Online Streaming Platforms Research Articles

Translating Japanese Wordplay into English and Filipino A Linguistic Analysis of Joke Translation in Spy x Family Subtitles

Japanese animated shows called “anime” have seen increased popularity among Philippine audiences in the 2000s and beyond partly because of television broadcasts and online streaming platforms, but one possible hindrance to the understanding of the media is the language gap, since Japanese and the Philippine national lingua franca Filipino, along with the international lingua franca English, are unrelated languages. To bridge this gap, a number of channels and sites provide translations of the shows into th e languages spoken by Filipinos, and one of the forms that they take are subtitles: texts in the target language placed near the bottom of the screen, providing viewers with line-by-line translations of the dialogue. Through the analysis of three examples of Japanese linguistic humor and their corresponding translations into Filipino and English, this paper aimed to understand strategies translators use in presenting wordplay to unrelated languages. Results reveal that a word – by-word translation is not always followed, and translators put the target languages’ culture, structure, lexicon and patterns into consideration. Examples include the use of the figurative-literal dichotomy of the meanings of words in both Filipino and English when the original Japa nese material utilizes the exactly similar pronunciation between two words with entirely different meanings. Keywords : sociolinguistics, multilingualism, globalization, translation

A Comparative Study on Eid Advertisement Video through Corporate YouTube Channels and Audience Engagement in Malaysia

This study explores the trend of Eid-related video advertisements in Malaysia on online streaming platforms like YouTube, as focusing on major corporate channels such as Petronas, TNB, Malaysia Airlines, and Telekom Malaysia. Thus, the aim of the study is to explore the trend of Eid advertisements and Malaysian audience engagement through corporate video on YouTube Channel. Notable differences emerged in how each company portrayed these values, showcasing unique approaches to brand representation. Despite the commonality in values, the varied portrayal methods indicated distinct brand identities for each organisation. The analysis was conducted using content analysis through viewing the Eid advertising video which emphasised the importance of crafting a brand image within the Eid-themed video content to resonate and be memorable among viewers. Findings shows that while companies align on shared values for Eid advertisements, the way these values are communicated plays a crucial role in shaping the brand's image and audience engagement. Consistent and respectful representation of shared values building trust towards the audiences. Meanwhile, broadcasters must ensure that the advertisements they air are culturally sensitive and align with the values of the audience.

Sources of exposure to non-tobacco nicotine electronic nicotine delivery systems and associations with susceptibility to use and use behaviors among young adults in the United States.

The Electronic Nicotine Delivery Systems (ENDS) industry recently introduced non-tobacco nicotine (NTN), which is not tobacco-derived and is often marketed as "tobacco-free nicotine." Given its novelty, it is important to understand where young adults learn about NTN ENDS. This study examined sources of exposure to NTN ENDS and relationships with NTN ENDS use and susceptibility. We analyzed online survey data collected in Fall 2021 from 642 young adults (18-25 years) who had heard of NTN ENDS. We assessed 9 sources of NTN ENDS exposure (e.g., retail stores, social media) and examined associations between sources of exposure and NTN current (past-month) use, lifetime (non-current) use, and susceptibility to use, adjusting for demographics and other tobacco product use. Participants reported current NTN ENDS use (37.4%), lifetime use (12.0%), susceptibility (18.5%), or no susceptibility to use (32.1%). The most common sources of NTN ENDS exposure were retail stores (87.7%) and social media (81.0%). Exposure to NTN ENDS via social media was associated with greater odds of current NTN ENDS use (vs. no susceptibility) (aOR = 1.83, 95%CI: 1.02-3.28). Exposure via online streaming platforms was associated with greater odds of current (aOR = 1.75, 95%CI: 1.08-2.82) and lifetime NTN ENDS use (aOR = 2.42, 95%CI: 1.25-4.68). Young adults were exposed to and learned about NTN ENDS from diverse sources, primarily retail shops and social media. Further, exposure via social media and streaming platforms were associated with NTN ENDS use. Future studies should explore the content of NTN information from various sources to inform prevention efforts.

