@inproceedings{722fd1a3b3124e2f983e2618a47dc2c1,
title = "Mining tweets for education reforms",
abstract = "Microblogging and social networking sites have become a popular means of communication channels among internet users. They provide tools for people to voice their opinions. These sites contain vast amounts of opinionated data, leading to an increased growth in research on sentiment analysis and opinion mining. The study aims at using Twitter, a major and popular platform for microblogging and social communication, to conduct sentiment analysis. Real time data was automatically streamed using the Twitter API to collect the public's sentiments regarding education. A survey was also used to capture the public's opinions. The study will help overcome frustrations during implementation of education policies and reforms by taking into account the public's views and opinions.",
keywords = "Education Reforms, Machine Learning, Sentiment Analysis, Social media",
author = "Omar, {Mwana Said} and Alexander Njeru and Samiullah Paracha and Muhammad Wannous and Sun Yi",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 IEEE International Conference on Applied System Innovation, ICASI 2017 ; Conference date: 13-05-2017 Through 17-05-2017",
year = "2017",
month = jul,
day = "21",
doi = "10.1109/ICASI.2017.7988441",
language = "English",
series = "Proceedings of the 2017 IEEE International Conference on Applied System Innovation: Applied System Innovation for Modern Technology, ICASI 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "416--419",
editor = "Teen-Hang Meen and Lam, {Artde Donald Kin-Tak} and Prior, {Stephen D.}",
booktitle = "Proceedings of the 2017 IEEE International Conference on Applied System Innovation",
}