In this paper, we introduce our psychological approach for collecting human-specific social knowledge (particularly personality and driving-related behavior) from a text corpus, using natural language processing (NLP) techniques. Although this social knowledge is not usually explicitly described, it is often shared among people. We used the language resources that were developed based on psychological research methods: a Japanese personality dictionary (317 words) and a driving experience corpus (8,080 sentences) annotated with behavior and subjectivity. We then automatically extracted collocations of personality descriptors and driving-related behavior from a driving corpus (1,803,328 sentences after filtering) to obtain 5,334 unique collocations. Furthermore, we designed four step-by-step crowdsourcing tasks to evaluate the adequacy of the collocations as social knowledge. The crowdsourcing resulted in 266 pieces of social knowledge, which included knowledge that might be difficult to recall by crowdworkers but is easy with which to agree. Finally, we discussed the acquired social knowledge and its implementation into systems.