Pith. sign in

REVIEW

On Text-based Personality Computing: Challenges and Future Directions

Not yet reviewed by Pith; the record is open.

Re-run · record.json Download PDF Read on arXiv ↗

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2212.06711 v4 pith:PJTEIIAL submitted 2022-12-13 cs.CL cs.CY

Qixiang Fang , Anastasia Giachanou , Ayoub Bagheri , Laura Boeschoten , Erik-Jan van Kesteren , Mahdi Shafiee Kamalabad , Daniel L Oberski This is my paper · ORCID
classification cs.CLcs.CY
keywords challengespersonalityresearchcomputingtext-basedaddressingattentionchallenge
verification ladder T0 review T1 audit T2 compute T3 formal

Signed reviews

No signed human review yet.

0 comments
read the original abstract

Text-based personality computing (TPC) has gained many research interests in NLP. In this paper, we describe 15 challenges that we consider deserving the attention of the research community. These challenges are organized by the following topics: personality taxonomies, measurement quality, datasets, performance evaluation, modelling choices, as well as ethics and fairness. When addressing each challenge, not only do we combine perspectives from both NLP and social sciences, but also offer concrete suggestions. We hope to inspire more valid and reliable TPC research.

Discussion (0). Continue with ORCID to comment.

Pith tools