Oxford Study: Political Data Mining Companies are Manipulating Elections Around the World

Oxford Study: Political Data Mining Companies are Manipulating Elections Around the World

Privacy issues[ edit ] Widening exposure of member information —12[ edit ] In , the Electronic Frontier Foundation identified two personal information aggregation techniques called “connections” and “instant personalization”. They demonstrated that anyone could get access to information saved to a Facebook profile, even if the information was not intended to be made public. Facebook treats such relationships as public information, and the user’s identity may be displayed on the Facebook page of the product or service. As soon as you visit the sites in the pilot program Yelp, Pandora, and Microsoft Docs the sites can access your name, your picture, your gender, your current location, your list of friends, all the Pages you have Liked—everything Facebook classifies as public information. Even if you opt out of Instant Personalization, there’s still data leakage if your friends use Instant Personalization websites—their activities can give away information about you, unless you block those applications individually. That’s an illustration of how confusing they can be. A visitor to the site copied, published and later removed the code from his web forum, claiming he had been served and threatened with legal notice by Facebook.

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Security applications[ edit ] Many text mining software packages are marketed for security applications , especially monitoring and analysis of online plain text sources such as Internet news , blogs , etc. Biomedical text mining A range of text mining applications in the biomedical literature has been described. Software applications[ edit ] Text mining methods and software is also being researched and developed by major firms, including IBM and Microsoft , to further automate the mining and analysis processes, and by different firms working in the area of search and indexing in general as a way to improve their results.

Feb 12,  · Online dating services, like , constantly sift through their Web listings of personal characteristics, reactions and communications to .

Flag of Vietnam Location map of Vietnam Vietnam , officially the Socialist Republic of Vietnam, is a long streched country along the eastern coast of the Indochinese Peninsula. Vietnam borders China in north, Laos and Cambodia in west. The country shares maritime borders with Indonesia , Malaysia , Philippines , and Thailand. Vietnam has a population of Spoken language is Vietnamese, English is increasingly favored as a second language, and there are still people speak some French. France occupied all of Vietnam by US economic and military aid to South Vietnam grew through the s in an attempt to bolster the government, but US armed forces were withdrawn following a cease-fire agreement in

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Next, as we consider the existing staff structure at Retro, we will need to identify what areas could potentially support data mining. Might also consider what services are available from consultants, and not to get stuck in the details number of personnel, total costs, etc. Jack Holsey and ultimately the executive board is looking for a general overview of staffing options, not a detailed cost breakdown.

It is interesting that no staff details were given, so I guess we need to work with what was provided. I hope this helps and take care.

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Now that I have some bandwidth again, I am getting back to work on several pet projects including the Amazon EC2 Cluster. I’m giving an EC2 talk at Pycon in March, so I’m really on the hook to wrap up that series of posts now. The event which prompted this long overdue blog post was another pet project: I keep an eye on topics of interest using del. The site apparently developed from his work on The Open Library. Over the past year, I’ve been tagging interesting data I find on the web in del.

I wrote a quick python script to pull the relevant links from my del. Most of these datasets are related to machine learning, but there are a lot of government, finance, and search datasets as well. I probably won’t get around to organizing and posting them to the wiki myself, but theinfo community should be able to figure out what to do with them.

The concept reminds me a lot of Jon Udell’s post on public data.

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Text analytics[ edit ] The term text analytics describes a set of linguistic , statistical , and machine learning techniques that model and structure the information content of textual sources for business intelligence , exploratory data analysis , research , or investigation. The term text analytics also describes that application of text analytics to respond to business problems, whether independently or in conjunction with query and analysis of fielded, numerical data.

It is a truism that 80 percent of business-relevant information originates in unstructured form, primarily text. Text analysis processes[ edit ] Subtasks—components of a larger text-analytics effort—typically include:

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The Ancient Art of the Numerati Chapters 1: More on classification 6: Clustering A guide to practical data mining, collective intelligence, and building recommendation systems by Ron Zacharski. It is available as a free download under a Creative Commons license. You are free to share the book, translate it, or remix it. About the book Before you is a tool for learning basic data mining techniques.

Most data mining textbooks focus on providing a theoretical foundation for data mining, and as result, may seem notoriously difficult to understand. This guide follows a learn-by-doing approach. Instead of passively reading the book, I encourage you to work through the exercises and experiment with the Python code I provide.

I hope you will be actively involved in trying out and programming data mining techniques. The textbook is laid out as a series of small steps that build on each other until, by the time you complete the book, you have laid the foundation for understanding data mining techniques. When you click on a chapter title below, you will be taken to a webpage for that chapter. Please let me know if you see an error in the book, if some part of the book is confusing, or if you have some other comment.

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Vatukoula is a low-sulphidation epithermal gold vein deposit associated with alkaline type igneous rocks in a volcanic setting, typical of several other major gold mines in the southwest Pacific region including Grasberg, Porgera and Lihir. Post caldera collapsing a critical genetic feature was the formation of a north-westerly shear system transecting the caldera, with flatly dipping structures within the peripheral basalts resulting from tectonic resettling.

