Media

Along with its interrelated companion volume, The Content, Impact, and Regulation of Streaming Video, this book covers the next generation of TV—streaming online video, with details about its present and a broad perspective on the future. It reviews the new technical elements that are emerging, both in hardware and software, their long-term trend, and the implications. It discusses the emerging ‘media cloud’ of video and infrastructure platforms, and the organizational form of such TV.

The author proposes a topic model tailored to the study of creative documents (e.g., academic papers, movie scripts), which extends Poisson factorization in two ways. First, the creativity literature emphasizes the importance of novelty in creative industries. Accordingly, this article introduces a set of residual topics that represent the portion of each document that is not explained by a combination of common topics. Second, creative documents are typically accompanied by summaries (e.g., abstracts, synopses).

We develop a flexible content-based search model that links the content preferences of search engine users to query search volume and click-through rates, while allowing content preferences to vary systematically based on the context of a search. Content preferences are defined over latent topics that describe the content of search queries and search result descriptions.

Along with its interrelated companion volume, The Technology, Business, and Economics of Streaming Video, this book examines the next generation of TV—online video. It reviews the elements that lead to online platforms and video clouds and analyzes the software and hardware elements of content creation and interaction, and how these elements lead to different styles of video content.

Online and social media campaigns reach billions of people every day. While commercial companies have built up extensive expertise in using these tools to recruit and build relationships with customers, researchers and policymakers have been slower to take full advantage of these new digital tools. The growth of mobile access in developing countries is opening up many opportunities to use social media tools to pursue development objectives: from surveys and impact evaluations to digital delivery of behavior-change campaigns.

Since 1980, economic growth in the U.S. has been fastest in its largest cities. We show that a group of skill- and information-intensive service industries are responsible for all of this new urban bias in recent growth. We then propose a simple explanation centered around the interaction of three factors: the disproportionate reliance of these services on information and communication technology (ICT), the precipitous price decline for ICT capital since 1980, and the preexisting comparative advantage of cities in skilled services.

We analyze methods for selecting topics in news articles to explain stock returns. We find, through empirical and theoretical results, that supervised Latent Dirichlet Allocation (sLDA) implemented through Gibbs sampling in a stochastic EM algorithm will often overfit returns to the detriment of the topic model. We obtain better out-of-sample performance through a random search of plain LDA models. A branching procedure that reinforces effective topic assignments often performs best. We test these methods on an archive of over 90,000 news articles about S&P 500 firms.

"Big data" financial technology raises concerns about market inefficiency. A common concern is that the technology might induce traders to extract others' information, rather than to produce information themselves. We allow agents to choose how much they learn about future asset values or about others' demands, and we explore how improvements in data processing shape these information choices, trading strategies and market outcomes. Our main insight is that unbiased technological change can explain a market-wide shift in data collection and trading strategies.