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Crowdsourced promotions in doubt: Analyzing effective crowdsourced promotions

Title
Crowdsourced promotions in doubt: Analyzing effective crowdsourced promotions
Author
김상욱
Issue Date
2018-03
Publisher
ELSEVIER SCIENCE INC
Citation
INFORMATION SCIENCES, v. 432, page. 185-198
Abstract
Recently, 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.
URI
https://www.sciencedirect.com/science/article/pii/S0020025517304851?via%3Dihubhttps://repository.hanyang.ac.kr/handle/20.500.11754/118047
ISSN
0020-0255; 1872-6291
DOI
10.1016/j.ins.2017.12.004
Appears in Collections:
COLLEGE OF ENGINEERING[S](공과대학) > COMPUTER SCIENCE(컴퓨터소프트웨어학부) > Articles
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