Kuhlmann Michael, Hofmann Markus J, Jacobs Arthur M
Department of Education and Psychology, Free University Berlin Berlin, Germany.
Department of Psychology, University Wuppertal Wuppertal, Germany.
Front Psychol. 2017 Mar 13;8:343. doi: 10.3389/fpsyg.2017.00343. eCollection 2017.
How do humans perform difficult forced-choice evaluations, e.g., of words that have been previously rated as being neutral? Here we tested the hypothesis that in this case, the valence of semantic associates is of significant influence. From corpus based co-occurrence statistics as a measure of association strength we computed individual neighborhoods for single neutral words comprised of the 10 words with the largest association strength. We then selected neutral words according to the valence of the associated words included in the neighborhoods, which were either mostly positive, mostly negative, mostly neutral or mixed positive and negative, and tested them using a valence decision task (VDT). The data showed that the valence of semantic neighbors can predict valence judgments to neutral words. However, all but the positive neighborhood items revealed a high tendency to elicit negative responses. For the positive and negative neighborhood categories responses congruent with the neighborhood's valence were faster than incongruent responses. We interpret this effect as a semantic network process that supports the evaluation of neutral words by assessing the valence of the associative semantic neighborhood. In this perspective, valence is considered a semantic super-feature, at least partially represented in associative activation patterns of semantic networks.
人类如何进行困难的强制选择评估，例如对先前被评定为中性的词语进行评估？在这里，我们测试了这样一个假设：在这种情况下，语义联想词的效价具有重大影响。基于语料库的共现统计作为关联强度的一种度量，我们为单个中性词计算了由10个具有最大关联强度的词组成的个体邻域。然后，我们根据邻域中包含的关联词语的效价来选择中性词，这些邻域要么主要是积极的，要么主要是消极的，要么主要是中性的，要么是正负混合的，并使用效价决策任务（VDT）对它们进行测试。数据表明，语义邻域的效价可以预测对中性词的效价判断。然而，除了积极邻域项目外，所有项目都显示出引发负面反应的高度倾向。对于积极和消极邻域类别，与邻域效价一致的反应比不一致的反应更快。我们将这种效应解释为一种语义网络过程，该过程通过评估关联语义邻域的效价来支持对中性词的评估。从这个角度来看，效价被认为是一种语义超级特征，至少部分地体现在语义网络的关联激活模式中。
