Assessing Influential Users in Live Streaming Social Networks

abstract: Live streaming has risen to significant popularity in the recent past and largely this live streaming is a feature of existing social networks like Facebook, Instagram, and Snapchat. However, there does exist at least one social network entirely devoted to live streaming, and specifically the live streaming of video games, Twitch. This social network is unique for a number of reasons, not least because of its hyper-focus on live content and this uniqueness has challenges for social media researchers. Despite this uniqueness, almost no scientific work has been performed on this public social network. Thus, it is unclear what user interaction features present on other social networks exist on Twitch. Investigating the interactions between users and identifying which, if any, of the common user behaviors on social network exist on Twitch is an important step in understanding how Twitch fits in to the social media ecosystem. For example, there are users that have large followings on Twitch and amass a large number of viewers, but do those users exert influence over the behavior of other user the way that popular users on Twitter do? This task, however, will not be trivial. The same hyper-focus on live content that makes Twitch unique in the social network space invalidates many of the traditional approaches to social network analysis. Thus, new algorithms and techniques must be developed in order to tap this data source. In this thesis, a novel algorithm for finding games whose releases have made a significant impact on the network is described as well as a novel algorithm for detecting and identifying influential players of games. In addition, the Twitch network is described in detail along with the data that was collected in order to power the two previously described algorithms.Dissertation/ThesisDoctoral Dissertation Computer Science 201

LIVE ALIVE The Community Ecology in Livestreaming Platforms

Essa pesquisa explora a ecologia de comunidades presentes na Twitch, a maior plataforma de transmissão ao vivo atualmente, diferenciando os diversos grupos e as ferramentas que proporcionam um maior senso de comunidade entre membros.This research explores the community ecology within Twitch, the biggest livestreaming platform to this date, shedding light on the different types of groups and the features that foster a stronger sense of community between members

SENTIMENT ANALYSIS OF HOW DIFFERENTLY MALE AND FEMALE STREAMERS CHAT ON TWITCH.TV

Video gameplay has traditionally been social, with arcades providing an outlet for public play and consoles, allowing people to play together at home. Onlookers are not limited to being passive spectatorship as they are also provided the opportunity to engage directly with the player, with gameplay live streaming being the newest iteration. Live streaming of video games has become dominated in most countries by the website Twitch.tv, where the challenge concerns highly skilled players with minimal communication and exchange, conversely, prioritizes showmanship over gameplay. This paper focuses on common communication characteristics of viewers who often send single messages and streamers who elaborate. Based on a large real dataset of live stream chats, this paper uses sentiment analysis to explore and compare the findings of different communication theories regarding viewers and how they perceive streamers along the spectrum of different sentiments

Exploring the Emerging Domain of Research on Video Game Live Streaming in Web of Science: State of the Art, Changes and Trends

In recent years, interest in video game live streaming services has increased as a new communication instrument, social network, source of leisure, and entertainment platform for millions of users. The rise in this type of service has been accompanied by an increase in research on these platforms. As an emerging domain of research focused on this novel phenomenon takes shape, it is necessary to delve into its nature and antecedents. The main objective of this research is to provide a comprehensive reference that allows future analyses to be addressed with greater rigor and theoretical depth. In this work, we developed a meta-review of the literature supported by a bibliometric performance and network analysis (BPNA). We used the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) protocol to obtain a representative sample of 111 published documents since 2012 and indexed in the Web of Science. Additionally, we exposed the main research topics developed to date, which allowed us to detect future research challenges and trends. The findings revealed four specializations or subdomains: studies focused on the transmitter or streamer; the receiver or the audience; the channel or platform; and the transmission process. These four specializations add to the accumulated knowledge through the development of six core themes that emerge: motivations, behaviors, monetization of activities, quality of experience, use of social networks and media, and gender issues

Interpersonal Relations and Social Actions on Live Streaming Services. A Systematic Review on Cyber-social Relations

