Relevant bibliographies by topics / Youtube Users

Academic literature on the topic 'Youtube Users'

Author: Grafiati
Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Youtube Users"

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Hariyani, Nunik. "Konstruksi Konten Vlog Penerima Diamond Play Button Di Youtube Indonesia." JURNAL SOSIAL : Jurnal Penelitian Ilmu-Ilmu Sosial 21, no. 1 (May 9, 2020): 24–33. http://dx.doi.org/10.33319/sos.v21i1.55.

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Abstract— The existence of YouTube since 2005, is currently the second most popular social network in the world after Facebook. YouTube users in the world 1.9 billion. YouTube is used to share content and comments. This video-based social media is used to share videos and comment on one another. YouTube users in Indonesia have reached 50 million people. This research will look at how YouTube's Atta Halilintar and Ricis Official content constructions are recipients of the Diamond Play Button award, and how the creative strategy used by YouTuber in its video content. The results of this study are YouTube being the most active social platform used in Indonesia today. Youtube is used for identity and as a promotional media based on PPC (Pay Per Click) where every video that is deemed eligible in it contains Google Adsense ads. Youtube is a money field for many YouTubers in Indonesia with creative concepts according to popular culture. Keywords—: YouTube; Creative Strategy; Video Content; Construction.
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Tsao, Wen-Yu. "Understanding Users’ Preference to Engage in YouTubers." International Journal of Human Resource Studies 9, no. 1 (February 17, 2019): 277. http://dx.doi.org/10.5296/ijhrs.v9i1.14357.

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The YouTubers are the new vocations to make money. People like to access the videos to relax or learn from the special YouTuber. Despite the growth and commercial potential of virtual worlds, relatively little is known about what users’ motivations to favor specific YouTubers. This paper offered and empirically tested a conceptual model to fill this gap. Given the system characteristics (mobility, reachability, compatibility, convenience) and YouTuber specific characteristics (escapism and post popularity) integrated extrinsic and intrinsic motivation as their preference determinants. Using PROCESS on a survey of 349 users of YouTube. The results confirmed the role of extrinsic and intrinsic motivation as preference determinants and showed the two system and two YouTuber specific characteristics as motivational basis. Implications for research and practice are discussed.
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Widjaja, Kevin, and Raymond Sunardi Oetama. "K-Means Clustering Video Trending di Youtube Amerika Serikat." Ultima InfoSys : Jurnal Ilmu Sistem Informasi 11, no. 2 (December 28, 2020): 78–84. http://dx.doi.org/10.31937/si.v11i2.1508.

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Youtube is the most popular video platform in the world today. Successful YouTubers can create videos that are widely viewed by many Youtube users around the world. A lot of viral videos on Youtube came from the United States. But, making viral videos on Youtube is a tough challenge, both for seasoned YouTubers and especially for new YouTubers. This research focuses on discovering the properties of these viral videos by clustering them into distinct clusters. K-Means algorithm is used for the clustering process. The purpose of this clustering process is to look for patterns in the data that were previously unseen. The result shows that the videos are divided into three clusters which are built from 3 variables; views, likes and dislikes. The patterns and insights found in this study can be useful for aspiring video makers who want to achieve success as a Youtuber.
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Buf, Diana-Maria, and Oana Ștefăniță. "Uses and Gratifications of YouTube: A Comparative Analysis of Users and Content Creators." Romanian Journal of Communication and Public Relations 22, no. 2 (July 1, 2020): 75. http://dx.doi.org/10.21018/rjcpr.2020.2.301.

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Drawing on the classic media theory of uses and gratifications, this paper comparatively analyzes the uses of YouTube and the rewards obtained by consumers and content of this video sharing platform. The aim of this research is two-fold: 1. to identify the main uses and gratifications that determine consumers and content creators to use YouTube, and 2) to examine the reasons behind the decision to become a content creator on YouTube. Based on a qualitative research method, the paper highlights how YouTube is used from the perspective of consumers and content creators and the types of needs it gratifies. The research consists of 20 in-depth interviews with YouTube consumers and content creators from Romania. While for content consumers YouTube is mainly a means of relaxation and information, for content creators this platform becomes a source of recognition and social validation. The study also indicates that vlogging can provide job-specific gratifications. Moreover, the research reveals essential aspects behind the decision to become a content creator.
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O’Callaghan, Derek, Derek Greene, Maura Conway, Joe Carthy, and Pádraig Cunningham. "Down the (White) Rabbit Hole: The Extreme Right and Online Recommender Systems." Social Science Computer Review 33, no. 4 (October 16, 2014): 459–78. http://dx.doi.org/10.1177/0894439314555329.