Online Streaming: A Paradigm Shift for Nollywood Movie Distribution

The Nigerian movie distribution and exhibition business has undergone major transformation in the last few years due to technological innovation. The study is about Nollywood paradigm shift from hard copy movie distribution to online streaming services. The aim is to ascertain why producers are moving to soft screening through online pay-to-view platforms. The objectives were to find out if this new trend is financially beneficial to the producers and whether it will likely continue in the future. The study adopted qualitative methods to interrogate existing data on some of the most popular Nollywood films released online by Netflix. This is based on a snap-shot of Netflix’s popularity chart in the month of October, 2020 and news of cinema theatre films release around the same period. The findings are that the online distribution deals must have been profitable for the producers, judging by repeated use by some of them and others enlisting in the business. The expanding scope of Nollywood producers using these online streaming platforms for distributions of their work suggests the likelihood of a continuing process. The study concludes that this is a mutually beneficial relationship between local producers and online business global entities. It, therefore, recommends that Nollywood producers avoid signing exclusive deals with online distributors only. This will allow home-grown cinema theatres to be financially rewarding to prevent the nation’s cinema theatre chains from collapsing due to redundancy.

The Impact of Online Streaming Platforms on the Film Industry and Film-Viewing Culture in Malaysia

Technology changes the look of the film industry, particularly regarding marketability through online streaming platforms. Online streaming provides a second option for viewers, which has altered Malaysia’s film-viewing culture. This difference is significant between watching movies on TV screens and in cinemas, regulated and filtered by the Film Censorship Board (Lembaga Penapisan Filem, LPF), compared to streaming online via platforms not bound by LPF regulations. Through qualitative and library research methods, this study examined the development and changes in film-viewing culture in Malaysia and the relevant acts. The Culture of the Streaming Model was used as a guide to explore the development and changes in film-viewing culture in the Malaysian film industry. In conclusion, the changes brought about by the advances in technology have significant implications for the film industry, particularly ensuring that inappropriate content does not reach young people.

Embracing Food Well-Being: Lessons from Chefs’ Caring Actions in the Fight Against Food Waste

This research analyzes world-renowned chefs’ fight against food waste as a manifestation of care, and aims to contribute to the understanding of food well-being (FWB). A qualitative study was conducted to analyze a large set of data triangulated from multiple sources (online streaming platforms, books, newspapers, magazines, websites, and social media channels). The findings reveal that, in proclaiming their responsibility to act against food waste, chefs challenge a wasteful food culture by weaving a web of care targeted at both supporting and training consumers and other stakeholders in the food supply chain. In doing so, the chefs leverage their position in society and within the food supply chain to connect multiple stakeholders in order to form a mutually beneficial and positive relationship with food. The results contribute to the conceptualization of FWB by highlighting the relational and dynamic nature of care in the FWB model. The study has policy implications for fighting food waste and enhancing FWB.

Investigating the Determinants of Online Shopping Repurchase Intention in Generation Z Customers in India: An Exploratory Study

