[目的/意义]尽管社交网络为用户提供了自由表达观点的平台，但在社交网络舆情形成和发展过程中，网民形成的群体极化也带来了严重的社会、经济和政治冲击，理解群体极化现象成为社交网络舆情发展中的新问题。[方法/过程]从数据层、分析层和概念层三个层面构建数据驱动的社交网络舆情极化群体用户画像模型，采用网络爬虫收集新浪微博平台中的“离婚冷静期”舆情话题数据，并对极化群体演化及类型、静态特征、动态特征、各时期极化群体进行画像分析。[结果/结论]数据分析结果表明，极化意见动态演变过程中，极化群体呈现由多极化向两极化转变的趋势。各个时期不同立场的极化群体画像呈现出复合性特征，既存在相同规律又存在明显差异。本研究丰富了群体极化和画像研究的理论和方法，并通过实证分析为网络舆情的干预和引导提供了实践指导。

[Purpose/significance] Although social networks provide a platform for users to freely express their opinions, the group polarization formed by Internet users during the formation and development of social network public opinion also brings serious social, economic and political impacts.The phenomenon of understanding group polarization becomes a new problem in the development of social network public opinion.[Method/process] A data- -driven user portrait model of polarized groups in social networks is constructed at three levels: data level, analysis level and conceptual level. A web crawler is used to collect data on the topie of“divoree cooling- -off period" in Sina W eibo platform the evolution and types of polarized groups, static characteristics, dynamic characteristics, and portrait analysis of polarized groups in each period are also analyzed.[Result/conclusion] The results of data analysis show that polarized groups show a trend from multi-polarization to bipolarization during the dy namic evolution of polarized opinions. The portraits of polarized groups with different positions in each period show composite characteristics, with both the same patterns

and obvious differences. This study enriches the theories and methods of group polarization and portrait research, and provides practical guidance for the intervention and guidance of online public opinion through empirical analysis.