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In addition to hosting user-generated video content, YouTube provides recommendation services, where sets of related and recommended videos are presented to users, based on factors such as co-visitation count and prior viewing history. This article is specifically concerned with extreme right (ER) video content, portions of which contravene hate laws and are thus illegal in certain countries, which are recommended by YouTube to some users. We develop a categorization of this content based on various schema found in a selection of academic literature on the ER, which is then used to demonstrate the political articulations of YouTube’s recommender system, particularly the narrowing of the range of content to which users are exposed and the potential impacts of this. For this purpose, we use two data sets of English and German language ER YouTube channels, along with channels suggested by YouTube’s related video service. A process is observable whereby users accessing an ER YouTube video are likely to be recommended further ER content, leading to immersion in an ideological bubble in just a few short clicks. The evidence presented in this article supports a shift of the almost exclusive focus on users as content creators and protagonists in extremist cyberspaces to also consider online platform providers as important actors in these same spaces.
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Kim, Dukjin, Wooyoung Lee, Dohyung Kim, and Gwangyong Gim. "An Empirical Study on Filter Bubbles in the YouTube Comments Network." International Journal of Software Innovation 9, no. 3 (July 2021): 52–65. http://dx.doi.org/10.4018/ijsi.2021070104.

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Some point out that the influence of YouTube's video recommendation algorithm is causing users to be exposed to only video clips in limited subjects or fields, especially to biased content with opinions that are tilted to one side. However, there is a lack of empirical research on filter bubbles as algorithms in YouTube have not been disclosed. This study indirectly demonstrated the phenomenon of filter bubble on YouTube by extracting comment-based content network between uploaders who posted videos and writers who wrote comments on the video by each subject of the contents. Also, this study analyzed communication patterns between users through social network analysis (SNA). According to the analysis, users' narrow information acquisition and communication phenomenon caused by the filter bubble in YouTube was found.
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Wattenhofer, Mirjam, Roger Wattenhofer, and Zack Zhu. "The YouTube Social Network." Proceedings of the International AAAI Conference on Web and Social Media 6, no. 1 (August 3, 2021): 354–61. http://dx.doi.org/10.1609/icwsm.v6i1.14243.

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Today, YouTube is the largest user-driven video content provider in the world; it has become a major platform for disseminating multimedia information. A major contribution to its success comes from the user-to-user social experience that differentiates it from traditional content broadcasters. This work examines the social network aspect of YouTube by measuring the full-scale YouTube subscription graph, comment graph, and video content corpus. We find YouTube to deviate significantly from network characteristics that mark traditional online social networks, such as homophily, reciprocative linking, and assortativity. However, comparing to reported characteristics of another content-driven online social network, Twitter, YouTube is remarkably similar. Examining the social and content facets of user popularity, we find a stronger correlation between a user's social popularity and his/her most popular content as opposed to typical content popularity. Finally, we demonstrate an application of our measurements for classifying YouTube Partners, who are selected users that share YouTube's advertisement revenue. Results are motivating despite the highly imbalanced nature of the classification problem.
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Khan, Rafaqat Alam. "Spammer Detection: A Study of Spam Filter Commentson YouTube Videos." International Journal for Electronic Crime Investigation 2, no. 4 (December 7, 2018): 5. http://dx.doi.org/10.54692/ijeci.2018.020425.

