分析特定于堕胎的Reddit论坛,产生与医疗信息寻求和个人世界观有关的各种对话:数据挖掘和自然语言处理比较研究
Danny Valdez1, Lucrecia Mena-Meléndez1, Brandon L Crawford1
1Department of Applied Health Science, Indiana University School of Public Health, Bloomington, IN, United States.
Journal of medical Internet research
|February 14, 2024
概括
在Reddit论坛上的社交媒体挖掘揭示了除了简单的标签之外的细微堕胎观点. 关于r/AbortionDebate的讨论集中在支持和信息上,而r/AbortionDebate的讨论集中在道德和法律的复杂性上.
科学领域:
- 社交媒体分析 社交媒体分析
- 自然语言处理自然语言处理.
- 公共卫生传播 公共卫生传播
背景情况:
- 堕胎的态度是复杂的,不能被二分化的标签所捕捉.
- 生活经历和环境塑造了对堕胎的微妙观点.
- 社交媒体平台可以提供对公共话语和与堕胎相关的健康信息搜索的见解.
研究的目的:
- 用自然语言处理和社交媒体挖矿分析Reddit论坛上的与堕胎有关的讨论.
- 为了确定r/Abortion和r/AbortionDebate分片中的关键主题和情绪.
- 了解个人如何在在线空间中传达他们对堕胎的看法.
主要方法:
- 应用了基于神经网络的主题建模管道BERTopic,以发现来自r/Abortion的2,151个帖子和来自r/AbortionDebate的2,815个帖子中的主题.
- 利用代一致性得分计算来确定每个子reddit的最佳主题数量.
- 通过Valence Aware词典和Sentiment Reasoner进行情感分析,并使用Text2Emotion词典进行情感分析.
主要成果:
- 在两个子节目中确定了10个不同的主题,其中r/Abortion关注信息共享和社会支持,r/AbortionDebate关注道德,道德和法律辩论.
- 情绪分析显示,这两种子网的影响几乎是中性的 (r/Abortion: 0.01,r/AbortionDebate: -0.06).
- 与r/AbortionDebate相比,恐惧在r/Abortion (0.36) 中略高,否则情绪一致.
结论:
- 雷迪特论坛促进了各种堕胎信仰和经验的分享,挑战了简单的身份标签.
- 话语风格有很大的不同,r/Abortion作为一个信息/宣传中心,r/AbortionDebate作为一个辩论平台.
- 社交媒体分析为堕胎观点和情况的复杂性和政治性质提供了宝贵的见解.
更多相关视频
09:20Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications
Published on: February 23, 2019
8.7K
07:41Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
9.0K
相关概念视频
Regression Toward the Mean
6.3K
Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
6.3K
Comparing the Survival Analysis of Two or More Groups
186
Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
186
Statistical Software for Data Analysis and Clinical Trials
550
Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
550
