Online Adaptive Topic Focused Tweet Acquisition

Twitter provides a public streaming API that is strictly limited, making it difficult to simultaneously achieve good coverage and relevance when monitoring tweets for a specific topic of interest. In this paper, we address the tweet acquisition challenge to enhance monitoring of tweets based on the client/application needs in an online adaptive manner such that the quality and quantity of the results improves over time. We propose a Tweet Acquisition System (TAS), that iteratively selects phrases to track based on an explore- exploit strategy and dynamically adapts the representation of topic of interest. Our experimental studies show that TAS significantly improves recall of relevant tweets and the performance improves when the topics are more specific.