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This paper presents a methodology to find out the spam comments on YouTube videos. The purpose of this research is to find out the comments of those spam users, who comment for their own promotional intentions or to detect users whose comments that have no relevancy with the given video.The monetization policy introduced by YouTube for its user's channel and advertisement of different ads on YouTube videos has attracted a large number of users. This increase in a large number of users has also lead to an increase in malicious users whose job is to create automated bots for commenting and subscription to different YouTube channels. These malicious users'comments hurt the channel publicity and also affect the normal user's experience. YouTube is also working on this issue by using different methods to limit these kinds of automated bots malicious comments by blocking those comments. These kinds of methods are ineffective so far as spammers have found out different methods to bypass those heuristic approaches. Different machine learning approaches provide somehow better classification accuracy with the introduction of new approaches to solve it better than that. In this work, different techniques used for classification of spam comments with those of normal user comments to improve the classification and recent trend going on in this area are briefly analyzed to tackle this major issue.
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Khan, Rafaqat Alam. "Spammer Detection: A Study of Spam Filter Commentson YouTube Videos." International Journal for Electronic Crime Investigation 2, no. 4 (December 7, 2018): 5. http://dx.doi.org/10.54692/ijeci.2019.030125.

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This paper presents a methodology to find out the spam comments on YouTube videos. The purpose of this research is to find out the comments of those spam users, who comment for their own promotional intentions or to detect users whose comments that have no relevancy with the given video.The monetization policy introduced by YouTube for its user's channel and advertisement of different ads on YouTube videos has attracted a large number of users. This increase in a large number of users has also lead to an increase in malicious users whose job is to create automated bots for commenting and subscription to different YouTube channels. These malicious users'comments hurt the channel publicity and also affect the normal user's experience. YouTube is also working on this issue by using different methods to limit these kinds of automated bots malicious comments by blocking those comments. These kinds of methods are ineffective so far as spammers have found out different methods to bypass those heuristic approaches. Different machine learning approaches provide somehow better classification accuracy with the introduction of new approaches to solve it better than that. In this work, different techniques used for classification of spam comments with those of normal user comments to improve the classification and recent trend going on in this area are briefly analyzed to tackle this major issue.
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Wijayanto, Xenia Angelica, and Lestari Nurhajati. "Copyright issue on music back sound usage by Indonesian YouTuber." Journal of Social Studies (JSS) 16, no. 2 (September 24, 2020): 137–56. http://dx.doi.org/10.21831/jss.v16i2.31055.

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According to We Are Social research in January 2018, Indonesia's population now is 265,4 million, while its social media active users reached 130 million. 43% of people are using Youtube as their primary social media. This situation shows us that Youtube is still the most used and liked social media channel, followed closely by Facebook and Whatsapp. The vlogger phenomenon is also getting stronger among Indonesian young people. The increasing number of Youtube content production ranged from artists, public figures, and ordinary people, also known as Youtuber. One of the famous Youtuber is Raditya Dika, whose subscriber reached more than 3.3 million, and estimated income per year around USD 46 thousand to USD 739 thousand. The problem that arises is about the copyright violation in background music used by Indonesian Youtuber. This research tries to dig further data about the youtube policy in protecting the copyright issue in that area. This research uses a discourse analysis method on 15 videos from the top 5 Youtuber in Indonesia as the unit of analysis. The result shows that some Youtuber still violate the copyright issue while using background music on their Youtube materials production.
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Dissertations / Theses on the topic "Youtube Users"

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OLIVEIRA, DANIELA FERNANDES DE. "SURFING ON YOUTUBE: THE MASS SELF COMMUNICATION AND THE VIDEOS BROADCASTED BY COMMON USERS." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2009. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=14700@1.

