Crowdsourced promotions in doubt: Analyzing effective crowdsourced promotions

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 crowdsourced 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.