Wed. Apr 24th, 2024
ARCHIVED CONTENT
You are viewing ARCHIVED CONTENT released online between 1 April 2010 and 24 August 2018 or content that has been selectively archived and is no longer active. Content in this archive is NOT UPDATED, and links may not function.
 

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.

A Study of “Churn” in Tweets and Real-Time Search Queries (Extended Version)

Analysis:  Summarized analysis from this paper includes observations on:

  • Churn
  • Unobserved Terms
  • Update Frequency
  • Churn Patters
  • Predictability

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).

 

Have a Request?

If you have information or offering requests that you would like to ask us about, please let us know, and we will make our response to you a priority.

ComplexDiscovery OÜ is a highly recognized digital publication focused on providing detailed insights into the fields of cybersecurity, information governance, and eDiscovery. Based in Estonia, a hub for digital innovation, ComplexDiscovery OÜ upholds rigorous standards in journalistic integrity, delivering nuanced analyses of global trends, technology advancements, and the eDiscovery sector. The publication expertly connects intricate legal technology issues with the broader narrative of international business and current events, offering its readership invaluable insights for informed decision-making.

For the latest in law, technology, and business, visit ComplexDiscovery.com.

 

Generative Artificial Intelligence and Large Language Model Use

ComplexDiscovery OÜ recognizes the value of GAI and LLM tools in streamlining content creation processes and enhancing the overall quality of its research, writing, and editing efforts. To this end, ComplexDiscovery OÜ regularly employs GAI tools, including ChatGPT, Claude, Midjourney, and DALL-E, to assist, augment, and accelerate the development and publication of both new and revised content in posts and pages published (initiated in late 2022).

ComplexDiscovery also provides a ChatGPT-powered AI article assistant for its users. This feature leverages LLM capabilities to generate relevant and valuable insights related to specific page and post content published on ComplexDiscovery.com. By offering this AI-driven service, ComplexDiscovery OÜ aims to create a more interactive and engaging experience for its users, while highlighting the importance of responsible and ethical use of GAI and LLM technologies.