This article provides a systematic review on interpersonal relations and social actions on live streaming services as, for instance, Twitch, Chaturbate, YouNow, or Taobao Live. Are those relations social, parasocial, or is there another specific kind of relation? Based on 77 articles, we give a short bibliometric overview and discuss interactions on live streaming services, social actions of streamers, social actions of viewers, shopping relations on live streaming services, and the streamers’ and viewers’ intentions to continuous actions leading (also supported by elements of gamification) the audience to a kind of stickiness towards individual streams, streamers, and services. Due to highly interactive communication between audience and broadcasters and among the viewers, social actions on live streaming services take a middle position between social and parasocial relations and―concerning shopping―also a middle position between physical event-shopping and ordering on an e-commerce platform. They form a new human-human relation, which we name “cyber-social relation.

PLAYING THE GAME: VIDEO GAMES AND VIDEO GAME STREAMING PLATFORMS AS MARKETING COMMUNICATION CHANNELS

While video games are generally viewed as a form of entertainment for a small subset of people, in reality they provide a channel for nearly 3.2 billion people to interact with others and offer multiple pathways for marketers to interact with consumers. Pair this alongside 140 million unique consumers who consumer nearly 24 billion hours of content on video game streaming platforms (VGSPs), such as Twitch, and there is a deep need for marketers to understand how to engage consumers in these environments. This dissertation provides a conceptualization of the video game ecosystem as well as the types of influencers on VGSPs, while highlighting important marketer-to-consumer interactions that occur through these platforms. In the first essay, I provide a new framework called the video game ecosystem to show how video games can be leveraged as a marketing communication channel and how it differs from other popular channels, such as social media and television. Furthermore, I identify 7 testable propositions from the marketer’s perspective I believe will meaningfully direct the current marketing practice while shaping marketing research’s future including outlining the ways marketers should build and present content through this channel, highlighting marketer-consumer interactions unique to this ecosystem, and showcasing the potential ways firms can leverage the video game ecosystem in their marketing strategies. Finally, in this essay I present 12 future research areas to help kickstart marketing research in this domain. In the second essay, I present a new conceptualization of influencer marketing through VGSPs. Specifically, I highlight how influencer-to-influencer (I2I), influencer-to-consumer (I2C), and consumer-to-consumer (C2C) relationships differ on VGSPs compared to traditional social media platforms, and how these relationships impact consumers downstream. I identify two unique types of influencers on VGSPs (video game streamers and esports athletes) and provide 6 novel propositions regarding the formation of social networks around these influencers. Finally, I provide 8 research areas to help shape the future of consumer research across multiple domains

ONLINE COMMUNITIES: AN EXAMINATION OF ONLINE COMMUNITY-BASED CASE STUDIES

Billions of people access the Internet and the World Wide Web every day. Inside this vast network, individuals interact with one another, whether consciously or unconsciously, sharing thoughts, views, and information at an unfathomable rate. The creation of Online Communi-ties (OCs) is based on this perpetual phenomenon, which happens silently in everyone's life. Without a thorough comprehension of every component triggered by these architectures, which is highlighted across disciplines, definitions, categorizations and classifications, it would be difficult to obtain a profound understanding of OCs. Intercepting such tendency, which is defined by the widespread use of OCs, is becoming a rising priority for businesses and marketers. This topic will be studied through an in-depth examination of selected case studies, which show a wide range of community uses in a variety of disruptive business models. Twitch’s analysis triggers the creation of a specific category, namely community incubator, where professional streamers can monetize their content with a level of interactivity never seen before. Estetista Cinica represents one of the most resonant cases of cultivation, investment and social influence in the OC, to the point of building a business around it. OneDay Group, on the other hand, has built its success thanks to the unique management of its OC, represent-ing their targeted customers, on which communication and marketing are continuously pro-jected. Finally, Meta has been launched with the aim of developing a metaverse, meaning an immersive virtual environment, namely, surreality. This case study suggests the emergence of a fourth classification of disruptive OC-based business models, described as the all-around OCs.Billions of people access the Internet and the World Wide Web every day. Inside this vast network, individuals interact with one another, whether consciously or unconsciously, sharing thoughts, views, and information at an unfathomable rate. The creation of Online Communi-ties (OCs) is based on this perpetual phenomenon, which happens silently in everyone's life. Without a thorough comprehension of every component triggered by these architectures, which is highlighted across disciplines, definitions, categorizations and classifications, it would be difficult to obtain a profound understanding of OCs. Intercepting such tendency, which is defined by the widespread use of OCs, is becoming a rising priority for businesses and marketers. This topic will be studied through an in-depth examination of selected case studies, which show a wide range of community uses in a variety of disruptive business models. Twitch’s analysis triggers the creation of a specific category, namely community incubator, where professional streamers can monetize their content with a level of interactivity never seen before. Estetista Cinica represents one of the most resonant cases of cultivation, investment and social influence in the OC, to the point of building a business around it. OneDay Group, on the other hand, has built its success thanks to the unique management of its OC, represent-ing their targeted customers, on which communication and marketing are continuously pro-jected. Finally, Meta has been launched with the aim of developing a metaverse, meaning an immersive virtual environment, namely, surreality. This case study suggests the emergence of a fourth classification of disruptive OC-based business models, described as the all-around OCs

