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dc.contributor.authorOmuya, Erick Odhiambo
dc.date.accessioned2019-03-25T07:50:06Z
dc.date.available2019-03-25T07:50:06Z
dc.date.issued2017
dc.identifier.urihttp://ir.mksu.ac.ke/handle/123456780/4136
dc.description.abstractThrough Social media, people are able to write short messages on their walls to express their sentiments using various social media like Twitter and Facebook. Through these messages also called status updates, they share and discuss things like news, jokes, business issues and what they go through on a daily basis. Tweets and other updates have become so important in the world of information and communication because they have a great potential of passing information very fast. They enable interaction among vast groups of people including students, businesses and their clients. These numerous amounts of information can be extracted, processed and properly utilized in areas like marketing and electronic learning. This paper reports on the successful development of a way of searching, filtering, organizing and storing the information from social media so that it can be put to some good use in an electronic learning environment. This helps in solving the problem of losing vital information that is generated from the social media. It addresses this limitation by using the data from twitter to cluster students and by so doing support group electronic learningen_US
dc.language.isoen_USen_US
dc.publisherAmerican Journal of Artificial Intelligenceen_US
dc.subjectSocial Mediaen_US
dc.subjectTwitter Application Programming Interfaceen_US
dc.subjectNatural Language Processingen_US
dc.subjectTwitteren_US
dc.subjectCorpusen_US
dc.titleA Model for Clustering Social Media Data for Electronic Learningen_US
dc.typeArticleen_US


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