@inproceedings{15d2ea28cbad420388aa4d762b8d3fe2,
title = "Mobile sentiment analysis",
abstract = "Mobile devices play a significant part in a user{\textquoteright}s communication methods and much data that they read and write is received and sent via mobile phones, for instance SMS messages, e-mails, Twitter tweets and social media networking feeds. One of the main goals is to make people aware of how much negative and positive content they read and write via their mobile phones. Existing sentiment analysis applications perform sentiment analysis on downloaded data from mobile phones or use an application installed on another computer to perform the analysis. The sentiment analysis described in this paper is to be performed locally on the mobile phone enabling immediate and private analysis of personal messages and social media contents, allowing the users to be able to reason about their mood and stress level that may be affected by what they had been receiving. Experimental results showed the effectiveness of the proposed system on Android smartphones with varying computational capabilities.",
author = "L. Chambers and E. Tromp and M. Pechenizkiy and M.M. Gaber",
year = "2012",
doi = "10.3233/978-1-61499-105-2-470",
language = "English",
isbn = "978-1-61499-104-5",
series = "Frontiers in Artificial Intelligence and Applications",
publisher = "IOS Press",
pages = "470--479",
editor = "M. Gra{\~n}a and Carlos Toro and J. Posada and R.J. Howlett and L.C. Jain",
booktitle = "Advances in Knowledge-Based and Intelligent Information and Engineering Systems (16th Annual KES Conference, San Sebastian, Spain, September 10-12, 2012)",
address = "Netherlands",
note = "conference; 16th Annual KES Conference; 2012-09-10; 2012-09-12 ; Conference date: 10-09-2012 Through 12-09-2012",
}