Near Real Time Data Aggregation for NLP

Com o aumento do uso das redes sociais, o número de opções de rede para usar e a variedade de funcionalidades que elas permitem leva à necessidade de os gestores desportivos prestarem uma atenção especial a estes meios. É seguindo este pensamento que surge o Projeto PLAYOFF e consequentemente esta tese. Foi feito um levantamento da literatura existente de soluções que combinam Apache Kafka com modelos de machine learning e foi possível verificar que, apesar de soluções diferentes, já existem referencias nesses domínios. É apresentada uma comparação entre Apache Kafka e RabbitMQ e as razões da escolha ter recaído para o Kafka. É apresentada de forma geral uma arquitetura de um projeto Kafka e, posteriormente, as diferentes abordagens pensadas e desenvolvidas no âmbito da dissertação, assim como o formato das mensagens trocadas usando este sistema. Uma serie de testes e seus resultados são descritos, de modo a comprovar a sua escolha e utilização. Nestes testes diferentes abordagem de execução paralela (threads e processos) são apresentadas, assim como a forma de obter dados das APIs das redes sociais também possui diferentes abordagens. As alterações que foram realizadas aos modelos originais são descritas e explicadas as razões para essas mudanças e de que forma se enquadram na ferramenta desenvolvida. Foi realizado um teste global e final, designado por “Teste Piloto”, onde em ambiente real, com um evento real foram testados todos os componentes deste projeto, incluindo os sistemas externos desenvolvidos pela MOG Technologies e os componentes desenvolvidos no âmbito desta dissertação. Por fim, é possível comprovar as soluções apresentadas e opções finais escolhidas para o projeto, através dos resultados obtidos nos diferentes testes. É ainda proposto trabalho futuro de continuação do desenvolvido.With the increasing use of social networks, the number of network options to use and the variety of functionalities that they allow leads to the need for sports managers to pay special attention to these media. It is following this thought that the PLAYOFF Project emerges and consequently this thesis. A search of the existing literature on solutions that combine Apache Kafka with machine learning models was carried out and it was possible to verify that, despite different solutions, there are already references in these domains. A comparison between Apache Kafka and RabbitMQ and the reasons for choosing Kafka are presented. A general architecture of a Kafka project is presented, as well as the different approaches thought and developed within the scope of the dissertation, as well as the format of the messages exchanged using this system. A series of tests and their results are described, in order to prove their choice and use. In these tests different parallel execution approaches (threads and processes) are presented, as well as the way of obtaining data from the APIs of social networks also has different approaches. The changes that were made to the original models are described and explained the reasons for these changes and how they fit into the developed tool. A final and global test was carried out, called “Pilot Test”, where in a real environment, with a real event, all the components of this project were tested, including the external systems developed by MOG Technologies and the components developed within the scope of this dissertation. Finally, it is possible to verify the solutions presented and final options chosen for the project, through the results obtained in the different tests. It is also proposed future work of continuation of the developed