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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO
Recentemente, de maneira mais extensiva, mas desde o fim da década de 90, um fenômeno pôs em cheque os papéis de quem produz e de quem consome informação no mundo. Esta dissertação procura analisar esse fenômeno na internet, chamado aqui de comunicação individual de massa. Especificamente, o foco deste estudo é o site de compartilhamento de vídeos YouTube, cujo slogan é broadcast yourself, ou seja, transmita você mesmo, e que conta com mais de 78 milhões de vídeos publicados – são cerca de 240 mil filmes adicionados todos os dias. Integrante da fase web 2.0, na qual pessoas comuns passaram a publicar textos, fotos, vídeos, comentários, desenhos e outros tipos de conteúdo na internet, o YouTube, originalmente concebido por três amigos desejosos de compartilhar com outros amigos seus vídeos pessoais, hoje integra o Google Inc., um dos maiores grupos do mercado web. Além das réplicas de conteúdos já exibidos no cinema, na TV e em outros meios, a grande maioria dos vídeos publicados e exibidos no site é totalmente inusitada. Para a análise, foram agrupados os vídeos produzidos por usuários comuns em três categorias: filmes virais, de família e videobiografias. Por meio das análises desses filmes e do diálogo com teóricos, são elaboradas questões atuais, como identidade, autoria e agenciamento coletivo, que parecem refletir bem a sociedade conectada.
Recently, more extensively, but since the end of the 90s, a phenomenon has changed the roles of those who produce and consume information in the world. This dissertation attempts to analyze this phenomenon, called here mass self communication, which took place in the internet in recent years. Specifically, the focus of this study is the website YouTube, whose slogan is broadcast yourself, and has over 78 million uploaded videos - about 240 thousand movies are being added there every day. Of the web 2.0 phase, in which ordinary people publish text, photos, videos, comments, drawings and other types of content on the internet, YouTube, originally conceived by three friends willing to share with their group their personal videos, today integrate Google Inc., one of the largest worldwide technology corporation groups. In addition to the large amount of cloned content, copied and digitalized from blockbuster movies, clips, TV soap opera and other sources, most of the videos published and displayed in YouTube are brand new. For the analysis of these videos produced by common users, they were grouped in three categories: viral films, family movies and video biographies. Some selected issues, particularly of identity, authorship and agency are then discussed, raising speculations about the nature and prospects of a interconnected society.
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Miia, Andrada, and Kaili Dong. "Avoiding Personalized Ads on Social Media : Understanding how YouTube users experience personalized advertising and what leads to ad avoidance in the context of personalization." Thesis, Internationella Handelshögskolan, Högskolan i Jönköping, IHH, Företagsekonomi, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-44135.

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Recent trends and developments in the fields of Big Data, Machine Learning, and Artificial Intelligence are completely transforming the way brands are engaging and communicating with their audience, allowing more personalized communications than ever. With the spread of social networking sites, such as Facebook, YouTube or Instagram a new opportunity arises for companies to connect to their consumers. However, since social media personalization implies the collection and analysis of highly personal data, consumers may develop negative reactions, attitudes or perceptions towards personalized advertising. Research covers extensively issues such as privacy concerns, invasiveness, forced exposure or irritation, which can lead to advertising avoidance. Though understanding the user perspective is crucial, the topic advertising avoidance in the context of personalization, especially in social media environments, hasn’t been discussed at great length. The purpose of this thesis is to understand how YouTube users experience personalized advertising while using the platform. The empirical findings of this thesis contribute to the ongoing research on personalized advertising within a social media setting. In addition, by understanding what can influence personalized ad avoidance on YouTube and describing how consumers express ad avoidance on the platform, this thesis aims to nurture a deeper understanding of the phenomenon. This study is based on an interpretative, abductive as well as a qualitative research design. It uses semi-structured interviews to explore the views, experiences, beliefs, and motivations of individual participants as well as focus groups that can leverage group dynamics to generate new qualitative data. The results of this thesis show that YouTube users experience ad avoidance in relationship with personalized ads for several reasons linked to prior negative attitudes, perceived goal impediment or ad irritation. The analysis of the findings revealed that users can experience cognitive, affective and behavioral ad avoidance as presented in the literature, but a theoretical model which can perfectly explain the phenomena of personalized ad avoidance on social media is currently not existent. While some antecedents claimed by the previously mentioned theoretical frameworks were also visible in the study, additional aspects may have an impact on how consumers experience personalized advertising avoidance in the social media environment, and more specifically on YouTube.
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Zhen, Zuguang. "The effect of mobile cellular network performance and contextual factors on smartphone users’ satisfaction : A study on QoE evaluation for YouTube video streaming via CrowdSourcing." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-177566.

