Raimond: Quantitative Data Extraction from Twitter to Describe Events

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9114)

Abstract

Social media play a decisive role in communicating and spreading information during global events. In particular, real-time microblogging platforms such as Twitter have become prevalent. Researchers have used microblogging for a number of tasks, including past events analysis, predictions, and information retrieval. Nevertheless, little attention has been given to quantitative data extraction. In this paper, we address two questions: can we develop a mechanism to extract quantitative data from a collection of tweets, and can we use the salient findings to describe an event? To answer the first question, we introduce Raimond, a virtual text curator, specialized in quantitative data extraction from Twitter. To address the second question, we use our system on three events and evaluate its output using a crowdsourcing strategy. We demonstrate the effectiveness of our approach with a number of real world examples.

Keywords

Microblogs Information extraction Events analysis 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.CWIAmsterdamThe Netherlands
  2. 2.Microsoft CorporationMountain ViewUSA

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