@inproceedings{358476351846402295be870b2b2890b9,
title = "Classifying perspectives on Twitter: Immediate Observation, Affection, and Speculation",
abstract = "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.",
keywords = "Data mining, Short message classification, Social media, Twitter",
author = "Yihong Zhang and Claudia Szabo and Sheng, {Quan Z.} and Fang, {Xiu Susie}",
year = "2015",
doi = "10.1007/978-3-319-26190-4_33",
language = "English",
isbn = "9783319261898",
volume = "9418",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer, Springer Nature",
pages = "493--507",
editor = "Jianyong Wang and Wojciech Cellary and Dingding Wang and Hua Wang and Shu-Ching Chen and Tao Li and Yanchun Zhang",
booktitle = "Web Information Systems Engineering – WISE 2015",
address = "United States",
note = "16th International Conference on Web Information Systems Engineering, WISE 2015 ; Conference date: 01-11-2015 Through 03-11-2015",
}