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Mobile data traffic will continue to show rapid growth in the coming years; however the data revenue is not rising fast enough to ensure the operators’ profitability. Therefore, mobile operators must seek new approaches to find out what service does the customers need and what quality makes the customers satisfied in order to keep their increasingly sophisticated customers satisfied at the same time minimizing their revenue gap. This paper investigate the effect of mobile cellular network performance and contextual factors on smartphone users’ satisfaction, this was done via crowdsourcing through an experiment where an Android Application and a user Survey were included, which is able to evaluate and analyze the perceived quality of experience (QoE) for YouTube service for Android Smartphone users. To achieve this goal, the App NPT performs measurements of objective quality of service (QoS) parameters, whereas the survey carriers out collecting subjective user opinion. The result show that network performance parameters do impact the MOS (Mean Opinion Score) exponentially, either in a positively or negatively way, however, multiple parameters need to be considered together in order to draw a more accurate correlation with QoE. In addition, QoE are heavily affected by many other contextual factors, such as age and gender as well as users location. QoE are also impacted by several subjective factors, such as user expectation. Not always the highest throughput will lead to the best QoE, and not always the best technology (LTE) deserves the best MOS. Even though user received very high downlink throughput, their MOS value may still be low due to they might think the video were not fun to watch and the quality has not meet their expectation.
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Gerlock, Grant L. "Have it Your Way: Audience and Brand Identity in User-Generated Advertising." Miami University / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=miami1322833440.

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Armstrong, Erin H. "Political Campaigning 2.0: How the 2008 Obama-Biden and McCain-Palin Campaigns and Web Users Framed Race, Gender, and Age." Ohio University / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1386020805.

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Lundberg, Niclas, and Anders Söderman. "Establishment on YouTube : Catchphrases, communities and user involvement." Thesis, Umeå universitet, Institutionen för informatik, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-46136.

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YouTube is a great place for attention and discussion. Individuals and companies canuse the context and the system for branding of their content. Previous research in thearea has had a larger focus on mass statistics and social patterns on YouTube asequations, rather than as a social platform with people using it. Our research focusedon the users and why they choose to involve themselves with the content of theSwedishMealTime channel on YouTube and what we could do as a producer to createa more established channel, since we run it ourselves. This gave us an opportunity toextract data from the statistics on both YouTube and the corresponding Facebookpage of SwedishMealTime. We sent out an online survey to our subscribers withquestions revolving around the channel and content, in order to gain more insight ofwhat kind of content they prefer. A netnographic study was made in combinationwith a survey to collect the data for the analysis. Our results suggest that a regularupload scheme, communication and interaction with subscribers and establishment ofthe channel increases the sense of belonging, which in turn increases the exposure ofthe channel and the number of users subscribing to it. Future research will requireinformation about more channels, to identify behaviour between them, and if thereare any patterns for a viral success.
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Hagerty, Sean P. "An examination of the uses and gratifications of YouTube." Click here for download, 2008. http://proquest.umi.com/pqdweb?did=1629576031&sid=1&Fmt=2&clientId=3260&RQT=309&VName=PQD.

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Kim, Jin. "User-generated content (UGC) revolution?: critique of the promise of YouTube." Diss., University of Iowa, 2010. https://ir.uiowa.edu/etd/529.

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This dissertation concerns the relationship between the liberating potential of an individuals' use of new media and the various institutional constraints on that. While I aim to explore the emancipatory potential of YouTube, I seek not to lose sight of the cultural, historical and political forces that limit individual use of it. This dissertation examines YouTube from agent, institution and text perspectives, the triangle of media studies. Each perspective illustrates tensions and conflicts between the personal and the public, amateurism and professionalism, narrowcasting and broadcasting, and User-Generated Content (UGC) and Professionally-Generated Content (PGC). Technological development promises the expansion of the human being, the empowerment of individuals and widening opportunities of communication through personalized media. Amateur users take advantage of the convenience and accessibility in YouTube, and consequently they have a chance to deeply engage in the media content production-distribution-consumption-feedback system. With its encouragement of amateur video production, this new medium seems to have the capability to change the nature of media users, from passive audiences to active creators. However, the myth of the active user is inseparable from celebrity culture. Self-expression on the web is often imbued with the fascination with fame, but is not the same as user empowerment. Amateurism in UGC came to be compromised when the line between UGC and PGC started to blur. From a techno futuristic perspective, YouTube seems to make the audience into interactive users, but that interactivity is close to active consumption in the realm of disposable celebrity. The development of mass media always involves a tension between mass communication and interpersonal communication. Historically, YouTube is positioned within the development of personalized media. YouTube is an evolutionary medium under the influence of traditional broadcasting, rather than a revolutionary medium discontinuous from media history. What contemporary people think new about YouTube are likely the consequences of technological evolution rather than those of media revolution. Exploring YouTube, I do not deny the convenience and accessibility of UGC media, but I do not want to lose sight of the legacy of amateurism, individualism and user participation.
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Ram, Shri, and Nitin Paliwal. "Design and Development of Multimedia Based User Education Program: The Advantages of YouTube." KBD Publication, 2012. http://hdl.handle.net/10150/299604.

