TY - GEN
T1 - Making Time Fly
T2 - 9th AAAI Conference on Human Computation and Crowdsourcing, HCOMP 2021
AU - Abbas, Tahir
AU - Gadiraju, Ujwal
AU - Vassilis-Javed, Khan
AU - Markopoulos, Panos
PY - 2021
Y1 - 2021
N2 - Crowd-Powered Conversational Systems (CPCS) are gaining traction due to their potential utility in a range of application fields where automated conversational interfaces are still inadequate. Currently, long response times negatively impact CPCSs, limiting their potential application as conversational partners. Related research has focused on developing algorithms for swiftly hiring workers and synchronous crowd coordination techniques to ensure high-quality work. Evaluation studies typically concern system reaction times and performance measurements, but have so far not examined the effects of extended wait times on users. The goal of this study, based on time perception models, is to explore how effective different time fillers are at reducing the negative impacts of waiting in CPCSs. To this end, we conducted a rigorous simulation-based between subjects (N = 930) study on the Prolific crowdsourcing platform to assess the influence of different filler types across three levels of delay (8, 16 & 32s) for Information Retrieval (IR) and stress management tasks. Our results show that asking users to perform secondary tasks (e.g., micro tasks or breathing exercises) while waiting for longer periods of time helped divert their attention away from timekeeping, increased their engagement, and resulted in shorter perceived waiting times. For shorter delays, conversational fillers generated more intense immersion and contributed to shorten the perception of time.
AB - Crowd-Powered Conversational Systems (CPCS) are gaining traction due to their potential utility in a range of application fields where automated conversational interfaces are still inadequate. Currently, long response times negatively impact CPCSs, limiting their potential application as conversational partners. Related research has focused on developing algorithms for swiftly hiring workers and synchronous crowd coordination techniques to ensure high-quality work. Evaluation studies typically concern system reaction times and performance measurements, but have so far not examined the effects of extended wait times on users. The goal of this study, based on time perception models, is to explore how effective different time fillers are at reducing the negative impacts of waiting in CPCSs. To this end, we conducted a rigorous simulation-based between subjects (N = 930) study on the Prolific crowdsourcing platform to assess the influence of different filler types across three levels of delay (8, 16 & 32s) for Information Retrieval (IR) and stress management tasks. Our results show that asking users to perform secondary tasks (e.g., micro tasks or breathing exercises) while waiting for longer periods of time helped divert their attention away from timekeeping, increased their engagement, and resulted in shorter perceived waiting times. For shorter delays, conversational fillers generated more intense immersion and contributed to shorten the perception of time.
UR - http://www.scopus.com/inward/record.url?scp=85129787629&partnerID=8YFLogxK
U2 - 10.1609/hcomp.v9i1.18935
DO - 10.1609/hcomp.v9i1.18935
M3 - Conference contribution
AN - SCOPUS:85129787629
SN - 9781577358725
T3 - Proceedings of the AAAI Conference on Human Computation and Crowdsourcing
SP - 2
EP - 14
BT - HCOMP 2021 - Proceedings of the 9th AAAI Conference on Human Computation and Crowdsourcing
A2 - Kamar, Ece
A2 - Luther, Kurt
PB - Association for the Advancement of Artificial Intelligence (AAAI)
Y2 - 14 November 2021 through 18 November 2021
ER -