TY - GEN
T1 - Acquiring social knowledge about personality and driving-related behavior
AU - Iwai, Ritsuko
AU - Kawahara, Daisuke
AU - Kumada, Takatsune
AU - Kurohashi, Sadao
N1 - Publisher Copyright:
© European Language Resources Association (ELRA), licensed under CC-BY-NC
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
KW - Driving
KW - Personality
KW - Psychology
KW - Social knowledge
UR - http://www.scopus.com/inward/record.url?scp=85096627391&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85096627391&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85096627391
T3 - LREC 2020 - 12th International Conference on Language Resources and Evaluation, Conference Proceedings
SP - 2306
EP - 2315
BT - LREC 2020 - 12th International Conference on Language Resources and Evaluation, Conference Proceedings
A2 - Calzolari, Nicoletta
A2 - Bechet, Frederic
A2 - Blache, Philippe
A2 - Choukri, Khalid
A2 - Cieri, Christopher
A2 - Declerck, Thierry
A2 - Goggi, Sara
A2 - Isahara, Hitoshi
A2 - Maegaard, Bente
A2 - Mariani, Joseph
A2 - Mazo, Helene
A2 - Moreno, Asuncion
A2 - Odijk, Jan
A2 - Piperidis, Stelios
PB - European Language Resources Association (ELRA)
T2 - 12th International Conference on Language Resources and Evaluation, LREC 2020
Y2 - 11 May 2020 through 16 May 2020
ER -