Author: Cosimo Accoto

“[…] For example, you buy things with your credit card, presumably to satisfy needs or desires in your life. Needs, desires: you purchase at your soft points. That visceral act is actually an interaction: you have just participated in a data-mining operation. Your input feeds a marketing analysis apparatus, and that feeds a product development machine. The system eventually gets back to you with new products responding to the input, and with new ways to reach you, massage your rhythms, air out your viscera, induce you to spend. New needs and desires are created. Even whole new modes of experience, which your life begins to revolve around. You have become, you have changed, in interaction with the system. You have literally shopped yourself into being. At the same time, the system has adapted itself . It ’ s a kind of double capture of mutual responsiveness in a reciprocal becoming” (B. Massumi, 48).

 (from Brian Massumi, “Semblance and Event”, The MIT Press, 2012)

“Nowadays companies are starting to realize the importance of using more data in order to  support decision for their strategies. It was said and proved through study cases that “More data usually beats better algorithms”. With this statement companies started to realize that they can chose to invest more in processing larger sets of data rather than investing in expensive algorithms. The large quantity of data  is better used as a whole because of the possible correlations on a larger amount, correlations that can never be found if the data is analyzed on separate sets or on a smaller set. A larger amount of data gives a better output but also working with it can become a challenge due to processing limitations.  This article intends to define the concept of Big Data and stress the importance of Big Data Analytics”

http://www.dbjournal.ro/archive/10/10.pdf

“Since the diffusion of the punched card tabulator following the 1890 U.S. Census, mass-scale information processing has been alternately a site of opportunity, ambivalence and fear in the American imagination. While large bureaucracies have tended to deploy database technology toward purposes of surveillance and control, the rise of personal computing made databases accessible to individuals and small businesses for the first time. Today, the massive collection of trace communication data by public and private institutions has renewed popular anxiety about the role of the database in society. This essay traces the social history of database technology across three periods that represent significant changes in the accessibility and infrastructure of information processing systems. Although many proposed uses of “big data” seem to threaten individual privacy, a largely-forgotten database populism from the 1970s and 1980s suggests that a reclamation of small-scale data processing might lead to sharper popular critique in the future”

“Abstract: In this paper we argue that the new availability of digital data sets allows one to revisit Gabriel Tarde’s (1843-1904) social theory that entirely dispensed with using notions such as individual or society. Our argument is that when it was impossible, cumbersome or simply slow to assemble and to navigate through the masses of information on particular items, it made sense to treat data about social connections by de???ning two levels: one for the element, the other for the aggregates. But once we have the experience of following individuals through their connections (which is often the case with pro???les) it might be more rewarding to begin navigating datasets without making the distinction between the level of individual component and that of aggregated structure. It becomes possible to give some credibility to Tarde’s strange notion of ‘monads’. We claim that it is just this sort of navigational practice that is now made possible by digitally available databases and that such a practice could modify social theory if we could visualize this new type of exploration in a coherent way”

“Before you try to understand what Big Data is, you should know why Big  Data matters to business. In a nutshell, the quest for Big Data is directly attributable to analytics, which has evolved from being a business initiative to a business imperative. In fact, we’d say that analytics has caused a bifurcation of industry participants: some are leaders and some are followers. It’s hard to overlook the impact that analytics has had on organizations during the last decade or so. IBM’s Institute of Business Value, in partnership with MIT’s Sloan Management Review, published the results of a study in a paper called The New Intelligent Enterprise. This paper concluded that organizations that achieve a competitive advantage with analytics are over two times more likely to substantially outperform their industry peers. Think about that for a moment: Analytics (specifically, analytics enriched with Big Data) will help you to outperform your competitors, so if your business is simply curious about Big Data, and your competitors are more than curious—well, you get the point”

http://www.ibmbigdatahub.com/blog/harness-power-big-data-book-excerpt

“This paper is a call to think beyond such limited analyses of the geoweb and the nowpopularized, simplistic visions of big data as an atheoretical solution to understanding the spatial  dimensions of everyday life that are increasing well documented on the geoweb (see Anderson  2008 for the most notable example of this kind of thinking). To think beyond the geoweb, we  suggest a reorientation of geoweb research in five key ways. First, we argue that the study of  geoweb practices should go beyond simple visualizations of content using latitude/longitude  coordinates. Second, we propose that geoweb research promote a perspective beyond the “here and now,” an approach which attends to the significance of spatial relations as they evolve over time. Third, we point to the promise of analysis that is not limited to the explicitly-geographic dimensions of geoweb activity but includes a relational dimension, such as social network analysis. Fourth, we highlight the fact that geoweb content is not produced solely by human users, but is the product of a complex, more-than-human assemblage involving a diversity of actors, including automated content producers like Twitter spam robots. Finally, we highlight the importance of including non-user-generated data, such as governmental or proprietary corporate data sources, as a supplement in geoweb research”

http://www.uky.edu/~tmute2/geography_methods/readingPDFs/2012-Beyond-the-Geot…

“When data mining aims to disclose information about the moral competences and values of individuals or groups – an undertaking we call ‘morality mining’ –, novel ethical problems emerge. These are only partially covered by the current debate on ethical data mining focusing on privacy with respect to discrimination, threats to autonomy, misuse of data, and the consequences of erroneous information. An ethics of morality mining is of particular relevance for research in social science and psychology that increasingly relies on data emerging from social networks, media portals, etc., where people act from or at least in accordance with their own values. In this conceptual contribution, we outline the basic idea of morality mining, explain why we believe that morality mining is associated with novel ethical problems, and suggest ways to address these problems”

http://www.encyclog.com/_upl/files/ChristenAlfanoBangerterLapsley_MoralityMin… 

“Recently, Savage and Burrows (2007) have argued that one way to invigorate sociology’s ‘empirical crisis’ is to take advantage of live, web-based digital transactional data. This paper argues that whilst sociologists do indeed need to engage with this growing digital data deluge, there are longer-term risks involved that need to be considered. More precisely, C. Wright Mills’ ‘sociological imagination’ is used as the basis for the kind of sociological research that one might aim for, even within the digital era. In so doing, it is suggested that current forms of engaging with transactional social data are problematic to the sociological imagination because they tend to be ahistorical and focus mainly on ‘now casting’. The ahistorical nature of this genre of digital research, it is argued, necessarily restricts the possibility of developing a serious sociological imagination. In turn, it is concluded, there is a need to think beyond the digitized surfaces of the plastic present and to consider the impact that time and temporality, particularly within the digital arena, have on shaping our sociological imagination”

http://onlinelibrary.wiley.com/doi/10.1111/j.1467-954X.2012.002120.x/abstract…

“Current science is characterized by the almost exclusive use of data in digital form, with the overwhelming quantities of data referred to as the “data deluge” largely arising due to the deployment of digital tools and, techniques, and computational methods (Hey and Trefethen 2003). We have become used to talking about data in terms of hundreds of terabytes and tens of petabytes, and in all forms of research new ways of storing, retrieving, organizing and processing these huge quantities of data are in constant demand. Some see this as a new paradigm of scientific method: data-driven or data-intensive science which is re-shaping our understanding of what it means to be a scientist and to do scientific research (Hey, Tansley, and Tolle 2009). If this is so, the visual will play a crucial role in this emerging mode of conducting science as visual renderings of all forms mediate and shape scientists’ access to data. There is an irony in this. The huge quantities of digital data and the computing know-how and power to deal with them promise new insights and breakthroughs in science by sheer dint of quantification”

http://spontaneousgenerations.library.utoronto.ca/index.php/SpontaneousGenera…