@inproceedings{fe8ffa17b0b343f5a9ad2d81c054aa34,
title = "Analyzing on-boarding time in context of crowdsourcing",
abstract = "Crowdsourcing is an emerging area which leverages collective intelligence of the crowd. Although crowdsourcing provides several benefits, it also brings uncertainty in any project ex- ecution. The uncertainty may be because of the time taken in on-boarding workers and lack of confidence in workers. The On-boarding time specifically becomes important when tasks are of short duration as it is not worth spending too much of time in on-boarding a worker for short task. In this paper, we empirically analyze 59,597 tasks data from Up- work, an online marketplace, to understand major factors that impact On-boarding time. We identified that certain factors, such as Feedback, Hiring rate, Total hours spent, Length of requirement etc., affect the On-boarding time. We applied two predictive models to predict the On-boarding time. Our study provides insights for researchers, organizations, etc. who are looking to accomplish their tasks through crowds ourcing and helps them to better understand factors which inuence the On-boarding time.",
keywords = "Crowds ourcing, Data Analytics, Flash Teams",
author = "Kumar Abhinav and Alex Kass and Alpana Dubey and Gurdeep Virdi",
year = "2016",
month = nov,
day = "13",
doi = "10.1145/2989238.2989243",
language = "English",
series = "SWAN 2016 - Proceedings of the 2nd International Workshop on Software Analytics, co-located with FSE 2016",
publisher = "Association for Computing Machinery, Inc",
pages = "29--35",
editor = "Latifa Guerrouj and David Lo and Olga Baysal and Jacek Czerwonka and Brendan Murphy",
booktitle = "SWAN 2016 - Proceedings of the 2nd International Workshop on Software Analytics, co-located with FSE 2016",
note = "2nd International Workshop on Software Analytics, SWAN 2016 ; Conference date: 13-11-2016",
}