Research: A Study of “Churn” in Tweets and Real-Time Search Queries (Extended Version)
Applicability: “A Study of “Churn” in Tweets and Real-Time Search Queries (Extended Version)” offers unique insight into the temporal dynamics of term distribution which may hold implications the design of search systems. As the growing importance of real-time search brings with it several information retrieval challenges; this paper frames one such challenge, that of rapid changes to term distributions, particularly for queries.
Abstract: The real-time nature of Twitter means that term distributions in tweets and in search queries change rapidly: the most frequent terms in one hour may look very different from those in the next. Informally, we call this phenomenon “churn”. Our interest in analyzing churn stems from the perspective of real-time search. Nearly all ranking functions, machine-learned or otherwise, depend on term statistics such as term frequency, document frequency, as well as query frequencies. In the real-time context, how do we compute these statistics, considering that the underlying distributions change rapidly? In this paper, we present an analysis of tweet and query churn on Twitter, as a first step to answering this question. Analyses reveal interesting insights on the temporal dynamics of term distributions on Twitter and hold implications for the design of search systems.
Analysis: Summarized analysis from this paper includes observations on:
Authors: Prepared by Jimmy Lin and Gilad Misne of Twitter, Inc., “A Study of “Churn” in Tweets and Real-Time Search Queries (Extended Version)” is a prepared paper submitted and accepted by the 6th International AAAI Conference on Weblogs and Social Media (ICWSM 2012).
This entry was posted on Tuesday, June 5th, 2012 at 2:39 pm. It is filed under chronology, discover and tagged with research, social media. You can follow any responses to this entry through the RSS 2.0 feed.
Comments are closed.
Taken from a combination of public market sizing estimations as shared in leading electronic discovery reports, publications and posts over time, the following eDiscovery Market Size Mashup shares general worldwide market sizing considerations for software and services in the electronic discovery market for the years between 2015 and 2020.
When Maura Grossman speaks, people listen. In 2011, she was already known as a leading e-discovery attorney and litigator. But her influence exploded when she released research with co-author Gordon Cormack, a computer science professor at the University of Waterloo in Ontario, that concluded software using predictive-coding technology can do as good a job of sifting through documents as human reviewers.
ComplexDiscovery | Creative Commons Attribution 4.0 International