research-article

My ever changing moods: sentiment-based event detection on the cloud

Authors:

Richard O. Sinnott,

Natasha Thomas,

Himanshu Bansal,

Zeyu ZhaoAuthors Info & Claims

UCC '16: Proceedings of the 9th International Conference on Utility and Cloud Computing

Pages 175 - 184

https://doi.org/10.1145/2996890.2996898

Published: 06 December 2016 Publication History

Abstract

Twitter is a globally used micro-blogging platform with hundreds of millions of tweets sent every day. Many researchers have explored Twitter analytics across a wide range of areas such as topic modeling, sentiment analysis, event detection, as well as the application of Twitter for a variety of domain-specific application areas, e.g. disaster management. One area that has not been explored is how changes in sentiment can be used to identify events. In this paper we present a scalable Cloud-based platform for harvesting, processing, analyzing and visualizing large-scale Twitter data. We focus especially on how changes in sentiment can be used to identify events in given contexts. What is novel is that the events that are detected are not dependent explicitly on the topic of any given tweet, but entirely on the change in sentiment. This offers new capabilities for event detection that have hitherto not been explored. To illustrate the approach, we present case studies related to sporting events identified entirely through changing sentiment with specific focus on the 2014 FIFA World Cup of Soccer and the 2015 World Cup of Cricket. (Abstract)

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Cited By

Cunliffe GLiang CSinnott R(2020)Using Social Media to Understand City-wide Movement Patterns and Behaviours2020 Seventh International Conference on Social Networks Analysis, Management and Security (SNAMS)10.1109/SNAMS52053.2020.9336560(1-8)Online publication date: 14-Dec-2020
https://doi.org/10.1109/SNAMS52053.2020.9336560
Karageorgou ILiakos PDelis A(2020)A Sentiment Analysis Service Platform for Streamed Multilingual Tweets2020 IEEE International Conference on Big Data (Big Data)10.1109/BigData50022.2020.9377837(3262-3271)Online publication date: 10-Dec-2020
https://doi.org/10.1109/BigData50022.2020.9377837
Sundararajan KSaravana JPalanisamy A(2020)Textual Feature Ensemble-Based Sarcasm Detection in Twitter DataIntelligence in Big Data Technologies—Beyond the Hype10.1007/978-981-15-5285-4_44(443-450)Online publication date: 26-Jul-2020
https://doi.org/10.1007/978-981-15-5285-4_44
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Published In

cover image ACM Other conferences

UCC '16: Proceedings of the 9th International Conference on Utility and Cloud Computing

December 2016

549 pages

ISBN:9781450346160

DOI:10.1145/2996890

General Chairs:
Changjun Jiang
Tongji University, China
,
Omer Rana
Cardiff University, UK
,
Nick Antonopoulos
University of Derby, UK

Copyright © 2016 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Publication History

Published: 06 December 2016

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UCC '16

UCC '16: 9th International Conference on Utility and Cloud Computing

December 6 - 9, 2016

Shanghai, China

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Overall Acceptance Rate 38 of 125 submissions, 30%

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Cited By

Cunliffe GLiang CSinnott R(2020)Using Social Media to Understand City-wide Movement Patterns and Behaviours2020 Seventh International Conference on Social Networks Analysis, Management and Security (SNAMS)10.1109/SNAMS52053.2020.9336560(1-8)Online publication date: 14-Dec-2020
https://doi.org/10.1109/SNAMS52053.2020.9336560
Karageorgou ILiakos PDelis A(2020)A Sentiment Analysis Service Platform for Streamed Multilingual Tweets2020 IEEE International Conference on Big Data (Big Data)10.1109/BigData50022.2020.9377837(3262-3271)Online publication date: 10-Dec-2020
https://doi.org/10.1109/BigData50022.2020.9377837
Sundararajan KSaravana JPalanisamy A(2020)Textual Feature Ensemble-Based Sarcasm Detection in Twitter DataIntelligence in Big Data Technologies—Beyond the Hype10.1007/978-981-15-5285-4_44(443-450)Online publication date: 26-Jul-2020
https://doi.org/10.1007/978-981-15-5285-4_44
Bharathan KDeepasree Varma P(2019)Polarity Detection Using Digital Media2019 9th International Conference on Advances in Computing and Communication (ICACC)10.1109/ICACC48162.2019.8986172(181-187)Online publication date: Nov-2019
https://doi.org/10.1109/ICACC48162.2019.8986172

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