Analyzing Twitter Data with Preferences

Lena Rudenko, Christian Haas, Markus Endres

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Today Twitter is one of the most important sources for information distribution. But finding useful and interesting tweets on a specific topic is a non-trivial task, because there are thousands of new posts every minute. In this paper, we describe our preference-based search approach on Twitter messages, which allows users to get the best possible results. For this, we introduce a new CONTAINS preference constructor to search on full-text data, use NLP techniques to handle natural language mistakes, and present experiments.

Original languageEnglish (US)
Title of host publicationNew Trends in Databases and Information Systems, ADBIS 2020 Short Papers, Proceedings
EditorsJérôme Darmont, Boris Novikov, Robert Wrembel
Number of pages12
ISBN (Print)9783030546229
StatePublished - 2020
Externally publishedYes
Event24th European Conference on Advances in Databases and Information Systems, ADBIS 2020 - Lyon, France
Duration: Aug 25 2020Aug 27 2020

Publication series

NameCommunications in Computer and Information Science
Volume1259 CCIS
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937


Conference24th European Conference on Advances in Databases and Information Systems, ADBIS 2020


  • NLP
  • Preferences
  • Twitter

ASJC Scopus subject areas

  • Computer Science(all)
  • Mathematics(all)


Dive into the research topics of 'Analyzing Twitter Data with Preferences'. Together they form a unique fingerprint.

Cite this