@inproceedings{e9ca878430434c529103ab324e8bb3b7,
title = "A public opinion keyword vector for social sentiment analysis research",
abstract = "In the Internet era, online platforms are the most convenient means for people to share and retrieve knowledge. Social media enables users to easily post their opinions and perspectives regarding certain issues. Although this convenience lets the internet become a treasury of information, the overload also prevents user from understanding the entirety of various events. This research aims at using text mining techniques to explore public opinion contained in social media by analyzing the reader's emotion towards pieces of short text. We propose Public Opinion Keyword Embedding (POKE) for the presentation of short texts from social media, and a vector space classifier for the categorization of opinions. The experimental results demonstrate that our method can effectively represent the semantics of short text public opinion. In addition, we combine a visualized analysis method for keywords that can provide a deeper understanding of opinions expressed on social media topics.",
keywords = "Reader emotion, Sentiment analysis, Social media",
author = "Chang, {Yung Chun} and Lee, {Fang Yi} and Chen, {Chun Hung}",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 10th International Conference on Advanced Computational Intelligence, ICACI 2018 ; Conference date: 29-03-2018 Through 31-03-2018",
year = "2018",
month = jun,
day = "8",
doi = "10.1109/ICACI.2018.8377555",
language = "English",
series = "Proceedings - 2018 10th International Conference on Advanced Computational Intelligence, ICACI 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "752--757",
booktitle = "Proceedings - 2018 10th International Conference on Advanced Computational Intelligence, ICACI 2018",
address = "United States",
}