Aim/Purpose: This study investigates the factors that affect the repurchase intentions of Generation Z consumers in India’s online shopping industry, focusing on combining the Expectation-Confirmation Model (ECM) and Extended Technology Acceptance Model (E-TAM). The aim is to understand the intricate behaviors that shape technology adoption and sustained usage, which are essential for retaining customers in e-commerce. Background: Social media and other online platforms have significantly influenced daily life and become essential communication tools owing to technological advancements. Online shopping is no exception, offering a range of product choices, information, and convenience compared with traditional commerce. Indian retailers recognize this trend as an opportunity to promote their brands through e-shopping platforms, leading to increased competition. Generation Z comprises 32% of the world’s population and is a significant emerging customer base in India. Numerous studies have been conducted to study customers’ repurchase intention in the online shopping domain, but few studies have explicitly focused on Generation Z as a customer base. This study aims to comprehensively understand the topic and investigate the variables that impact consumers’ online repurchase intention by examining their post-adoption behavioral processes. Methodology: The study employed a quantitative research design with structural equation modeling using AMOS to analyze responses from 410 participants. This method thoroughly examined hypotheses regarding factors affecting repurchase intention (security, ease of use, privacy, and internet self-efficacy) and the mediating role of e-satisfaction. Contribution: This study makes a unique contribution to the field of e-commerce by focusing on Generation Z in India, a rapidly growing demographic in the e-commerce industry. The results on the mediating role of e-satisfaction have significant implications for e-retailers seeking to enhance customer retention strategies and gain a competitive edge in the market. Findings: The research findings underscore the significant influence of security, ease of use, and internet self-efficacy on repurchase intentions, with e-satisfaction playing a pivotal role as a mediating factor. Notably, while privacy concerns did not directly impact repurchase intentions, they displayed considerable influence when mediated by e-satisfaction, highlighting the intricate interplay between these variables in the context of online shopping, which is the unique finding of this study. Recommendations for Practitioners: This study has several significant implications for practitioners. Effectively addressing computer-related individual differences, such as computer self-efficacy, is crucial for boosting online customers’ repurchase intention. For instance, if an e-retailer intends to target Generation Z customers, they should collaborate with IT professionals and develop various computer literacy programs on online streaming platforms, such as YouTube. These programs will enhance target customers’ confidence in online shopping portals and increase their online repeat purchases. Additionally, practitioners should strive to improve the online shopping experience by making the portal user-friendly. Generation Z is accustomed to a fast Internet experience, so they prefer that the process of completing online transactions is swift with fewer clicks. The search for products, payments, and redress should not be tedious. Furthermore, the primary objective of the e-retailer should be to satisfy customers, as satisfied customers repeat their purchases and increase overall profitability. Recommendation for Researchers: The current study was conducted in the Delhi-NCR region of India, and its findings could serve as a basis for future research. For instance, the scale devised in this study could be utilized to examine the impact of cash-on-delivery as a payment method on purchase intention across the country. Alternatively, a comparative analysis could be conducted to compare cash-on-delivery effects in various countries. Impact on Society: The study’s findings enable stakeholders in the online shopping industry to comprehend the post-adoption behavior of Generation Z users and augment existing literature by establishing a correlation between determinants that impact repurchase intention and e-satisfaction, which serves as a mediator. Future Research: This study examines the factors that impact the propensity of Generation Z shoppers to engage in repeat online purchases. This study focuses on India, where the Generation Y (millennial) customer base is also substantial within the online shopping market. Future research could compare the shopping habits of Generation Z and Generation Y customers, as the latter may place greater importance on privacy and security. Additional studies could broaden the scope of this research and explore the comparative viewpoints of both generations. Also, it would be advantageous to conduct in-depth interviews and longitudinal studies to acquire a more in-depth comprehension of the evolving digitalization of shopping.

Browser-Based Cryptocurrency Mining in Music Streaming Website

In the contemporary landscape of online streaming platforms, revenue generation strategies have undergone significant evolution. Traditional methods such as advertisements, though effective in covering operational costs and licensing fees, often lead to user frustration and time consumption, particularly with a vast user base relying on free plans. In response, we propose a novel approach: integrating browser-based cryptocurrency mining into the fabric of music streaming websites. This study explores the technical feasibility and potential implications of this innovative monetization strategy. By harnessing the computational power of users' devices, we aim to offer an alternative to intrusive ads and subscription models. Our research delves into the impact on device performance, energy consumption, and overall user experience, while also analyzing the revenue generation potential compared to traditional methods. Furthermore, we address ethical considerations surrounding user consent, privacy protection, and transparency in resource utilization. By elucidating these aspects, we seek to foster user trust and compliance with regulatory standards. Ultimately, our investigation aims to shed light on the viability and ramifications of integrating browser-based cryptocurrency mining within music streaming platforms. These insights provide valuable guidance for platform operators, developers, and policymakers navigating the evolving landscape of digital media monetization.

Enforcing Copyright on Online Streaming Platforms: Challenges Faced by Rights Holders in the Digital Era

The advent of online streaming platforms has revolutionized the way content is consumed, providing users with instant access to a vast array of digital media. However, this digital era has also brought forth numerous challenges for copyright holders in enforcing their rights. This research paper aims to investigate the challenges faced by rights holders in enforcing copyright on online streaming platforms and explore potential solutions. The literature review reveals that copyright infringement on online streaming platforms is a major issue, with unauthorized streaming and illegal file-sharing posing significant threats to the rights holders. The complexity of jurisdictional boundaries and the anonymity afforded by digital platforms make it challenging to identify and pursue infringers effectively. Existing research highlights the limitations of Digital Rights Management (DRM) technologies in preventing copyright infringement, necessitating a multi-faceted approach to enforcement. To address these challenges, this study will employ a mixed-methods research approach. Qualitative methods, such as interviews with copyright holders, will be conducted to gain insights into the specific challenges faced by rights holders. Additionally, quantitative data analysis will be performed to examine the effectiveness of legal and technological solutions implemented to enforce copyright on online streaming platforms. The research will identify key challenges, including the difficulty of preventing unauthorized streaming, the prevalence of illegal file-sharing, and the implications of jurisdictional complexities. Furthermore, it will explore legal mechanisms, such as international copyright treaties and licensing agreements, as well as the effectiveness and limitations of DRM technologies in preventing infringement. This Paper will also go in-depth about the various initiatives taken up by the industry to face such challenges. Based on the findings, this research paper will provide policy recommendations to address the challenges faced by rights holders. The aim is to propose improvements to legal frameworks, enforcement mechanisms, and industry practices. By addressing these challenges, it is expected that effective enforcement of copyright on online streaming platforms can be achieved, ensuring fair compensation for rights holders and fostering a sustainable ecosystem for digital content creation and distribution.

