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We propose a computational framework to predict synchronyof action in online social media. Synchrony is a temporalsocial network phenomenon in which a large number of usersare observed to mimic a certain action over a period of timewith sustained participation from early users.Understanding social synchrony can be helpful in identifyingsuitable time periods(More)
In this paper we develop a recommendation framework to connect image content with communities in online social media. The problem is important because users are looking for useful feedback on their uploaded content, but finding the right community for feedback is challenging for the end user. Social media are characterized by both content and community.(More)
In this paper, we develop a simple model to study and analyze communication dynamics in the blogosphere and use these dynamics to determine interesting correlations with stock market movement. This work can drive targeted advertising on the web as well as facilitate understanding community evolution in the blogosphere. We describe the communication dynamics(More)
This article investigates the impact of user homophily on the social process of information diffusion in online social media. Over several decades, social scientists have been interested in the idea that similarity breeds connection—precisely known as “homophily”. “Homophily”, has been extensively studied in the social sciences and refers to the idea that(More)
During broadcast events such as the Superbowl, the U.S. Presidential and Primary debates, etc., Twitter has become the de facto platform for crowds to share perspectives and commentaries about them. Given an event and an associated large-scale collection of tweets, there are two fundamental research problems that have been receiving increasing attention in(More)
Rich media social networks promote not only creation and consumption of media, but also communication about the posted media item. What causes a conversation to be interesting, that prompts a user to participate in the discussion on a posted video? We conjecture that people participate in conversations when they find the conversation theme interesting, see(More)
Social media channels such as Twitter have emerged as platforms for crowds to respond to public and televised events such as speeches and debates. However, the very large volume of responses presents challenges for attempts to extract sense from them. In this work, we present an analytical method based on joint statistical modeling of topical influences(More)
This paper describes preliminary findings related to a system for "live" collaborative tagging of enterprise meetings taking place on an audio bridge between distributed participants. Participants can apply tags to different points of the interaction as it is ongoing and can see, in near real-time, the "flow" of tags as they are being contributed. Two novel(More)