Classifying perspectives on Twitter: Immediate Observation, Affection, and Speculation

Yihong Zhang*, Claudia Szabo, Quan Z. Sheng, Xiu Susie Fang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

7 Citations (Scopus)


Popular micro-blogging services such as Twitter enable users to effortlessly publish observations and thoughts about ongoing events. Such social sensing generates a very large pool of rich and up-to-date information. However, the large volume and a fast rate of posting make it very challenging to read through the posts and find out useful information in relevant tweets. In this paper, we propose an automated tweet classification approach that distinguishes three perspectives in which a Twitter user may compose messages, namely Immediate Observation, Affection, and Speculation. Using tweets made about the Ukraine Crisis in 2014, our experimental results show that, with the right choice of features and classifiers, we can generally obtain very satisfying results, with the classification precisions in many cases higher than 0.8. We show that the classification results can be used in event time and location detection, public sentiment analysis, and early rumor detection.

Original languageEnglish
Title of host publicationWeb Information Systems Engineering – WISE 2015
Subtitle of host publication16th International Conference, Proceedings
EditorsJianyong Wang, Wojciech Cellary, Dingding Wang, Hua Wang, Shu-Ching Chen, Tao Li, Yanchun Zhang
Place of PublicationCham
PublisherSpringer, Springer Nature
Number of pages15
ISBN (Electronic)9783319261904
ISBN (Print)9783319261898
Publication statusPublished - 2015
Externally publishedYes
Event16th International Conference on Web Information Systems Engineering, WISE 2015 - Miami, United States
Duration: 1 Nov 20153 Nov 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other16th International Conference on Web Information Systems Engineering, WISE 2015
Country/TerritoryUnited States


  • Data mining
  • Short message classification
  • Social media
  • Twitter


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