Introduction to the Minitrack on Firm-Generated, User-Generated and Machine Generated Content in the Digital Economy: Analytics, Prediction, Recommendation, and Impact

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dc.contributor.authorKlaas, Michael
dc.contributor.authorBeurer-Zuellig, Bettina
dc.date.accessioned2022-12-27T19:10:49Z
dc.date.available2022-12-27T19:10:49Z
dc.date.issued2023-01-03
dc.format.extent2
dc.identifier.doi10.24251/HICSS.2023.480
dc.identifier.isbn978-0-9981331-6-4
dc.identifier.other05875c0b-b2f9-4d97-816f-e8783e5a9b91
dc.identifier.urihttps://hdl.handle.net/10125/103111
dc.language.isoeng
dc.relation.ispartofProceedings of the 56th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectFirm-Generated, User-Generated and Machine Generated Content in the Digital Economy: Analytics, Prediction, Recommendation, and Impact
dc.titleIntroduction to the Minitrack on Firm-Generated, User-Generated and Machine Generated Content in the Digital Economy: Analytics, Prediction, Recommendation, and Impact
dc.type.dcmitext
prism.startingpage3931

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Firm-Generated, User-Generated and Machine Generated Content in the Digital Economy: Analytics, Prediction, Recommendation, and Impact