Cross-country persistent tags discovery from YouTube trending video big dataset

Year 2023, Volume: 12 Issue: 4, 1538 - 1544, 15.10.2023

Yeşim Dokuz

https://doi.org/10.28948/ngumuh.1330386

Abstract

YouTube is the primary video content platform among video sharing social media platforms with its easy-to-use interface and huge number of users. Due to the big data nature of YouTube video datasets, analyzing and extracting knowledge from these datasets would provide insights into researchers and government directors on social orientation and tendency YouTube users. However, analyzing YouTube big datasets is challenging due to the difficulty of image and speech processing applications, the hardness of utilizing semantic analysis methods on irregular YouTube contents, and big data nature of YouTube video datasets. Literature studies focus on video recommendation systems, semantic analysis on YouTube comments and trending video analysis. In this study, a new method and an algorithm are proposed to discover cross-country persistent tags over YouTube trending video big dataset for three countries (United States of America, Canada, and Great Britain). The discovered cross-country persistent tags show that some YouTube video tags are globally utilized on videos, while some certain tags are utilized for only one country.

Keywords

YouTube trend video analysis, cross-country persistent tags discovery, video tag analysis, YouTube big data analytics

Project Number

MMT2023/1-BAGEP

YouTube trend büyük veri kümelerinden ülkeler arası kalıcı etiketlerin keşfi

Abstract

YouTube kolay kullanılan arayüzü ve büyük miktarda kullanıcı sayısı ile video paylaşım sosyal medya platformları arasından birinci video paylaşım platformudur. YouTube video veri kümelerinin büyük veri doğasından dolayı bu veri kümelerinin analizi ve bilgi çıkarımı, araştırmacılar ve kurum yöneticilerine YouTube kullanıcılarının sosyal eğilimleri hakkında fikir vermektedir. Ancak, YouTube büyük verilerinin analizi, görüntü ve ses işleme uygulamalarının zorluğu, semantik analiz metotlarını düzensiz YouTube içeriklerine uygulamanın zorluğu ve YouTube video veri kümelerinin büyük veri özelliği nedeniyle zordur. Literatürdeki çalışmalar video tavsiye sistemleri, YouTube yorumlarından semantik analizler ve trend video analizleri üzerine odaklanmaktadır. Bu çalışmada, üç ülkeye ait YouTube trend video büyük verisi (Amerika Birleşik Devletleri, Kanada ve İngiltere) kullanılarak ülkeler arası kalıcı etiketlerin keşfi için yeni bir metot ve algoritma önerilmiştir. Keşfedilen ülkeler arası kalıcı etiketler, bazı YouTube video etiketlerinin küresel olarak kullanıldığı, ancak bazı etiketlerin ise yalnız bir ülkede kullanıldığını göstermektedir.

Keywords

YouTube trend video analizi, ülkeler arası kalıcı etiketler keşfi, video etiket analzii, YouTube büyük veri analizi

Supporting Institution

Niğde Ömer Halisdemir Üniversitesi Bilimsel Araştırma Projeleri Koordinasyon Birimi Koordinatörlüğü

Project Number

MMT2023/1-BAGEP

Thanks

Bu araştırma Niğde Ömer Halisdemir Üniversitesi Bilimsel Araştırma Projeleri Koordinasyon Birimi Koordinatörlüğü’nce desteklenmiştir. Proje No: MMT2023/1-BAGEP

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