Big Five: What User Posts Say?
Author:
Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-43789-2_7
Reference23 articles.
1. Azucar, D., Marengo, D., Settanni, M.: Predicting the big 5 personality traits from digital footprints on social media: a meta-analysis. Personality Individ. Differ. 124, 150–159 (2018). https://doi.org/10.1016/j.paid.2017.12.018
2. Bai, S., Hao, B., Li, A., Yuan, S., Gao, R., Zhu, T.: Predicting big five personality traits of microblog users. In: 2013 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT), vol. 1, pp. 501–508 (2013). https://doi.org/10.1109/WI-IAT.2013.70
3. Boot, P., Zijlstra, H., Geenen, R.: The Dutch translation of the linguistic inquiry and word count (LIWC) 2007 dictionary. Dutch J. Appl. Linguist. 6(1), 65–76 (2017). https://doi.org/10.1075/dujal.6.1.04boo
4. Chancellor, S., Choudhury, D.: Methods in predictive techniques for mental health status on social media: a critical review, vol. 3 (2020). https://doi.org/10.1038/s41746-020-0233-7
5. Deeva, I.: Computational personality prediction based on digital footprint of a social media user. Procedia Comput. Sci. 156, 185–193 (2019). https://doi.org/10.1016/j.procs.2019.08.194. 8th International Young Scientists Conference on Computational Science, YSC2019, 24–28 June 2019, Heraklion, Greece
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
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