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Analyzing crowdsourced promotion effects in online social networks

Authors
Kim, Hee-JeongChae, Dong-KyuKim, Sang-WookLee, Jongwuk
Issue Date
Apr-2016
Publisher
Association for Computing Machinery
Keywords
Crowdsourced promotion; Crowdsourcing; Fiverr; Promotion effects; Twitter
Citation
Proceedings of the ACM Symposium on Applied Computing, v.04-08-April-2016, pp.820 - 823
Indexed
SCOPUS
Journal Title
Proceedings of the ACM Symposium on Applied Computing
Volume
04-08-April-2016
Start Page
820
End Page
823
URI
https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/154833
DOI
10.1145/2851613.2852005
Abstract
In recent years, crowdsourcing has been actively used for many people to promote their products in online social networks (OSN), e.g., Twitter. The promotion activity in Twitter is typically performed by retweeting tweets by some accounts, called workers who earn monetary profits by deliberately promoting products for a requester. In this process, a fundamental question is whether the promotions by workers are really effective or not. To answer this question, in this paper, we analyze topological characteristics for the networks of workers, and evaluate the effect of promotions. Our empirical study demonstrates that the network of workers tends to be connected as a small-world network and their promotions show low impacts in the network of workers.
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