Abstract
As computing and communication systems evolve rapidly and ubiquitously, it has become convenient and almost effortless for individual users to generate, share, and exchange information on online social media. Through online social media, a wide range of digital content, which covers blogging, forums, reviews, social networking, question-answer databases, digital video, mobile phone photography, and wikis, is created by users and has dramatically changed the way people work and interact. However, the simplicity of creating such digital content online has also led to an increase of users? concern about the trustworthiness of such information. To address the issue of trustworthiness, a widely recognized approach is to evaluate the quality of the online information based on feedback from large scale, virtual word-of-mouth networks where individuals share their own opinions and experiences. The aggregated result of such feedback is called digital reputation. Digital reputation has already been widely adopted by current online social media. For example, viewers on YouTube may ?like? or ?dislike? a video clip, buyers on Amazon share their purchasing experiences, travelers evaluate hotels or restaurants on Yelp, and readers can either ?dig? or ?bury? a piece of social news on Reddit. The reputation-based solution is playing an increasingly important role in influencing users? online social interactions. For example, eBay sellers with established reputations can expect about 8% more revenue than new sellers marketing the same goods [1]; the survey in [2] reveals that the services receiving five-star ratings will attract 20% more revenue than the same services receiving four-star ratings.
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