Please use this identifier to cite or link to this item: http://hdl.handle.net/10125/59670

Detection of Sentiment Provoking Events in Social Media

File Size Format  
0230.pdf 264.58 kB Adobe PDF View/Open

Item Summary

Title:Detection of Sentiment Provoking Events in Social Media
Authors:Daou, Hoda
Keywords:Data Analytics, Data Mining and Machine Learning for Social Media
Digital and Social Media
Classification, Events, Machine Learning, Social Media
Date Issued:08 Jan 2019
Abstract:Social media has become one of the main sources of news and events due to its ability to disseminate and propagate information very fast and to a large population. Social media platforms are widely accessible to the population making it difficult to extract relevant information from the huge amount of posted data. In our study, we propose an algorithm that automatically detects events using strong sentiment classification and appropriate clustering techniques. We focus our study on a specific type of events that triggers strong sentiment among the public. Results show that the suggested methodology is able to identify important events, such as a mass shooting and plane crash, using a generalized and simple approach.
Pages/Duration:9 pages
URI:http://hdl.handle.net/10125/59670
ISBN:978-0-9981331-2-6
DOI:10.24251/HICSS.2019.279
Rights:Attribution-NonCommercial-NoDerivatives 4.0 International
https://creativecommons.org/licenses/by-nc-nd/4.0/
Appears in Collections: Data Analytics, Data Mining and Machine Learning for Social Media


Please email libraryada-l@lists.hawaii.edu if you need this content in ADA-compliant format.

This item is licensed under a Creative Commons License Creative Commons