Tracking food insecurity from tweets using data mining techniques

Data mining algorithms can be applied to extract useful patterns from social media conversations to monitor disasters such as tsunami, earth quakes and nuclear power accidents. While food insecurity has persistently remained a world concern, its monitoring with this strategy has received limited att...

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Bibliographic Details
Published in:	2018 IEEE ACM Symposium on Software Engineering in Africa (SEiA) pp. 27 - 34
Main Authors:	Lukyamuzi, Andrew, Ngubiri, John, Okori, Washington
Format:	Conference Proceeding
Language:	English
Published:	New York, NY, USA ACM 27.05.2018
Series:	ACM Conferences
Subjects:	Big Data Data mining Food insecurity Information systems Information systems > Information systems applications Information systems > Information systems applications > Data mining Machine Learning Algorithms Monitoring Security Social Networks Text Mining Twitter Web text mining big data food insecurity machine learning algorithms web social networks
ISBN:	1450357199, 9781450357197
Online Access:	Get full text
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