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The speed of development in Big Data and associated phenomena, such as social media, has surpassed the capacity of the average consumer to understand his or her actions and their knock-on effects. We are moving towards changes in how ethics has to be perceived: away from individual decisions with specific and knowable outcomes, towards actions by many unaware that they may have taken actions with unintended consequences for anyone. Responses will require a rethinking of ethical choices, the lack thereof and how this will guide scientists, governments, and corporate agencies in handling Big Data. This essay elaborates on the ways Big Data impacts on ethical conceptions.

Unique insights to implement big data analytics and reap big returns to your bottom line Focusing on the business and financial value of big data analytics, respected technology journalist Frank J. Ohlhorst shares his insights on the newly emerging field of big data analytics in Big Data Analytics . This breakthrough book demonstrates the importance of analytics, defines the processes, highlights the tangible and intangible values and discusses how you can turn a business liability into actionable material that can be used to redefine markets, improve profits and identify new business opportunities. Reveals big data analytics as the next wave for businesses looking for competitive advantage Takes an in-depth look at the financial value of big data analytics Offers tools and best practices for working with big data Once the domain of large on-line retailers such as eBay and Amazon, big data is now accessible by businesses of all sizes and across industries. From how to mine the data your company collects, to the data that is available on the outside, Big Data Analytics shows how you can leverage big data into a key component in your business's growth strategy.

The adoption of European norms has led to a high degree of legal and policy convergence. However, national laws remain divergent in many ways, and the assessment of discrepancies is becoming increasingly problematic because of the growing volumes of legislation. So far, comparative law has been the go-to solution for investigating similarities and differences between Member States as a result of harmonization policies. However, the vast complexity of current multilevel governance structures and their policies challenges the usefulness of classical comparative law as a method of investigation for such meta-issues. This article holds that comparative law can be considered Big Data and investigated as such. In other words, more complex and voluminous law and legal interpretations can be either coded into more quantitative observations on the basis of the premises of numerical comparative law, or, alternatively, they can be analysed with the help of new research technologies.

In Debate with Kari Palonen versammelt 48 Essays von Wissenschaftlern und Wissenschaftlerinnen verschiedenster Disziplinen. Sie analysieren Palonens zentrale Argumente und Konzepte und erörtern ihre Wirkung in verschiedensten Subfeldern der Sozial- und Kulturwissenschaften.Im ersten Teil des Buches, Concepts, werden Bezüge zwischen der Conceptual History (Begriffsgeschichte) und Teildisziplinen der Politikwissenschaft sowie anderen Disziplinen erörtert. Im zweiten Teil, Politics, werden zeitgenössische und historische politische Konstellationen, Institutionen, und Prozesse im Lichte der Ideen und Kategorien Palonens diskutiert. Im Zentrum steht hierbei Politik als Aktivität, bzw. das politische Handeln. Der dritte Teil, Histories, beschäftigt sich mit Geschichte im Plural und mit den intellektuellen Beziehungen, in denen Palonen stand und bis heute steht. In Debate with Kari Palonen gibt damit Studierenden wie Wissenschaftler/innen die Möglichkeit, generationenübergreifende intellektuelle Debatten nachzuvollziehen. Der Band ist von zentraler Bedeutung für das zeitgenössische politische Denken.

Refining big data is a new multipurpose way to find, collect, and analyze information obtained from the web and off-line information sources about any research subject. It gives the opportunity to investigate (with an assumed level of statistical significance) the past and current status of information on a subject, and it can even predict the future. The refining of big data makes it possible to quantitatively investigate a wide spectrum of raw information on significant human issues—social, scientific, political, business, and others. Refining creates a space for new, rich sources of information and opens innovative ways for research. The article describes a procedure for refining big data and gives examples of its use.

Chinese social media and big data represent an important share of the global Internet, but have received relatively less attention. This editorial examines three dominant discourses based on China's distinctive and complex political, economic and social realities: "Big Data" (technical focus), "Big Brother" (political focus), and "Big Profit" (economic focus). We argue that the prevailing discourse and practice of big data in China is largely technocentric, decontextualized and nonreflexive, and much less attuned to the social, political, cultural, epistemological, and ethical implications of big data that a humancentric approach would demand. Second, the authoritarian Chinese state poses incredible political challenges to big data research and practice. Third, the practice of Chinese social media and big data is imbued with a discourse of technological nationalism, driven by a handful of monopolistic "national champions." Despite contention, the state and market players have formed a largely mutually beneficial symbiotic relationship to maximize their political and economic gains. We argue a comparative perspective to foster a global conversation on social media and big data is necessary in order to formulate collective responses to such challenges.

Digitalization, Big Data and fantasies in education One may be surprised what digitalization and Big Data are being used for in education. Through digital technologies, Big Data is being gathered to provide access for politicians and the public to school matters in general and specifically if schools and teachers do not reach determined goals. For example, attainment of socioeconomic reference indicators, measured by students' grade point average. Many fantasies are attached to digitalization and Big Data. Fantasies about increased transparency, safety, and prediction (Zuboff, 2019). However, digitalization and Big Data may also produce a culture of 'shaming and blaming', displaying those schools that do not live up to fixed goals. This in turn may lead to goal-fixation, nearsightedness, and 'prophylactic' reasoning in schools. In this paper we analyze the fantasies and powerful beliefs that make it difficult to problematize and critically reflect on the emergence of digitalization and Big Data. Inspired by psychoanalytical theory (Zizek, 2008), political and organizational theory (Ball, 2008; Agamben, 2013; Weick et al. 2005; Gioia & Chittipeddi, 1991), and anthropological studies of the performance of magic in 'primitive' and 'modern' organizations (Malinowski, 1948; Clark and Salaman, 1996), we will discuss examples of fantasies from previous and ongoing research (Rüsselbæk Hansen & Phelan, 2019); Bøje et al., 2018; Balslev & Raae 2019). We argue that delicate balances between monitoring and democracy are tipping. Furthermore, we argue that digitalization and Big Data support and are being supported by a neoliberal fantasy where measurement, clarity, comparison, and competition set the educational scene (Brown, 2015). That way a certain regime is produced which seems to regulate schools, teachers and students in ways that risk dismantling democratic engagement and conversation. This scenario will be illustrated as well as discussed: how can this be avoided so democracy does not turn into another lost ideal in education?

AbstractThe newly established judicial-transparency platforms, like China Judgements Online, have provided access to a new resource—judicial big data—making it possible to conduct empirical, big-data-based legal research. However, as is often the case with new products, these platforms—China Judgements Online, in particular—pose a few problems for big-data-based legal research: insufficient academic depth; immature technical methods; and lack of innovation due to flawed data, strict technical thresholds, and lack of theoretical ambition and ability. In the future, big-data-based legal research should make use of current data resources, continue to promote statistical science and computer science in research, and apply small-data research methods, and in the meanwhile pay attention to the combination of data and theory.