Social media analytics: a survey of techniques, tools and platforms

This paper is written for (social science) researchers seeking to analyze the wealth of social media now available. It presents a comprehensive review of software tools for social networking media, wikis, really simple syndication feeds, blogs, newsgroups, chat and news feeds. For completeness, it also includes introductions to social media scraping, storage, data cleaning and sentiment analysis. Although principally a review, the paper also provides a methodology and a critique of social media tools. Analyzing social media, in particular Twitter feeds for sentiment analysis, has become a major research and business activity due to the availability of web-based application programming interfaces (APIs) provided by Twitter, Facebook and News services. This has led to an ‘explosion’ of data services, software tools for scraping and analysis and social media analytics platforms. It is also a research area undergoing rapid change and evolution due to commercial pressures and the potential for using social media data for computational (social science) research. Using a simple taxonomy, this paper provides a review of leading software tools and how to use them to scrape, cleanse and analyze the spectrum of social media. In addition, it discussed the requirement of an experimental computational environment for social media research and presents as an illustration the system architecture of a social media (analytics) platform built by University College London. The principal contribution of this paper is to provide an overview (including code fragments) for scientists seeking to utilize social media scraping and analytics either in their research or business. The data retrieval techniques that are presented in this paper are valid at the time of writing this paper (June 2014), but they are subject to change since social media data scraping APIs are rapidly changing

Iowa Public Television’s Planning Targets 2011-2014

Agency Performance Plan, Iowa Public Televisio

Report from GI-Dagstuhl Seminar 16394: Software Performance Engineering in the DevOps World

This report documents the program and the outcomes of GI-Dagstuhl Seminar 16394 "Software Performance Engineering in the DevOps World". The seminar addressed the problem of performance-aware DevOps. Both, DevOps and performance engineering have been growing trends over the past one to two years, in no small part due to the rise in importance of identifying performance anomalies in the operations (Ops) of cloud and big data systems and feeding these back to the development (Dev). However, so far, the research community has treated software engineering, performance engineering, and cloud computing mostly as individual research areas. We aimed to identify cross-community collaboration, and to set the path for long-lasting collaborations towards performance-aware DevOps. The main goal of the seminar was to bring together young researchers (PhD students in a later stage of their PhD, as well as PostDocs or Junior Professors) in the areas of (i) software engineering, (ii) performance engineering, and (iii) cloud computing and big data to present their current research projects, to exchange experience and expertise, to discuss research challenges, and to develop ideas for future collaborations

Using Data in Undergraduate Science Classrooms

Provides pedagogical insight concerning the skill of using data The resource being annotated is: http://www.dlese.org/dds/catalog_DATA-CLASS-000-000-000-007.htm

Firm Assets and Investments in Open Source Software Products

Open source software (OSS) has recently emerged as a new way to organize innovation and product development in the software industry. This paper investigates the factors that explain the investment of profit-oriented firms in OSS products. Drawing on the resource-based theory of the firm, we focus on the role played by pre-OSS firm assets both upstream and downstream, in the software and the hardware dimensions, to explain the rate of product introduction in OSS. Using a self-assembled database of firms that have announced releases of OSS products during the period 1995-2003, we find that the intensity of product introduction can be explained by a strong position in software technology and downstream market presence in hardware. Firms with consolidated market presence in proprietary software and strong technological competences in hardware are more reluctant to shift to the new paradigm. The evidence is stronger for operating systems than for applications. The fear of cannibalization, the crucial role of absorptive capacity, and complementarities between hardware and software are plausible explanations behind our findings.Product Introduction, Open Source Software, Absorptive Capacity

Inclusive Economy Indicators: Framework & Indicator Recommendations

This report provides a summary of our research and recommendations for indicators to measure inclusive economies