种族、族裔和种族主义相关提及的英文独特推文。我们进行了基于词典的情感分析，以确定推特话语中表达的情感极性和情绪，并进行了结构主题建模，以识别和检查潜在主题。
在检索到的推文中，0.7%（=23,044条）包含与种族、族裔和种族主义相关的提及。总体情感极性为负面（均值=-0.41，标准差=1.48）。约60.0%（=12,092条）表达了负面情绪，而39.0%（=8,145条）表达了正面情绪，3.0%（=619条）表达了中性情绪。主题模型中出现了20个潜在主题。话语中的主要主题与“种族怨恨”（主题2，11.3%）、“人权”（主题2，7.9%）和“社会经济劣势”（主题16，7.4%）相关。
我们的研究表明，（某项裁决）被推翻后存在广泛的种族问题，并支持在（该裁决）后的时代积极监测堕胎服务中种族和族裔差异的必要性。
