Avishay Livne

Learn More
In this work, we study the use of Twitter by House, Senate and gubernatorial candidates during the midterm (2010) elections in the U.S. Our data includes almost 700 candidates and over 690k documents that they produced and cited in the 3.5 years leading to the elections. We utilize graph and text mining techniques to analyze differences between Democrats,(More)
As the volume of scientific literature grows faster it becomes more difficult for researchers to identify promising papers that are likely to become influential in their field. We study the problem of predicting future citation counts of papers given information available at the time of publication (five years forward in our pilot study). We apply machine(More)
As individuals communicate, their exchanges form a dynamic network. We demonstrate, using time series analysis of communication in three online settings, that network structure alone can be highly revealing of the diversity and novelty of the information being communicated. Our approach uses both standard and novel network metrics to characterize how(More)
A person often uses a single search engine for very different tasks. For example, an author editing a manuscript may use the same academic search engine to find the latest work on a particular topic or to find the correct citation for a familiar article. The author's tolerance for latency and accuracy may vary according to task. However, search engines(More)
Monitoring distributed streams of data is a basic construct in many distributed systems. Examples include a wireless sensor network, where we would like to receive an alert every time the average of the temperature readings taken by the sensors exceeds a given threshold, or a distributed search engine, where we would like to determine the set of queries(More)
  • 1