Trend sensing via Twitter

Yavuz Selim Yilmaz, Muhammed Fatih Bulut, Cuneyt Gurcan Akcora, Murat Ali Bayir, Murat Demirbas

Research output: Contribution to journalArticle

8 Citations (Scopus)


Due to its ever increasing popularity, Twitter has become a pervasive information outlet. In this paper, we present a passive sensing framework for identifying trends via Twitter. In our framework, we use a multi-dimensional corpus for finegranularity sensing of trends, and employ both vector-space and set-space methods for achieving accuracy.We present two applications of our framework. The first one is sensing trends in public opinion by using an emotion-category corpus. The second application is sensing trends in location-types in a city by using a location-category corpus. Our experiments show that the proposed methods are able to determine changes in trends effectively in both application scenarios.

Original languageEnglish
Pages (from-to)16-26
Number of pages11
JournalInternational Journal of Ad Hoc and Ubiquitous Computing
Issue number1
Publication statusPublished - 18 Sep 2013



  • City-wide sensing
  • Opinion mining
  • Trend sensing
  • Twitter

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Networks and Communications

Cite this

Yilmaz, Y. S., Bulut, M. F., Akcora, C. G., Bayir, M. A., & Demirbas, M. (2013). Trend sensing via Twitter. International Journal of Ad Hoc and Ubiquitous Computing, 14(1), 16-26.