For storage restriction purposes, audio streaming services often rely on lossy compression formats as files used for playback. In 2018, the audio streaming giant SoundCloud went from using 128 kbps MP3 files to 64 kbps Opus files, and shortly after this was unveiled, music press and users of the service claimed it to be an audio quality impairment. To investigate the reliability in these claims, listening tests using popular songs were performed, having 17 trained listeners assessing perceptual audio quality in 128 kbps MP3 and 64 kbps Opus compared to 44.1 kHz, 24 bit WAV files. When counting scores of all used audio stimuli combined, results showed MP3 outperforming Opus with statistical significance.

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The research conducted focused on the media practices by a South Korean band « BTS » and the named fandom « A.R.M.Y ». Through the use of Twitter, the research consisted in making use of BTS’s Twitter posts to study what they are doing on social media in order to engage fans, as well as the type of practices that are being executed. The second part of the study investigated the fandoms’ interaction, participation, and online engagement in regard to the media content tweeted by the south Korean band. Mix methods were used in order to answer the three research questions that were presented for this research. An analysis of media practices was conducted through a content analysis then followed by an online survey. The analysis highlighted that shared practices and regular media use were an important factor in the creation of a participatory culture. Culture was also shown to be an important component to the generation of fan engagement and artist interaction with their respective fandom. In addition, through fans high participation in online activities, the investigation was able to demonstrate that fans developed shared practices and shared identities, which were emerged from their activities. Furthermore, BTS members have shown that their cultural habits were important for engaging fans. Overall, the results of this study concluded that media practices are various and are executed in ways that allow the South Korean band to keep an online relationship with their fans through diverse media content that is published on their own personal managed Twitter account. In response to that, fans have shown a constant interactions and engagements by liking, retweeting, commenting to the bands’ tweets, along with other different activities that have been demonstrated in the analysis chapter.    Keywords: Social Media, K-pop, Fandom, Digital media practices, Participatory culture, engagement and interaction, Twitter

Pursuing threads of my own activity that are discussed or enacted in texts and their related curatorial and publication projects, I put forward a practice that performs curating in the act of doing it. The thesis lays out a context for this approach to curating against a backdrop of how curatorial theory has been moving the practice towards disciplinarity. Through proposing the adoption of the persona of a curator, facilitating a means to play with the conventions of art, I explore how exhibitions and the institutions in which they are staged my be convened as a different form of public space. This stands as a countermove against the formation of curating as a discipline. In this, curating is displayed as a fundamental aspect of the contemporary aesthetic where narratives, both real and fictive, suffused with the a sense of self in a broader cultural landscape. I touch on a shift where veracity in saying and acting out roles has supplanted concrete truths. As a fundamental player in a globalised culture, the curator, and doing curating, is claimed as potentially emancipatory, albeit fraught with tensions. My own work proves illustrative of how these tensions might be generative by adopting rules or conventions as game-like structures. This offers a unique consideration of what lies between critical and practice-based acts – exhibition-making, critical writing and an element of strategically deployed tom-foolery - in an attempt to avoid simple definition and lay out alternative, speculative positions. I illustrate and narrate these moves in the outcomes of a selected number of projects over the past decade, and lay out how my approach may be transferred into a formal museum setting.

The works presented here constitute an examination of the impact of new media technologies (focusing on social media) on the practice of journalism, with an emphasis on integrating empirical and sociological research. The use of a combination of content analysis, interviews and personal reflections and columns by journalists, case studies and observations, serves to verify and triangulate the evidence. The use of a comprehensive model to examine and analyse media products is a substantial contribution to the field of journalism studies. Previous studies that focused on new media technologies tended to either simply describe these technologies and their potential for change, or to analyse them purely in relationship to older technologies and processes, reducing both forms of practice to a tautological definition: each is that which the other is not. Taking a clear snapshot of the current landscape, and examining it without reference to specific technologies or past practices, the model allows for clear examination of relationships and practices, without being limited by the previous analyses. A number of key themes emerge from research: the tension between the potential of new technologies to expand and improve journalistic practice and output is countered by the fear that the technology will render journalists and their practices redundant. The impact of economic forces is also apparent in the research. The economic structures that underpin journalism were undergoing substantial changes as new media was introduced, and have undergone additional changes as a result of the social and usage changes that technology has wrought. Technology cannot be abstracted from society and economics, and this interrelationship is apparent in the development of the model of the new media ecology which we developed. The work expands on ideas of the first wave of sociological research into the practice of journalism, taking the methods and ideas and applying them to current environments. The iterative development of a model for the new media environments, and its application to empirical and observed research is a key contribution to the field.

