Sentiment Analysis and View Count Forcasting Using Youtube

Kwok, Shuk Kwan

Please use this identifier to cite or link to this item: http://dspace.cityu.edu.hk/handle/2031/8254

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DC Field	Value	Language
dc.contributor.author	Kwok, Shuk Kwan	en_US
dc.date.accessioned	2016-01-07T01:24:12Z
dc.date.accessioned	2017-09-19T09:15:22Z
dc.date.accessioned	2019-02-12T07:34:04Z	-
dc.date.available	2016-01-07T01:24:12Z
dc.date.available	2017-09-19T09:15:22Z
dc.date.available	2019-02-12T07:34:04Z	-
dc.date.issued	2015	en_US
dc.identifier.other	2015eeksk929	en_US
dc.identifier.uri	http://144.214.8.231/handle/2031/8254	-
dc.description.abstract	Youtube has become one of the most successful video sharing website which allows the users to view, share and comment on the video posted. In this paper, we are interested in how the emotion expressed in the viewers’ comment would affect the view count of the video. The comment of the selected music video are collected using the Youtube Data api and are preprocessed by removing useless features. The processed comment are then classified into six categories: anger, disgust, fear, joy, sadness and surprise during the sentiment analysis. Generally, we can find certain correlation between the emotion expressed in the comment as well as the view count of the video.	en_US
dc.rights	This work is protected by copyright. Reproduction or distribution of the work in any format is prohibited without written permission of the copyright owner.	en_US
dc.rights	Access is restricted to CityU users.	en_US
dc.title	Sentiment Analysis and View Count Forcasting Using Youtube	en_US
dc.contributor.department	Department of Electronic Engineering	en_US
dc.description.supervisor	Supervisor: Mr. TING, Van C W; Assessor: Dr. LAI, Man PO	en_US
Appears in Collections:	Electrical Engineering - Undergraduate Final Year Projects

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