Pregled bibliografske jedinice broj: 1270669
You Are What You Talk About: Inducing Evaluative Topics for Personality Analysis
You Are What You Talk About: Inducing Evaluative Topics for Personality Analysis // Findings of the Association for Computational Linguistics: EMNLP 2022
Abu Dhabi, Ujedinjeni Arapski Emirati, 2022. str. 3986-3999 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 1270669 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
You Are What You Talk About: Inducing Evaluative
Topics for Personality Analysis
Autori
Jukić, Josip ; Vukojević, Iva ; Šnajder, Jan
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Findings of the Association for Computational Linguistics: EMNLP 2022
/ - , 2022, 3986-3999
Skup
The 2022 Conference on Empirical Methods in Natural Language Processing
Mjesto i datum
Abu Dhabi, Ujedinjeni Arapski Emirati, 07.12.2022. - 11.12.2022
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
evaluative topics ; personality ; Reddit ; topic modelling ; canonical correlation
Sažetak
Expressing attitude or stance toward entities and concepts is an integral part of human behavior and personality. Recently, evaluative language data has become more accessible with social media’s rapid growth, enabling large-scale opinion analysis. However, surprisingly little research examines the relationship between personality and evaluative language. To bridge this gap, we introduce the notion of evaluative topics, obtained by applying topic models to pre-filtered evaluative text from social media. We then link evaluative topics to individual text authors to build their evaluative profiles. We apply evaluative profiling to Reddit comments labeled with personality scores and conduct an exploratory study on the relationship between evaluative topics and Big Five personality facets, aiming for a more interpretable, facet-level analysis. Finally, we validate our approach by observing correlations consistent with prior research in personality psychology
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo, Psihologija
POVEZANOST RADA
Projekti:
HRZZ-IP-2020-02-8671 - Računalni modeli za predviđanje i analizu ličnosti na temelju teksta (psy.txt) (Šnajder, Jan, HRZZ - 2020-02) ( CroRIS)
Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb,
Filozofski fakultet, Zagreb