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User education is one of the essential activities of the library to optimize the use of library services. This paper discusses the use of multimedia based videos for the promotion of library services and activities with the help of emerging trends and technologies and the power of Web 2.0 especially YouTube. Through this paper, it is tried to demonstrate the procedural aspects of promoting user education through developing multimedia based user education program and utilizing the services of YouTube as media of marketing and communication at Jaypee University of Information Technology, Solan, Himachal Pradesh, India.
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Ram, Shri, and Nitin Paliwal. "Design and Development of Multimedia Based User Education Program: The Advantages of YouTube." KBD Publications, 2013. http://hdl.handle.net/10150/283594.

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User education is one of the essential activities of the library to optimize the use of library services. This paper discusses the use of multimedia based videos for the promotion of library services and activities with the help of emerging trends and technologies and the power of Web 2.0 especially YouTube. Through this paper, it is tried to demonstrate the procedural aspects of promoting user education through developing multimedia based user education program and utilizing the services of YouTube as media of marketing and communication at Jaypee University of Information Technology, Solan, Himachal Pradesh, India.
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Books on the topic "Youtube Users"

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L, Hargrave C., ed. I, Justine: An analog memoir. New York: Simon & Schuster, 2015.

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La edad de la verdad. Mexico, D.F: Planeta Pub Corp., 2015.

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Really professional Internet person. New York, NY: Scholastic, Incorporated, 2015.

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Han'gukhyŏng UCC mak'et'ing. Sŏul-si: Haenaem, 2007.

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Chin-yŏng, Chang, ed. Taehan Minʼguk UCC tʻŭraedŭ. Sŏul-si: Saebit, 2007.

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Chin-yŏng, Chang, ed. Taehan Minʼguk UCC tʻŭraedŭ. Sŏul-si: Saebit, 2007.

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Chin-yŏng, Chang, ed. Taehan Minʼguk UCC tʻŭraedŭ. Sŏul-si: Saebit, 2007.

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The cult of the amateur: How blogs, MySpace, YouTube, and the rest of today's user-generated media are destroying our economy, our culture, and our values. New York: Currency Doubleday, 2007.

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Keen, Andrew. The cult of the amateur: How today's internet is killing our culture. London: Nicholas Brealey, 2007.

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Keen, Andrew. The Cult of the Amateur. New York: Broadway Books, 2007.

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Book chapters on the topic "Youtube Users"

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Hutchinson, Jonathon, and Tim Dwyer. "How Instagram and YouTube users share news." In The Dynamics of Influencer Marketing, 123–42. London: Routledge, 2022. http://dx.doi.org/10.4324/9781003134176-8.

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Vazquez-Calvo, Boris, Nikolaj Elf, and Adriana Gewerc. "Catalan Teenagers’ Identity, Literacy and Language Practices on YouTube." In Technology and the Psychology of Second Language Learners and Users, 251–78. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-34212-8_10.

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Sureka, Ashish, Ponnurangam Kumaraguru, Atul Goyal, and Sidharth Chhabra. "Mining YouTube to Discover Extremist Videos, Users and Hidden Communities." In Information Retrieval Technology, 13–24. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-17187-1_2.

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Vybihal, Joseph, and Mika Desblancs. "Analysis of the Impact of Algorithms on Siloing Users: Special Focus on YouTube." In AI and Society, 51–69. Boca Raton: Chapman and Hall/CRC, 2022. http://dx.doi.org/10.1201/9781003261247-6.

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Yang, Peter. "The Cognitive and Psychological Effects of YouTube Video Captions and Subtitles on Higher-Level German Language Learners." In Technology and the Psychology of Second Language Learners and Users, 83–112. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-34212-8_4.

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Rulyova, Natalia. "Russian New Media Users’ Reaction to a Meteor Explosion in Chelyabinsk: Twitter Versus YouTube." In Emerging Genres in New Media Environments, 79–97. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-40295-6_4.

