Replication Data for: Thematic analysis of in-group and out-group debates in an online right-wing extremist community

The resurgence of Right-Wing Extremism (RWE) has become a cause for concern in Western countries during the twenty-first century. An increase in white nationalist sentiment in recent years has provided impetus to understand the contemporary drivers of far right ideology. This study examines in-group and out-group debates on Stormfront.org, which is the largest and oldest online community dedicated to white nationalism and extreme right-wing political views. It used a dataset of approximately 1m posts collected from the open Opposing Views forum on Stormfront from the period 2001 to 2020 to create a corpus of over 195m words for thematic analysis. A Natural Language Processing (NLP) model was used to analyze the corpus and a topic modeling algorithm was used to identify key topics in the debate. The study finds that key issues being debated between in-group and out-group members of the Stormfront online community relate to perceptions of white identity, African American identity, racial issues, conservative political issues, and the history and politics of the United States. These findings highlight the issues of mutual importance to in-group and out-group members and identify opportunities for further research into the ideology of online RWE communities.

二十一世纪以来，右翼极端主义（Right-Wing Extremism, RWE）的死灰复燃已在西方国家引发广泛担忧。近年来白人民族主义情绪的抬头，为探究极右翼意识形态的当代驱动因素提供了研究契机。本研究针对Stormfront.org平台上的群内与群外辩论展开分析，该平台是全球规模最大、历史最悠久的专注于白人民族主义与极右翼政治观点的在线社区。本研究从Stormfront平台的公开论坛“Opposing Views”中采集了2001年至2020年间的约100万条帖子，构建了包含逾1.95亿词的语料库用于主题分析。研究采用自然语言处理（Natural Language Processing, NLP）模型对该语料库进行分析，并通过主题建模算法识别辩论中的核心议题。研究发现，Stormfront在线社区的群内与群外成员所辩论的核心议题涉及白人身份认同、非裔美国人身份认同、种族问题、保守派政治议题以及美国历史与政治。上述研究结果明确了群内与群外成员共同关注的议题，并为后续针对在线右翼极端主义社区意识形态的研究指明了方向。