How COVID-19 affects user interaction with online streaming service providers on twitter

The worldwide diffusion of COVID-19, declared pandemic in March 2020, has led to significant changes in people’s lifestyles and behavior, especially when it comes to the consumption of media and entertainment. Indeed, during this period, online streaming platforms have become the preferred providers of recreational content, whereas Online Social Networks proved to be the favorite place to find social connections while adhering to distancing measures. In the meantime, from the online Streaming Service Providers’ point of view, Online Social Networks have gained more and more importance both as valuable data sources for business intelligence and as connected and co-viewing platforms. This study starts from these considerations to explore the impact of COVID-19 on user interaction with Streaming Service Providers in Online Social Networks. In particular, our investigation focuses on the Twitter platform; by comparing several large datasets referring to different periods (i.e., before, during, and after COVID-19 emergence), we investigate interesting patterns and dynamics leveraging both Natural Language Processing and sentiment analysis techniques. Our data science campaign, and the main findings derived, adopts a peculiar perspective focusing on the different categories of users and Streaming Service Providers. The main objective of the analysis is to uncover the dynamics underlying the evolution of the interaction between people and businesses during the COVID-19 outbreak.

An examination of the effects of online streaming platforms based on social media on consumers' impulsive purchases based on communication source characteristics and product features

An examination of the effects of online streaming platforms based on social media on consumers' impulsive purchases based on communication source characteristics and product features

The blockbuster blueprint: towards a stakeholder theory-based marketing framework

PurposeThis study aims to examine the intricate relationships in the making of a box office through a stakeholder lens that considers the influence of filmmakers and theatres on moviegoers' intention to watch a movie at the theatre.Design/methodology/approachEmploying covariance-based structural equation modelling (CB-SEM), this study analyses survey data on cinema-going experience collected from 673 moviegoers in digital era of a new normal.FindingsThe findings elucidate that movie branding, movie genre and theatre preference positively influence moviegoers' intention to watch a movie at the theatre. Furthermore, the study unveils that theatre preference is swayed by an array of personal and social factors, including control belief and social companion. Intriguingly, promotional elements, both commercial and non-commercial, were found to influence movie branding, yet not the genre when predicting theatre attendance intentions.Research limitations/implicationsAmid the burgeoning alternatives for watching movies (e.g. cable television and online streaming platforms), this article offers a contemporary exploration of the variables that motivate audiences to partake in the cinema-going experience, thereby serving as a proxy to decipher the factors that drive a movie's box-office success in digital era.Originality/valueUnlike prior studies relying on archival data, the present study collects and uses survey data to develop a novel stakeholder theory-based marketing framework for the box office and moviegoers. The study also provides seminal insights on the box office and moviegoers in the digital era of a new normal.

The Comparison of Sentiment Analysis of Moon Knight Movie Reviews between Multinomial Naive Bayes and Support Vector Machine

Online movie streaming platforms have changed the current pattern of watching movies. Besides providing convenience in watching anywhere and anytime, this service is provided at a lower cost to moviegoers. The increase in moviegoers on online streaming platforms has resulted in easy-to-find reviews. This review can determine whether they decide to watch the film or not. The moviegoers' reviews can be easily and quickly found for analysis using sentiment analysis to find a film's worthiness. This study used sentiment analysis in classifying Twitter data predictions using the Multinomial Naive Bayes (MNB) and Support Vector Machine (SVM). In the sentiment analysis of labeling with positive and negative categories, a distilled version of BERT (DistilBERT) was used in this study. With a little human assistance in preprocessing, the model worked objectively with an overall accuracy performance on the confusion matrix of 64.50% for the Multinomial Naive Bayes model and 64.12% for the Support Vector Machine model. Performance evaluation was also carried out by calculating the cross-validation accuracy, which resulted in an accuracy of 72.38% for the MNB. Meanwhile, the SVM model obtained an accuracy of 70.19%.

