Reaching a desired set of users via different paths: an online advertising technique on micro-blogging platforms

Social media and micro-blogging platforms have been successful for communication and information exchange enjoying vast number of user participation. Given their millions of users, it is natural that there is a lot of interest for marketing and advertising on these platforms as attested by the introduced advertising platforms on Twitter and Facebook. In this paper, inspired by micro-blogging advertising platforms, we introduce two problems to aid ad and marketing campaigns. The first problem identifies topics (called analogous topics) that have approximately the same audience in a micro-blogging platform as a given query topic. The main idea is that by bidding on an analogous topic instead of the original query topic, we reach approximately the same audience while spending less of our budget. Then, we present algorithms to identify expert users on a given query topic and categorize these experts to finely understand their diversified expertise. This is imperative for word of mouth marketing where individuals have to be targeted precisely. We evaluate our algorithms and solutions for both problems on a large dataset from Twitter attesting to their e ciency and accuracy compared with alternate approaches.