社会地位与权势的研究一直是社会语言学领域的一个热点话题。该文借助数据挖掘中的关系提取方案雪球算法(Snowball Algorithm),实现了《红楼梦》文本中候选的特征语言模式(pattern)和人物关系对之间的相互定位与赋权,对小说中频繁同现的人物对之间的社会等级关系进行挖掘,以此建立了能反映人物等级关系的有向加权人际关系网络。进一步应用最小树形图算法,生成了涵盖192个《红楼梦》主要人物的单向联通的树状社会关系图。通过这种方法生成的社会关系图不但能有效反映人际交往亲密度与社区影响力,同时还透视了人与人之间的社会等级差异。相较于单纯基于人际交往亲密程度的无向关系网络,能更加客观地表达出社会交往中人际关系网络的真实图景。
Abstract
The study of social status has always been a hot spot in sociolinguistics. In this study, we applied Snowball Algorithm and HITS Algorithm to discover the social relationships in the Chinese novel The Story of the Stone. By locating and weighting “Patterns” and “Tuples” iteratively, we construct a relationship network with social class information. Finally, we generate a min-cost arborescence of the social relationships of 192 main characters in The Story of the Stone with Chu–Liu/Edmonds' algorithm. The generated social relationship reflects not only the intimacy and social influences, but also the hierarchical inequality of people. We regard it as a more objective and authentic reflection of social relationship network in class society.
关键词
关系提取 /
权势关系 /
社会关系网络 /
最小树形图
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Key words
relationship extraction /
power relationships /
social network analysis /
min-cost arborescence
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参考文献
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脚注
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基金
国家自然科学基金(M1321005);国家自然科学基金(61472017)
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