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O’Neill, Stephen. "Theorizing User Agency in YouTube Shakespeare." In The Shakespeare User, 129–47. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-61015-3_7.

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Han, Yo-Sub, Laehyun Kim, and Jeong-Won Cha. "Evaluation of User Reputation on YouTube." In Online Communities and Social Computing, 346–53. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02774-1_38.

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Ksiazek, Thomas B., and Limor Peer. "User Comments And Civility On Youtube." In The Routledge Companion to Digital Journalism Studies, 244–52. London ; New York : Routledge, 2017.: Routledge, 2016. http://dx.doi.org/10.4324/9781315713793-25.

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Tiwari, Sunita, Abhishek Jain, Prakhar Kothari, Rahul Upadhyay, and Kanishth Singh. "Learning User Preferences for Recommender System Using YouTube Videos Tags." In Computational Science and Its Applications – ICCSA 2018, 464–73. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-95171-3_36.

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Conference papers on the topic "Youtube Users"

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Chowdhury, Shaiful Alam, and Dwight Makaroff. "Characterizing Videos and Users in YouTube: A Survey." In 2012 Seventh International Conference on Broadband and Wireless Computing, Communication and Applications (BWCCA). IEEE, 2012. http://dx.doi.org/10.1109/bwcca.2012.47.

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Tomlein, Matus, Branislav Pecher, Jakub Simko, Ivan Srba, Robert Moro, Elena Stefancova, Michal Kompan, Andrea Hrckova, Juraj Podrouzek, and Maria Bielikova. "Black-box Audit of YouTube's Video Recommendation: Investigation of Misinformation Filter Bubble Dynamics (Extended Abstract)." In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. California: International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/749.

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In this paper, we describe a black-box sockpuppeting audit which we carried out to investigate the creation and bursting dynamics of misinformation filter bubbles on YouTube. Pre-programmed agents acting as YouTube users stimulated YouTube's recommender systems: they first watched a series of misinformation promoting videos (bubble creation) and then a series of misinformation debunking videos (bubble bursting). Meanwhile, agents logged videos recommended to them by YouTube. After manually annotating these recommendations, we were able to quantify the portion of misinformative videos among them. The results confirm the creation of filter bubbles (albeit not in all situations) and show that these bubbles can be bursted by watching credible content. Drawing a direct comparison with a previous study, we do not see improvements in overall quantities of misinformation recommended.
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Anagnostou, Antonios, Ioannis Mollas, and Grigorios Tsoumakas. "Hatebusters: A Web Application for Actively Reporting YouTube Hate Speech." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/841.

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Hatebusters is a web application for actively reporting YouTube hate speech, aiming to establish an online community of volunteer citizens. Hatebusters searches YouTube for videos with potentially hateful comments, scores their comments with a classifier trained on human-annotated data and presents users those comments with the highest probability of being hate speech. It also employs gamification elements, such as achievements and leaderboards, to drive user engagement.
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Spinelli, Larissa, and Mark Crovella. "How YouTube Leads Privacy-Seeking Users Away from Reliable Information." In UMAP '20: 28th ACM Conference on User Modeling, Adaptation and Personalization. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3386392.3399566.

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Gao, Wenxi, Ishmael Rico, and Yu Sun. "Data-Driven Intelligent Application for Youtube Video Popularity Analysis using Machine Learning and Statistics." In 2nd International Conference on Blockchain and Internet of Things (BIoT 2021). AIRCC Publishing Corporation, 2021. http://dx.doi.org/10.5121/csit.2021.110807.

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People now prefer to follow trends. Since the time is moving, people can only keep themselves from being left behind if they keep up with the pace of time. There are a lot of websites for people to explore the world, but websites for those who show the public something new are uncommon. This paper proposes an web application to help YouTuber with recommending trending video content because they sometimes have trouble in thinking of the video topic. Our method to solve the problem is basically in four steps: YouTube scraping, data processing, prediction by SVM and the webpage. Users input their thoughts on our web app and computer will scrap the trending page of YouTube and process the data to do prediction. We did some experiments by using different data, and got the accuracy evaluation of our method. The results show that our method is feasible so people can use it to get their own recommendation.
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Nie, Bin, Honggang Zhang, and Yong Liu. "Social interaction based video recommendation: Recommending YouTube videos to facebook users." In IEEE INFOCOM 2014 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS). IEEE, 2014. http://dx.doi.org/10.1109/infcomw.2014.6849175.