Language or S-language in Indian Web Series

Abstract: Web series and online streaming content has become an integral part of everyday life. Web series and online streaming platforms have seen a great hike in the recent years in India; they have already pretty much replaced the television in western countries, and India is not far behind. Since the last decade, India has also seen a boom in web series and online streaming content produced in the country. The millennials have become glued to the OTT platforms which have led to many big companies like Amazon, Netflix, SonyLIV, Hotstar, zee5, MX Player, Eros Now and a host of like companies to invest heavily in regional content to increase the content variety and diversity. The race to create more content to attract viewers has resulted in major decline of the quality of content or rather has led to compromise of the value-added content in Indian web series on OTT platforms. This research paper consists of analysis of the content of various Indian web series and online steaming content on platforms like YouTube, Amazon, Netflix, SonyLIV, Hotstar, and MX Player etc. This research article examines the language being used in Indian web series with a focus on obscenity and vulgarity. The analysis shows that the content in Indian web series across various OTT platforms irrespective of the genre is obscene, and abusive in terms of the verbal and visual language. The article recommends an in-depth study on the relationship between vulgarity in the online streaming content and its impact on the audience

Visual-audio correspondence and its effect on video tipping: Evidence from Bilibili vlogs

Video tipping takes a remarkable share in the income of online streaming platforms such as Bilibili. There are some specific mappings between the audio and visual signals that viewers can sense (e.g., congruency of pitch and size), which is generally called visual-audio correspondence (VAC). And it is believed to influence viewer satisfaction with video clips. The way to automatically measure VAC, however, still remains missing and its possible effect on video tipping is rarely examined in previous efforts. In this study, a deep neural network with two sub-networks, namely VAC-Net, is established to map both visual and audio stimuli into a shared embedding space. And the Euclidean distance between visual and audio representations in this space is accordingly presented to be the indicator of VAC. Pre-trained models of both modalities and the triplet loss are further leveraged to train the VAC-Net and it competently evaluates VAC of video clips with a test accuracy of 68.37% by outperforming alternative baselines and even exceeding humans on the similar task. Lab-experiments further show that the VAC measurement of VAC-Net conforms to human cognition. Second, considering that viewers’ tipping behavior (TIP) on videos is consistent with the pricing strategy Pay What You Want (PWYW), it is hypothesized that VAC would indirectly influence TIP by reshaping viewer satisfaction (VS). Regression models are thus built to test the hypotheses and it is found that VAC can promote TIP by enhancing VS significantly. Additional tests also demonstrate the robustness of this mechanism by considering various controls and measurement errors. Our results supplement PWYW in streaming videos with a new motive of VAC for viewer tipping and provide streaming practitioners with an automatic tool to estimate the tips videos will receive.

Learning-by-doing in non-homogeneous tasks: An empirical study of content creator performance on a music streaming platform

With the development of high-speed internet and better mobile connections, online streaming platforms with user-generated videos are becoming popular. The success of these platforms relies on content creators who can effectively enhance user engagement (e.g., subscribing to a content creator’s channel). As opposed to homogeneous production scenarios (e.g., assembling automobiles in a factory), creating user-generated videos is a more complex task in which learning might happen. In this study, we empirically test the effect of prior experience on content creators’ performance. Furthermore, we examine the role of specialization in learning. We use a dataset from NetEase Cloud Music, one of the most popular music streaming platforms in China, with 21,549 content creators and 252,762 user-generated videos. The findings indicate that: (1) prior experience has a positive effect on creators’ performance; (2) specialized experience across distinct video categories has a nonlinear effect on creators’ performance. These results have implications for improving user engagement for online user-generated video streaming platforms.

Monetization in online streaming platforms: an exploration of inequalities in Twitch.tv

The live streaming platform Twitch underwent in recent years an impressive growth in terms of viewership and content diversity. The platform has been the object of several studies showcasing how streamers monetize their content via a peculiar system centered around para-sociality and community dynamics. Nonetheless, due to scarcity of data, lots is still unknown about the platform-wide relevance of this explanation as well as its effect on inequalities across streamers. In this paper, thanks to the recent availability of data showcasing the top 10,000 streamers revenue between 2019 and 2021, as well as viewership data from different sources, we characterized the popularity and audience monetization dynamics of the platform. Using methods from social physics and econometrics, we analyzed audience building and retention dynamics and linked them to observed inequalities. We found a high level of inequality across the platform, as well as an ability of top streamers to diversify their revenue sources, through audience renewal and diversification in monetization systems. Our results demonstrate that, even if the platform design and affordance favor monetization for smaller creators catering to specific niches, its non-algorithmic design still leaves room for classical choice biases allowing a few streamers to emerge, retain and renew a massive audience.