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Thesis: S.M., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2016. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 97-103). / Microblogging services, most notably Twitter, have become popular avenues to voice opinions and be active participants of discourse on a wide range of topics. As a consequence, Twitter has become an important part of the political battleground that journalists and political analysts can harness to analyze and understand the narratives that organically form, spread and decline among the public in a political campaign. A challenge with social media is that important discussions around certain issues can be overpowered by majoritarian or controversial topics that provoke strong reactions and attract large audiences. In this thesis we develop a method to identify the specific ideas and sentiments that represent the overall conversation surrounding a topic or event as reflected in collections of tweets. We have developed this method in the context of the 2016 US presidential elections. We present and evaluate a large scale data analytics framework, based on recent advances in deep neural networks, for identifying and analyzing election- related conversation on Twitter on a continuous, longitudinal basis in order to identify representative tweets across prominent election issues. The framework consists of two main components, (1) a dynamic topic model that identifies all tweets related to election issues using knowledge from news stories and continuous learning of Twitter's evolving vocabulary, (2) a semantic model of tweets called Tweet2vec that generates general purpose tweet embeddings used for identifying representative tweets by robust semantic clustering. The topic model performed with an average F-1 score of 0.90 across 22 different election topics on a manually annotated dataset. Tweet2Vec outperformed state-of-the- art algorithms on widely used semantic relatedness and sentiment classification evaluation tasks. To demonstrate the value of the framework, we analyzed tweets leading up to a primary debate and contrasted the automatically identified representative tweets with those that were actually used in the debate. The system was able to identify tweets that represented more semantically diverse conversations around each of the major election issues, in comparison to those that were presented during the debate. This framework may have a broad range of applications, from enabling exemplar-based methods for understanding the gist of large collections of tweets, extensible perhaps to other forms of short text documents, to providing an input for new forms of data-grounded journalism and debate. / by Prashanth Vijayaraghavan. / S.M.

Thesis: S.M., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2018. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 61-69). / The miracle of life is only possible thanks to a wide range of biochemical interactions between assortments of molecular agents. Amidst these agents, which enable all cellular activities, proteins are undoubtedly among the most important groups. Proteins facilitate countless intra- and inter-cellular functions, from regulation of gene expression to immune responses to muscle contraction, but they rarely act in isolation. These are the interactions between proteins, known as protein-protein interactions or PPIs, which sustain the fundamental role of proteins in all living organisms. PPIs are also central to the study of diseases and development of therapeutics. Aberrant human PPIs are the primary cause of many life-threatening conditions, such as Alzheimer, Creutzfeldt-Jakob, and cancer; making the regulation of PPI activities a promising direction for pharmaceutical development. Despite the indisputable importance of PPIs, so far only a tiny fraction of all human PPIs has been discovered, and our current understanding of the core mechanisms and primary functionalities is insufficient. While computational methods in general and machine learning in particular showed encouraging potential to address this challenge, their application in real-life has been limited. To mitigate this gap and make sure computational results perform as well in real-life, we introduce a set of gold-standard machine learning practices called NetPPI. The contributions of this thesis include NetPPI, a minimally-biased, carefully curated dataset of experimentally detected PPIs for training and evaluation of machine learning models; a comprehensive study of protein sequence representations for use with discriminative models; and data splitting methodology for machine learning purposes. We also present the Bilinear PPI model for state-of-the-art PPI prediction. Finally, we propose fundamental biological insight on the nature of PPIs, based on performance analysis of different prediction models. / by Kfir Schreiber. / S.M.

Thesis: S.M., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, September 2016. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 86-89). / Years after the inception of the Radical Atoms vision, significant advances in technology have seen to dynamic tangible interfaces that bridge the biological and micromechanical to enable radical physical interaction with computation. With an increasing multi-modal complexity in such interfaces, this thesis explores a new methodologies and frameworks to designing input/output coincident and physically embodied computers. New types of Shape Changing Interfaces introduce physical perception of material properties to dynamic shape with physically accurate force feedback and introduce Radical Materiality as a way to afford physical interactions with a rendered object. Finally, the Radical Reality Test is proposed as an objective for such interfaces to eventually become indistinguishable from the physical entity or behavior they are computationally and dynamically imitating. / by Luke Vink. / S.M.

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