基于用户评论情感分析的YouTube视频检索

2017 IEEE International Conference on Signal and Image Processing Applications (ICSIPA) Pub Date : 2017-09-01 DOI:10.1109/ICSIPA.2017.8120658

Hanif Bhuiyan, Jinat Ara, Rajon Bardhan, Md. Rashedul Islam

{"title":"基于用户评论情感分析的YouTube视频检索","authors":"Hanif Bhuiyan, Jinat Ara, Rajon Bardhan, Md. Rashedul Islam","doi":"10.1109/ICSIPA.2017.8120658","DOIUrl":null,"url":null,"abstract":"YouTube is one of the comprehensive video information source on the web where video is uploading continuously in real time. It is one of the most popular site in social media, where users interact with sharing, commenting and rating (like/views) videos. Generally the quality, relevancy and popularity of the video is maintained based on this rating. Sometimes irrelevant and low quality videos ranked higher in the search result due to the number of views or likes, which seems untenable. To minimize this issue, we present a Natural Language processing (NLP) based sentiment analysis approach on user comments. This analysis helps to find out the most relevant and popular video of YouTube according to the search. The effectiveness of the proposed scheme has been proved by a data driven experiment in terms of accuracy of finding relevant, popular and high quality video.","PeriodicalId":268112,"journal":{"name":"2017 IEEE International Conference on Signal and Image Processing Applications (ICSIPA)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"52","resultStr":"{\"title\":\"Retrieving YouTube video by sentiment analysis on user comment\",\"authors\":\"Hanif Bhuiyan, Jinat Ara, Rajon Bardhan, Md. Rashedul Islam\",\"doi\":\"10.1109/ICSIPA.2017.8120658\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"YouTube is one of the comprehensive video information source on the web where video is uploading continuously in real time. It is one of the most popular site in social media, where users interact with sharing, commenting and rating (like/views) videos. Generally the quality, relevancy and popularity of the video is maintained based on this rating. Sometimes irrelevant and low quality videos ranked higher in the search result due to the number of views or likes, which seems untenable. To minimize this issue, we present a Natural Language processing (NLP) based sentiment analysis approach on user comments. This analysis helps to find out the most relevant and popular video of YouTube according to the search. The effectiveness of the proposed scheme has been proved by a data driven experiment in terms of accuracy of finding relevant, popular and high quality video.\",\"PeriodicalId\":268112,\"journal\":{\"name\":\"2017 IEEE International Conference on Signal and Image Processing Applications (ICSIPA)\",\"volume\":\"71 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"52\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE International Conference on Signal and Image Processing Applications (ICSIPA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSIPA.2017.8120658\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE International Conference on Signal and Image Processing Applications (ICSIPA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSIPA.2017.8120658","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 52

摘要

YouTube是网络上综合性的视频信息源之一，视频实时上传不断。它是社交媒体中最受欢迎的网站之一，用户可以在这里分享、评论和评价(喜欢/观看)视频。一般来说，视频的质量、相关性和受欢迎程度是基于这个评级来维持的。有时不相关和低质量的视频在搜索结果中排名靠前是因为观看次数或点赞次数，这似乎是站不住脚的。为了最小化这个问题，我们提出了一种基于自然语言处理(NLP)的用户评论情感分析方法。这种分析有助于根据搜索找出YouTube上最相关和最受欢迎的视频。数据驱动实验证明了该方法在寻找相关视频、热门视频和高质量视频的准确性方面的有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Retrieving YouTube video by sentiment analysis on user comment

YouTube is one of the comprehensive video information source on the web where video is uploading continuously in real time. It is one of the most popular site in social media, where users interact with sharing, commenting and rating (like/views) videos. Generally the quality, relevancy and popularity of the video is maintained based on this rating. Sometimes irrelevant and low quality videos ranked higher in the search result due to the number of views or likes, which seems untenable. To minimize this issue, we present a Natural Language processing (NLP) based sentiment analysis approach on user comments. This analysis helps to find out the most relevant and popular video of YouTube according to the search. The effectiveness of the proposed scheme has been proved by a data driven experiment in terms of accuracy of finding relevant, popular and high quality video.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

2017 IEEE International Conference on Signal and Image Processing Applications (ICSIPA)

自引率

0.00%

发文量