293 0

Full metadata record

DC FieldValueLanguage
dc.contributor.author김상욱-
dc.date.accessioned2019-12-07T11:29:16Z-
dc.date.available2019-12-07T11:29:16Z-
dc.date.issued2018-03-
dc.identifier.citationINFORMATION SCIENCES, v. 432, page. 185-198en_US
dc.identifier.issn0020-0255-
dc.identifier.issn1872-6291-
dc.identifier.urihttps://www.sciencedirect.com/science/article/pii/S0020025517304851?via%3Dihub-
dc.identifier.urihttps://repository.hanyang.ac.kr/handle/20.500.11754/118047-
dc.description.abstractRecently, crowdsourcing systems have been adopted for promoting products in online social networks (OSN), e.g., Twitter. We call it the crowdsourced promotion. When promoting products using crowdsourcing systems, it is critical to qualify the effectiveness of such promotions in OSN. One possible solution is to use conventional attributes for the characteristics of workers such as worker levels, the number of followers, and Klout scores. Unlike existing crowdsourcing tasks that are performed in crowdsourcing systems, crowdsourced promotions are mainly performed in OSN. Therefore, conventional attributes for workers are ineffective for validating the quality of crowdsourced promotions.In this paper, we propose a new method for measuring the effectiveness of crowd-sourced promotions. It is important to determine whether workers can deliver promotional messages to legitimate users in OSN. In other words, because workers usually propagate the promotional messages to their followers, we aim to measure the ratio of legitimate users to the followers of the worker. Toward this goal, we first devise various attributes to identify legitimate users among all followers. Then, using these attributes, we build a classifier to distinguish between legitimate and non-legitimate users. Lastly, we measure the effectiveness of crowdsourced promotions by using the ratio of legitimate users to followers. Our empirical study demonstrates that the proposed method outperforms the existing baseline methods using conventional attributes. (C) 2017 Elsevier Inc. All rights reserved.en_US
dc.description.sponsorshipThis work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (No. 2015R1C1A1A01055442 and No. NRF-2017R1A2B3004581) and by Next-Generation Information Computing Development Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT (NRF-2017M3C4A7069440).en_US
dc.language.isoen_USen_US
dc.publisherELSEVIER SCIENCE INCen_US
dc.titleCrowdsourced promotions in doubt: Analyzing effective crowdsourced promotionsen_US
dc.typeArticleen_US
dc.relation.volume432-
dc.identifier.doi10.1016/j.ins.2017.12.004-
dc.relation.page185-198-
dc.relation.journalINFORMATION SCIENCES-
dc.contributor.googleauthorKim, Hee-Jeong-
dc.contributor.googleauthorLee, Jongwuk-
dc.contributor.googleauthorChae, Dong-Kyu-
dc.contributor.googleauthorKim, Sang-Wook-
dc.relation.code2018002510-
dc.sector.campusS-
dc.sector.daehakCOLLEGE OF ENGINEERING[S]-
dc.sector.departmentDEPARTMENT OF COMPUTER SCIENCE-
dc.identifier.pidwook-
Appears in Collections:
COLLEGE OF ENGINEERING[S](공과대학) > COMPUTER SCIENCE(컴퓨터소프트웨어학부) > Articles
Files in This Item:
There are no files associated with this item.
Export
RIS (EndNote)
XLS (Excel)
XML


qrcode

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

BROWSE