HICSS '00 Proceedings of the 33rd Hawaii International Conference on System Sciences-Volume 6 - Volume 6
Robust methodologies for modeling web click distributions
Proceedings of the 16th international conference on World Wide Web
I tube, you tube, everybody tubes: analyzing the world's largest user generated content video system
Proceedings of the 7th ACM SIGCOMM conference on Internet measurement
Power-Law Distributions in Empirical Data
SIAM Review
Everyone's an influencer: quantifying influence on twitter
Proceedings of the fourth ACM international conference on Web search and data mining
The role of social networks in information diffusion
Proceedings of the 21st international conference on World Wide Web
Social influence in social advertising: evidence from field experiments
Proceedings of the 13th ACM Conference on Electronic Commerce
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Despite the growing interest in using online social networking services (OSNS) for advertising, little is understood about what contributes to the social advertising performance. In this research, we pose following questions: How many clicks do social advertisements actually receive? What are the characteristics of the advertisements that receive many clicks? What factors contribute to the clicks on advertisements? In order to answer these questions, we collect data from AdbyMe, a social media advertisement platform that connects businesses, or advertisers, with users of online social network services. Businesses can reach a large target audience through AdbyMe users who publish the advertisements on their social networks. We analyze the factors that may affect the clicks on advertisements being published on OSNS. In particular, we look into the advertised contents as well as the characteristics of users who publish the advertisements. We find that the traditional advertisement content analysis alone cannot fully explain the effectiveness of social advertisements. More importantly, we discover that in a social advertising paradigm, social influence of a publisher has a strong impact on the number of clicks on the advertisements. Our findings suggest that considering both the advertised contents and the influence of advertising publishers allows better understanding of the social advertisement phenomenon.