Difference between revisions of "Real Time Twitter Filtering Framework"

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(Introduction)
(Architecture and Approach)
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=Architecture and Approach=
 
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==Tweet Topic Classification==
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==Clustering of Tweets==
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==Top K Ranking of Tweets for Clusters==
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=Evaluation=
 
=Evaluation=
 
=Tasks=
 
=Tasks=

Revision as of 04:07, 22 December 2014

Introduction

Twitter, a popular microblogging platform, generates approximately 500 Million tweets everyday. These tweets are filtered by diverse domains to analyze and gain insights into the opinion of online users on corresponding topics. For instance, brands monitor tweets to track their products' success and issues, journalists follow twitter to gain insights on real-time news and developments on certain issues.

Architecture and Approach

Tweet Topic Classification

Clustering of Tweets

Top K Ranking of Tweets for Clusters

Evaluation

Tasks

References

  1. Empirical Study of Topic Modeling on Twitter
  2. Searching for Quality Microblog Posts: Filtering and Ranking Based on Content Analysis and Implicit Links
  3. Semantics + filtering + search = twitcident. exploring information in social web streams
  4. Small worlds with a difference: New gatekeepers and the filtering of political information on twitter

People

  • Pavan Kapanipathi
  • Alan Smith
  • Adarsh Alex