Author: Cosimo Accoto

“Daily interactions naturally dene social circles. Individuals tend to be friends with the people they spend time with and they choose to spend time with their friends, inextricably entangling physical location and social relationships. As a result, it is possible to predict not only someone’s location from their friends’ locations but also friendship from spatial and temporal co-occurrence. While several models have been developed to separately describe mobility and the evolution of social networks, there is a lack of studies coupling social interactions and mobility. In this work, we introduce a new model that bridges this gap by explicitly considering the feedback of mobility on the formation of social ties. Data coming from three online social networks (Twitter, Gowalla and Brightkite) is used for validation. Our model reproduces various topological and physical properties of these networks such as: i) the size of the connected components, ii) the distance distribution between connected users, iii) the dependence of the reciprocity on the distance, iv) the variation of the social overlap and the clustering with the distance. Besides numerical simulations, a mean-eld approach is also used to study analytically the main statistical features of the networks generated by the model. The robustness of the results to changes in the model parameters is explored, finding that a balance between friend visits and long-range random connections is essential to reproduce the geographical features of the empirical networks” (from “Entangling mobility and interactions in social media”, 2013)

Click to access 1307.5304.pdf

“[…] While we do not argue that deriving measurement concepts from data rather than theory is problematic, per se, researchers should be aware that the most easily available measure may not be the most valid one, and they should discuss to what degree its validity converges with that of established instruments. For example, both communication research and linguistics have a long tradition of content-analytic techniques that are, at least in principle, easily applicable to digital media content.Of course, it is not possible to manually annotate millions of comments, tweets, or blog posts. However, any scholar who analyzes digital media can and should provide evidence for the validity of measures used, especially if they rely on previously unavailable or untested methods. The use of shallow, ‘‘available’’ measures often coincides with an implicit preference for automatic coding instruments over human judgment. There are several explanations for this phenomenon: First, many Big Data analyses are conducted by scholars who have a computer science or engineering background and may simply be unfamiliar with standard social science methods such as content analysis (but some are discussing the benefits of more qualitative manual analyses; Parker et al., 2011). Moreover, these researchers often have easier access to advanced computing machinery than trained research assistants who are traditionally employed as coders or raters […]  (from “The Value of Big Data in Digital Media Research”, by Merja Mahrt  & Michael Scharkow, 2013)

http://www.tandfonline.com/toc/hbem20/57/1#.UfLSd2S9-IU

“Welcome to the engine rooms of the Internet. Filled with rows of sophisticated computing equipment, massive air conditioners and elaborate electrical systems, Data Centers power the Internet, foster productivity, and drive the global economy. They’re also flat out cool—ultramodern technology chambers with peta-flops of processing and megawatts of electrical capacity. I began working in Data Centers more than 15 years ago, first stocking supplies and inventorying hardware, and eventually designing and managing dozens of these specialized computing environments for Cisco. I also visited hundreds of other Data Centers during those years, taking tours and chatting with their designers and managers whenever possible. Data Center folks are all trying to wrestle the same set of physics to the ground, and I’m always curious to see what elegant (or maybe not so elegant) solutions people have implemented. The idea for The Art of the Data Center  originated in 2009 while I was working on a different book, Grow a Greener Data Center . I was writing about geothermal cooling and wanted to provide examples of Data Centers constructed underground and discovered Bahnhof’s co-location facility in Stockholm. Housed in a former nuclear bunker, it was dubbed “The James Bond Villain Data Center” by several technology websites thanks to unique features such as man-made waterfalls and a glass-walled conference room that looms over its data hall. I smiled at the cinematic touches such as dramatic lighting and artificial fog and wished I knew more about it” (from the Preface, The Art of Data Center, 2013)

“According to Altimeter Group research, the average enterprise-class company owns 178 social media accounts, while 13 departments—from marketing to customer support to legal– actively engage in social media. Yet social media— and as a result, social data— are still largely isolated from business-critical enterprise data sourced from platforms such as Customer Relationship Management, Business Intelligence and market research. This lack of a holistic view of social signals in the context of other enterprise and external data can lead to partially-informed decisions, missed opportunity, and increased risk and cost, as the organization makes decisions without the benefit of critical input from external constituencies. In this Altimeter Group research report reflecting input from 35 enterprise-class organizations and technology ecosystem contributors, industry analyst Susan Etlinger lays out an imperative for Social Data Intelligence, identifying key dimensions that organizations must understand, pragmatic steps they can take toward mature integration, and how successful businesses are already using social data in the context of other critical enterprise data to drive measurable value throughout the organization (Altimeter Grouo, July 25 2013)

” […] It’s important to note here, however, that even though brands are finding proven ways to measure the ROI of social endeavors, it is generally agreed that ROI, in some ways, is beside the point. When talking about social business, the discussion refers to building a culture of empowered, engaged social employees who are as confident working collaboratively as they are working independently. Social business, then, is a long-term game plan for corporate sustainability, accountability, and transparency. The benefits of social business grow exponentially—and will continue to be felt for generations to come. Thinking simply in terms of ROI is, quite frankly, far too narrow a view when experiencing nothing short of a cultural revolution […] “from the Social Employee, 2013” (Burgess and Burgess, “The Social Employee”, 2013, p.30)

“I understand the temporality of database aesthetics as a system that may re-present the past, a system that may make the past present again. But not in the sense that is merely reconfigured by a technological process. Here I do not picture the past as an outside to be grasped by the database and organized. Rather I view the database as a process. Importantly, this is a process that not only changes the information that it archives but is also generative of a particular type of presentness in which the information is accessed. This is a process that brings pastness and presentness; a process that does not sit outside or beyond the everyday life, but rather a system that is involved in a process with everyday life; a system that is necessarily temporal” (p. 161-162) in Time and the Digital: Connecting Technology, Aesthetics and a Process Philosophy of Time, by Timothy Scott Barker; 2013, University Press of England)

See in particular, chapter 8 “DATABASES AND TIME”

• Multi-temporality and Frames
• Organizing Temporality
• Events and the Archive
• The Database in Time
• The Database and Temporal Relationships
• Reterritorializing Data
• Databases and the Extension of Occasions

[Abstract] As popular social media have been adopted by corporations for professional sharing and internal communication, ties are strengthened in the network as employee users communicate frequently with each other on work practices. On the other hand, the company hierarchy connects and governs users in a way that shapes the pattern of posting activity, interactions and enacted topics. In this paper, we investigate social ties of employees and information flow in Yammer communication by quantifying the effect of company hierarchy with experiments on a large-scale real dataset…”

http://www-scf.usc.edu/~ketansin/673/CSCI_673_Project_Paper.pdf

http://mitpress.mit.edu/books/aesthesia-networks

Social Business Metrics (inside and outside) according to MIT Sloan Management Review Report (July, 2013, p.22)