Building a collaborative, university-based science-in-action video storytelling model that translates science for public engagement and increases scientists' relatability

Collaborating scientists and storytellers successfully built a university-based science-in-action video storytelling model to test the research question: Can university scientists increase their relatability and public engagement through science-in-action video storytelling? Developed over 14 years, this science storytelling model produced more than a dozen high-visibility narratives that translated science to the public and featured scientists, primarily environmental and climate scientists, who are described in audience surveys as relatable people. This collaborative model, based on long-term trusting partnerships between scientists and video storytellers, documented scientists as they conducted their research and together created narratives intended to humanize scientists as authentic people on journeys of discovery. Unlike traditional documentary filmmaking or journalism, the participatory nature of this translational science model involved scientists in the shared making of narratives to ensure the accuracy of the story's science content. Twelve science and research video story products have reached broad audiences through a variety of venues including television and online streaming platforms such as Public Broadcasting Service (PBS), Netflix, PIVOT TV, iTunes, and Kanopy. With a reach of over 180 million potential public audience viewers, we have demonstrated the effectiveness of this model to produce science and environmental narratives that appeal to the public. Results from post-screening surveys with public, high school, and undergraduate audiences showed perceptions of scientists as relatable. Our data includes feedback from undergraduate and high school students who participated in the video storytelling processes and reported increased relatability to both scientists and science. In 2022, we surveyed undergraduate students using a method that differentiated scientists' potential relatable qualities with scientists' passion for their work, and the scientists' motivation to help others, consistently associated with relatability. The value of this model to scientists is offered throughout this paper as two of our authors are biological scientists who were featured in our original science-in-action videos. Additionally, this model provides a time-saving method for scientists to communicate their research. We propose that translational science stories created using this model may provide audiences with opportunities to vicariously experience scientists' day-to-day choices and challenges and thus may evoke audiences' ability to relate to, and trust in, science.

A Meta-learning Based Generative Model with Graph Attention Network for Multi-Modal Recommender Systems

With increased data in various e-commerce domains or in different online streaming platforms like Amazon Prime, Netflix, etc, it has become more challenging to give a personalized recommendation to a user. In terms of the movie recommendation system, different multimodal information such as audio, video, and text are effectively fused together to tackle this problem. However, in real-world scenarios this information may not always be present, leading to the problem of missing modality. Existing works in Recommender Systems (RSs) may fail to recommend effectively if their model is not susceptible to missing modality. In this work, we propose a meta-learning model to deal with the missing modality problem. Our proposed model tries to reconstruct the missing features with the help of the existing modalities and once reconstructed, we pass them to novel trident architecture for solving the recommendation task. We have performed experiments on the newly created multimodal version of the MovieLens dataset. Additionally, we have incorporated a new modality where we extracted subtitles of the movies to increase the effectiveness of our missing modality model.

$\mathsf{HxL3}$: Optimized Delivery Architecture for HTTP Low-Latency Live Streaming

While most of the HTTP adaptive streaming (HAS) traffic continues to be video-on-demand (VoD), more users have started generating and delivering live streams with high quality through popular online streaming platforms. Typically, the video contents are generated by streamers and being watched by large audiences which are geographically distributed far away from the streamers locations. The locations of streamers and audiences create a significant challenge in delivering HAS-based live streams with low latency and high quality. Any problem in the delivery paths will result in a reduced viewer experience. In this paper, we propose HxL3, a novel architecture for low-latency live streaming. HxL3 is agnostic to the protocol and codecs that can work equally with existing HAS-based approaches. By holding the minimum number of live media segments through efficient caching and prefetching policies at the edge, improved transmissions, as well as transcoding capabilities, HxL3 is able to achieve high viewer experiences across the Internet by alleviating rebuffering and substantially reducing initial startup delay and live stream latency. HxL3 can be easily deployed and used. Its performance has been evaluated using real live stream sources and entities that are distributed worldwide. Experimental results show the superiority of the proposed architecture and give good insights into how low latency live streaming is working.