摘要
控制感是人类的根本需要,相信世界稳定有序、"善有善报、恶有恶报"的正义动机可以帮助我们获得控制感.正义动机是一个内隐加工过程,指向他人遭遇(而非自身遭遇)或社会整体的正义动机是人类根深蒂固的价值判断和社会态度,但由于受传统方法社会赞许效应和样本偏差影响,如何在内隐层面准确测量和验证正义动机的他人凸显效应一直是正义研究的难题.因此,本研究采用词嵌入联想测验(word embedding association test)的词、句向量指标,检验正义动机在内隐水平上的他人凸显效应.微博语料库的词向量分析表明,"他人"-"正义"的余弦相似度(语义关联度)显著大于"自我"-"正义"余弦相似度;谷歌BERT模型的句向量分析也重复了上述结果.总之,基于机器学习的词嵌入联想测验证明了内隐正义动机的他人凸显效应,即人们在潜意识里相信他人(而非自己)遭遇或社会整体是个简单美好的正义世界.这提示我们,看似无序的网络世界却蕴含民众对社会秩序的强烈需要,而词嵌入联想测验也为无结构文本背后的社会态度测量提供了新的算法.
Maintenance of control and non-randomness is the fundamental need of human beings,and people are motivated to see social and physical environments as stable and orderly,so that the belief about the controlled and nonrandom world is protected.According to just motive theory,people tend to believe in a just world,in which good deeds get rewarded and bad evils get punished,and this belief helps individuals get the sense of control.Otherwise,it is difficult for individuals to pursuit long-term goals and obey social rules in ordinary lives.Recent evidence shows that there are self-others’distinctions regarding belief in a just world(BJW).In particular,BJW for others is found to be processed more primitively and influenced more possibly by cultural norms,whereas BJW for the self is processed more elaborately and influenced more possibly by personal experiences.And BJW for others is more related to the indicators of human values and social attitudes,such as world assumption and justice restoration,whereas BJW for the self is more related to the indicators of personal wellness,such as self-esteem and mental health.More important,justice motive is an implicit process,and in particular justice motive for others(vs.for the self)plays a critical role in shaping human values and social attitudes,which is often hidden in the explicit measurement because of social desirability and sample bias.However,it is difficult for researchers to measure the implicit process of justice motive,especially for others’lives and the whole society.Many studies,especially those conducted among college students and middle class populations,yielded that BJW for others was endorsed lower than BJW for the self.Therefore,more and more researchers recommend that BJW(s)should be measured through implicit tests and large-scale samples.Based on machine learning and Word Embedding Association Test(WEAT),the present research was to test the robust effect of justice for others in terms of the word or sentence vector similarity,with a greater similarity i
作者
吴胜涛
杨晨曦
王世强
马瑞启
韩布新
Shengtao Wu;Chenxi Yang;Shiqiang Wang;Ruiqi Ma;Buxin Han(School of Sociology and Anthropology,Xiamen University,Xiamen 361005,China;School of Electronic Science and Engineering,Xiamen University,Xiamen 361005,China;School of Informatics,Xiamen University,Xiamen 361005,China;Institute of Psychology,Chinese Academy of Sciences,Beijing 100101,China)
出处
《科学通报》
EI
CAS
CSCD
北大核心
2020年第19期2047-2054,共8页
Chinese Science Bulletin
基金
中央高校基本科研业务费专项(20720181086)
厦门大学本科教学改革专项经费(2019Y1135)资助。
关键词
正义动机
自我
他人
机器学习
词嵌入联想测验
justice motive
self
others
machine learning
word embedding association test
