Pregled bibliografske jedinice broj: 959433
Reddit: A Gold Mine for Personality Prediction
Reddit: A Gold Mine for Personality Prediction // Proceedings of the Second Workshop on Computational Modeling of People’s Opinions, Personality, and Emotions in Social Media
New Orleans (LA): Association for Computational Linguistics (ACL), 2018. str. 87-97 doi:10.18653/v1/w18-1112 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 959433 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Reddit: A Gold Mine for Personality Prediction
Autori
Gjurković, Matej ; Šnajder, Jan
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Proceedings of the Second Workshop on Computational Modeling of People’s Opinions, Personality, and Emotions in Social Media
/ - New Orleans (LA) : Association for Computational Linguistics (ACL), 2018, 87-97
Skup
2nd Workshop on Computational Modeling of People’s Opinions, Personality, and Emotions in Social Media
Mjesto i datum
New Orleans (LA), Sjedinjene Američke Države, 06.06.2018
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
personality prediction ; data mining ; computation social science ; personality ; machine learning
Sažetak
Automated personality prediction from social media is gaining increasing attention in natural language processing and social sciences communities. However, due to high labeling costs and privacy issues, the few publicly available datasets are of limited size and low topic diversity. We address this problem by introducing a large-scale dataset derived from Reddit, a source so far overlooked for personality prediction. The dataset is labeled with Myers-Briggs Type Indicators (MBTI) and comes with a rich set of features for more than 9k users. We carry out a preliminary feature analysis, revealing marked differences between the MBTI dimensions and poles. Furthermore, we use the dataset to train and evaluate benchmark personality prediction models, achieving macro F1-scores between 67% and 82% on the individual dimensions and 82% accuracy for exact or one- off accurate type prediction. These results are encouraging and comparable with the reliability of standardized tests.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo
POVEZANOST RADA
Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb