TY - GEN
T1 - HyEnA
T2 - 1st International Conference on Hybrid Human-Artificial Intelligence, HHAI 2022
AU - Van Der Meer, Michiel
AU - Liscio, Enrico
AU - Jonker, Catholijn M.
AU - Plaat, Aske
AU - Vossen, Piek
AU - Murukannaiah, Pradeep K.
PY - 2022
Y1 - 2022
N2 - The key arguments underlying a large and noisy set of opinions help understand the opinions quickly and accurately. Fully automated methods can extract arguments but (1) require large labeled datasets and (2) work well for known viewpoints, but not for novel points of view. We propose HyEnA, a hybrid (human + AI) method for extracting arguments from opinionated texts, combining the speed of automated processing with the understanding and reasoning capabilities of humans. We evaluate HyEnA on three feedback corpora. We find that, on the one hand, HyEnA achieves higher coverage and precision than a state-of-the-art automated method, when compared on a common set of diverse opinions, justifying the need for human insight. On the other hand, HyEnA requires less human effort and does not compromise quality compared to (fully manual) expert analysis, demonstrating the benefit of combining human and machine intelligence.
AB - The key arguments underlying a large and noisy set of opinions help understand the opinions quickly and accurately. Fully automated methods can extract arguments but (1) require large labeled datasets and (2) work well for known viewpoints, but not for novel points of view. We propose HyEnA, a hybrid (human + AI) method for extracting arguments from opinionated texts, combining the speed of automated processing with the understanding and reasoning capabilities of humans. We evaluate HyEnA on three feedback corpora. We find that, on the one hand, HyEnA achieves higher coverage and precision than a state-of-the-art automated method, when compared on a common set of diverse opinions, justifying the need for human insight. On the other hand, HyEnA requires less human effort and does not compromise quality compared to (fully manual) expert analysis, demonstrating the benefit of combining human and machine intelligence.
KW - argument extraction
KW - hybrid intelligence
KW - natural language processing
UR - http://www.scopus.com/inward/record.url?scp=85142170750&partnerID=8YFLogxK
U2 - 10.3233/FAIA220187
DO - 10.3233/FAIA220187
M3 - Conference contribution
AN - SCOPUS:85142170750
T3 - Frontiers in Artificial Intelligence and Applications
SP - 17
EP - 31
BT - HHAI2022
A2 - Schlobach, Stefan
A2 - Perez-Ortiz, Maria
A2 - Tielman, Myrthe
PB - IOS Press
Y2 - 13 June 2022 through 17 June 2022
ER -