Analyzing crowdsourced promotion effects in online social networks
- Authors
- Kim, Hee-Jeong; Chae, Dong-Kyu; Kim, Sang-Wook; Lee, 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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