{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T19:05:24Z","timestamp":1778267124674,"version":"3.51.4"},"reference-count":7,"publisher":"Association for Computing Machinery (ACM)","issue":"Autumn","license":[{"start":{"date-parts":[[2017,11,27]],"date-time":"2017-11-27T00:00:00Z","timestamp":1511740800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["SIGWEB Newsl."],"published-print":{"date-parts":[[2017,11,27]]},"abstract":"<jats:p>Leveraging the online crowd replacing limited experts has become a successful practice over the last decade for solving diverse real-life problems. Various complex problems are now being solved utilizing the power of crowd, an approach popularly termed as 'crowdsourcing'. Judgment analysis refers to a particular type of crowdsourcing task where we aggregate the opinions collected from the crowd for a purpose. We, being the rational agents, have a common interest towards knowing others' opinions before providing our own. This broadly categorizes the problem of judgment analysis into two types --- with independent and with dependent opinions. However, a new paradigm of crowd based judgment analysis has recently evolved, which can tackle the constrained opinions of crowd workers. In this article, we touch upon this novel problem of constrained crowd judgment analysis and discuss its possible dimensions of research.<\/jats:p>","DOI":"10.1145\/3146484.3146488","type":"journal-article","created":{"date-parts":[[2017,11,28]],"date-time":"2017-11-28T13:21:34Z","timestamp":1511875294000},"page":"1-3","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["\"Constrained crowd judgment analysis\" by Sujoy Chatterjee, Anirban Mukhopadhyay and Malay Bhattacharyya with Martin Vesely as coordinator"],"prefix":"10.1145","volume":"2017","author":[{"given":"Sujoy","family":"Chatterjee","sequence":"first","affiliation":[{"name":"University of Kalyani, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Anirban","family":"Mukhopadhyay","sequence":"additional","affiliation":[{"name":"University of Kalyani, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Malay","family":"Bhattacharyya","sequence":"additional","affiliation":[{"name":"Indian Institute of Engineering Science and Technology, Shibpur, India"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2017,11,27]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"Proceedings of the 33rd IEEE International Conference on Data Engineering (ICDE). IEEE","author":"Chatterjee S.","unstructured":"Chatterjee , S. , Mukhopadhyay , A. , and Bhattacharyya , M . 2017a. Judgment analysis based on crowdsourced opinions . In Proceedings of the 33rd IEEE International Conference on Data Engineering (ICDE). IEEE , San Diego, USA, 1439--1444. Chatterjee, S., Mukhopadhyay, A., and Bhattacharyya, M. 2017a. Judgment analysis based on crowdsourced opinions. In Proceedings of the 33rd IEEE International Conference on Data Engineering (ICDE). IEEE, San Diego, USA, 1439--1444."},{"key":"e_1_2_1_2_1","volume-title":"Proceedings of the AAAI 2017 Spring Symposium on AI for Social Good (AISOC). AAAI Press","author":"Chatterjee S.","unstructured":"Chatterjee , S. , Mukhopadhyay , A. , and Bhattacharyya , M . 2017b. Smart city planning with constrained crowd judgment analysis . In Proceedings of the AAAI 2017 Spring Symposium on AI for Social Good (AISOC). AAAI Press , Palo Alto, USA, 16--22. Chatterjee, S., Mukhopadhyay, A., and Bhattacharyya, M. 2017b. Smart city planning with constrained crowd judgment analysis. In Proceedings of the AAAI 2017 Spring Symposium on AI for Social Good (AISOC). AAAI Press, Palo Alto, USA, 16--22."},{"key":"e_1_2_1_3_1","unstructured":"CrowdMed. https:\/\/www.crowdmed.com.  CrowdMed. https:\/\/www.crowdmed.com."},{"key":"e_1_2_1_4_1","unstructured":"Glatz J. 2010. Canning food from napoleon to now. In Illinois Times.  Glatz J. 2010. Canning food from napoleon to now. In Illinois Times."},{"key":"e_1_2_1_5_1","volume-title":"International Encyclopedia of Communication Online.","author":"Webster J. G.","unstructured":"Webster , J. G. 2008. Nielsen ratings . In International Encyclopedia of Communication Online. Webster, J. G. 2008. Nielsen ratings. In International Encyclopedia of Communication Online."},{"key":"e_1_2_1_6_1","volume-title":"Proceedings of the Neural Information Processing System","author":"Welinder P.","year":"2010","unstructured":"Welinder , P. , Branson , S. , Belongie , S. , and Perona ., P. 2010 . The multidimensional wisdom of crowds . In Proceedings of the Neural Information Processing System . Vancouver, Canada, 2424--2432. Welinder, P., Branson, S., Belongie, S., and Perona., P. 2010. The multidimensional wisdom of crowds. In Proceedings of the Neural Information Processing System. Vancouver, Canada, 2424--2432."},{"key":"e_1_2_1_7_1","volume-title":"Proceedings of the Neural Information Processing System","author":"Whitehill J.","year":"2009","unstructured":"Whitehill , J. , Ruvolo , P. , Wu , T. , Bergsma , J. , and Movellan ., J. 2009 . Whose vote should count more: Optimal integration of labels from labelers of unknown expertise . In Proceedings of the Neural Information Processing System . Vancouver, Canada , 2035--2043. Whitehill, J., Ruvolo, P., Wu, T., Bergsma, J., and Movellan., J. 2009. Whose vote should count more: Optimal integration of labels from labelers of unknown expertise. In Proceedings of the Neural Information Processing System. Vancouver, Canada, 2035--2043."}],"container-title":["ACM SIGWEB Newsletter"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3146484.3146488","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3146484.3146488","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T02:13:33Z","timestamp":1750212813000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3146484.3146488"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,11,27]]},"references-count":7,"journal-issue":{"issue":"Autumn","published-print":{"date-parts":[[2017,11,27]]}},"alternative-id":["10.1145\/3146484.3146488"],"URL":"https:\/\/doi.org\/10.1145\/3146484.3146488","relation":{},"ISSN":["1931-1745","1931-1435"],"issn-type":[{"value":"1931-1745","type":"print"},{"value":"1931-1435","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,11,27]]},"assertion":[{"value":"2017-11-27","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}