@inproceedings{48c4326921f04cc18eea3b0e18198579,
title = "Features for mood prediction in social media",
abstract = "Usage of social networks has exploded over the past decade or so. Users now routinely share their thought, opinions, feelings as well as their daily activities on various social networks. An interesting consequence of this explosive usage of social networks is that it is possible to glean the current mood and emotion of a user from his or her social network postings. A question that arises in this context is: Can we use any differentiating features exhibited by people on their online social activities to build appropriate classifiers that can identify the positivity or negativity of users with high accuracy and low false positive and negative rates?",
author = "Mahnaz Roshanaei and Richard Han and Shivakant Mishra",
year = "2015",
doi = "10.1145/2808797.2809342",
language = "English",
series = "Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015",
publisher = "Association for Computing Machinery, Inc",
pages = "1580--1581",
editor = "Jian Pei and Fabrizio Silvestri and Jie Tang",
booktitle = "Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015",
note = "IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015 ; Conference date: 25-08-2015 Through 28-08-2015",
}