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East European Conference on Advances in Databases and Information Systems

ADBIS 2015: New Trends in Databases and Information Systems pp 259-267 | Cite as

Detection of Trends and Opinions in Geo-Tagged Social Text Streams

  • Jevgenij JakunschinEmail author
  • Andreas Heuer
  • Antje Raab-Düsterhöft
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 539)

Abstract

This paper, describes an application of social media, database and data-mining techniques for the analysis of conflicting trends and opinions in a spatial area. This setup was used to demonstrate the distribution of interests during a global event and can be used for several social media datamining tasks, such as trend prediction, sentiment analysis and social-psychological feedback tracing. To this end the application clusters trends in social text media streams, such as Twitter and detects the different opinion differences within a single trend based on the temporal, spatial and semantic-pragmatic dimensions. The data is stored in a multidimensional space to detect correlations and combine similar trends into clusters, as it is expanded over time. The results of this work provide a system, with the focus to trace several clusters of conflicts within the same trend, as opposed to the common approach of tag-based filtering and sorting by occurrence count.

Keywords

Events Trends Clustering Social text media Spatial Temporal Semantic Visualization Social decay 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Jevgenij Jakunschin
    • 1
    Email author
  • Andreas Heuer
    • 2
  • Antje Raab-Düsterhöft
    • 1
  1. 1.Natural Language Processing Laboratory, Department of Electronics and Information TechnologyUniversity of WismarWismarGermany
  2. 2.Department for Databases and Information-SystemsUniversity of RostockRostockGermany

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