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CommuniMents: A Framework for Detecting Community Based Sentiments for Events

delete2017-04-01
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PRE
AI
M
Muhammad Aslam Jarwar *
R
Rabeeh Ayaz Abbasi
N
Naif Radi Aljohani
A
Ali Daud
J
Jalal S. Alowibdi
J
José-Ramón Cano
S
Salvador García
I
Ilyoung Chong
DOI:10.4018/IJSWIS.2017040106delete
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Abstract

Abstract

En 中文
Social media has revolutionized human communication and styles of interaction. Due to its effectiveness and ease, people have started using it increasingly to share and exchange information, carry out discussions on various events, and express their opinions. Various communities may have diverse sentiments about events and it is an interesting research problem to understand the sentiments of a particular community for a specific event. In this article, the authors propose a framework CommuniMents which enables us to identify the members of a community and measure the sentiments of the community for a particular event. CommuniMents uses automated snowball sampling to identify the members of a community, then fetches their published contents (specifically tweets), pre-processes the contents and measures the sentiments of the community. The authors perform qualitative and quantitative evaluation for a variety of real world events to validate the effectiveness of the proposed framework.
Keywords:
Communities
Events
Sentiment Analysis
Social Media
Twitter
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I
International Journal on Semantic Web and Information Systems
IF:
5.6
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471
Citations:
914

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