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Ribeiro, Manoel Horta, Virgílio A. F. Almeida, and Wagner Meira Jr. "Misinformation, Radicalization and Hate Through the Lens of Users." In Concurso de Teses e Dissertações da SBC. Sociedade Brasileira de Computação - SBC, 2020. http://dx.doi.org/10.5753/ctd.2020.11373.

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The popularization of Online Social Networks has changed the dynamics of content creation and consumption. In this setting, society has witnessed an amplification in phenomena such as misinformation and hate speech. This dissertation studies these issues through the lens of users. In three case studies in social networks, we: (i) provide insight on how the perception of what is misinformation is altered by political opinion; (ii) propose a methodology to study hate speech on a user-level, showing that the network structure of users can improve the detection of the phenomenon; (iii) characterize user radicalization in far-right channels on YouTube through time, showing a growing migration towards the consumption of extreme content in the platform.
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Ie, Eugene, Vihan Jain, Jing Wang, Sanmit Narvekar, Ritesh Agarwal, Rui Wu, Heng-Tze Cheng, Tushar Chandra, and Craig Boutilier. "SlateQ: A Tractable Decomposition for Reinforcement Learning with Recommendation Sets." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/360.

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Reinforcement learning methods for recommender systems optimize recommendations for long-term user engagement. However, since users are often presented with slates of multiple items---which may have interacting effects on user choice---methods are required to deal with the combinatorics of the RL action space. We develop SlateQ, a decomposition of value-based temporal-difference and Q-learning that renders RL tractable with slates. Under mild assumptions on user choice behavior, we show that the long-term value (LTV) of a slate can be decomposed into a tractable function of its component item-wise LTVs. We demonstrate our methods in simulation, and validate the scalability and effectiveness of decomposed TD-learning on YouTube.
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Hanafi, Muhammad Zein, and Rusdah. "Segmentation of Customers’ Experiences of YouTube Streaming Application Users in South Jakarta using K-means Method." In 2020 International Conference on Smart Technology and Applications (ICoSTA). IEEE, 2020. http://dx.doi.org/10.1109/icosta48221.2020.1570613873.

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"An Examination of Trendyol’s Legendary-Days Youtube Ads Through Comments." In COMMUNICATION AND TECHNOLOGY CONGRESS. ISTANBUL AYDIN UNIVERSITY, 2021. http://dx.doi.org/10.17932/ctcspc.21/ctc21.035.

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The internet, where people spend a big chunk of their time, has become an indispensable part of life. Thanks to online e-commerce websites, being able to choose from different categories and products and procure everything needed, from clothes to technology, from major appliances to groceries, is one of the most important conveniences of our age. As the interest of consumers increased, so did the number of e-commerce websites. These websites started to make numerous special offers and marketing campaigns to differentiate themselves from their competitors. One of these campaigns, the Black Friday, has taken the shopping habits within the context of consumption culture to a whole new level the moment it was introduced in Turkey. This discount tradition that went beyond the borders of the US with globalization, has spread around the world. An example to the fact that traditional shopping has given its place to e-commerce applications thanks to the rapid development of digitalization, one of Turkey’s pioneer e-commerce applications, Trendyol has transformed Black Friday and started the “Legendary Days” campaign. The frequency of the promotion work within the process of this campaign has caused the emergence of a different range of perceptions in the target audience. Encountering Trendyol’s “Legendary Days” advertising campaign too often has created both positive and negative perception, especially during COVID-19 lockdowns where people spend most of their time watching TV, browsing the internet, or playing online games. In this study, 429 YouTube comments on Trendyol’s four commercial films on YouTube for Trendyol’s “Legendary Days” campaign that took place on 25th, 26th, and 27th of November 2020, have been examined through a content analysis of 13 items. Additionally, a text analysis was conducted on comments. According to the results of the study, it was found that being exposed to YouTube advertisements on a frequent basis, especially during a pandemic where people cannot leave their homes, had created a negative reputation for Trendyol’s “Legendary Days” campaign among YouTube users. This case causes a discrepancy between the positive reputation works Trendyol has conducted during the pandemic period.
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