Gold mineralisation is thought to have been set downbetween 3 and 7 million years ago, post-dating magmatism by around , years. As currently understood, the vast majority of the gold at Vatukoula is located within a two square kilometre fractured block, largely in the form of gold in arsenopyrite.

The following script is from “The Data Brokers” which aired on March 9, , and was rebroadcast on Aug. 24, Steve Kroft is the correspondent. Graham Messick and Maria Gavrilovic, producers.

During the U. More than ever before, social media became an arena for disseminating information, often false information, to sway public opinion this way or that way. It was orginally seen and reported as a masterfully orchestrated campaign by strategic players such as Steve Bannon, who used a provocative content and a mixture of truth and false information to bait people into believing things such as Hillary Clinton being involved in a pedophile ring.

Only in , a year after Trump was inaugurated, it became increasingly clear that the manipulation of the social media was not done by individuals or even by political groups and campaigns, but by highly professional companies hired, such as Cambridge Analytica, to design strategies with content of so-called fake news, but also to use complex datamining methods in order to know how to disseminate the information in the most effective way.

The method is now, as we know it, is considered what troll farms do, and the Homeland Security Secretary Kirstjen Nielsen said this week that the social media campaign intended to skew the results of the U. We are facing an urgent, evolving crisis in cyberspace. In fact, I believe that cyber threats collectively now exceed the danger of physical attacks against us.

Without aggressive action to secure our networks, it is only a matter of time before we get hit hard in the homeland. Two years ago, as we all know, a foreign power launched a brazen, multifaceted influence campaign to undermine public faith in our democratic process and to distort our presidential election. Let me be clear:

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There are, however, other predictors that have many more distinct values and can create a much more complex histogram. Consider, for instance, the histogram of ages of the customers in the population. In this case the histogram can be more complex but can also be enlightening. Consider if you found that the histogram of your customer data looked as it does in figure 1.

The Remaking of Reading: Data Mining and the Digital Humanities Matthew G. Kirschenbaum University of Maryland [email protected] Abstract This paper discusses applications of data mining in the.

Buenavista uses state-of-the-art computer monitoring systems at the concentrators, the crushing plant and the flotation circuit in order to coordinate inflows and optimize operations. In the original concentrator, material with a copper grade over 0. The ore is then sent to the ball mills, which grind it to the consistency of fine powder. The finely ground powder is agitated in a water and reagents solution and is then transported to flotation cells.

Air is pumped into the cells producing a froth, which carries the copper mineral to the surface but not the waste rock, or tailings. Concentrates are then shipped by rail to the smelter at La Caridad. In the second concentrator, material with a copper grade over 0. The ore is then sent to a circuit of six ball mills, which grind it to the consistency of fine powder.

Concentrates are then sent by trucks or by railroad to the La Caridad smelter or to the Guaymas port, at Sonora, for exporting. As part of the expansion program for this unit, in we completed the construction of the first molybdenum plant with an annual production capacity of 2, tons of molybdenum contained in concentrate. The molybdenum plant consists of thickeners, homogenizer tanks, flotation cells, column cells and a holo-flite dryer. The second molybdenum plant, is still under construction and we expect to finish this project and initiate operations in All copper ore with a grade lower than the mill cut-off grade of 0.

A cycle of leaching and resting occurs for approximately five years in the run-of-mine dumps and three years for the crushed leach material.

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The National Security Agency has obtained direct access to the systems of Google, Facebook , Apple and other US internet giants, according to a top secret document obtained by the Guardian. The NSA access is part of a previously undisclosed program called Prism , which allows officials to collect material including search history, the content of emails, file transfers and live chats, the document says. The Guardian has verified the authenticity of the document, a slide PowerPoint presentation — classified as top secret with no distribution to foreign allies — which was apparently used to train intelligence operatives on the capabilities of the program.

The document claims “collection directly from the servers” of major US service providers.

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Real-world streaming analytics calls for novel algorithms that run online, and corresponding tools for evaluation. Abstract We are seeing an enormous increase in the availability of streaming, time-series data. Largely driven by the rise of connected real-time data sources, this data presents technical challenges and opportunities. One fundamental capability for streaming analytics is to model each stream in an unsupervised fashion and detect unusual, anomalous behaviors in real-time.

Early anomaly detection is valuable, yet it can be difficult to execute reliably in practice. Application constraints require systems to process data in real-time, not batches. Streaming data inherently exhibits concept drift, favoring algorithms that learn continuously. Furthermore, the massive number of independent streams in practice requires that anomaly detectors be fully automated. In this paper we propose a novel anomaly detection algorithm that meets these constraints.

We also present results using the Numenta Anomaly Benchmark NAB , a benchmark containing real-world data streams with labeled anomalies. The benchmark, the first of its kind, provides a controlled open-source environment for testing anomaly detection algorithms on streaming data.

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Busy with full-time work? DSU was originally founded in as the first teacher training institution in the Dakota Territory. DSU is a small school, with a student body of 3, , and the student to faculty ratio is relatively low at 18 to 1. Students across all disciplines at DSU use iPads and laptops in the classroom, and all students are required to take introductory courses in computer literacy and programming.

Data Mining: Practical Machine Learning Tools and Techniques, Fourth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining highly anticipated fourth edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know .

The rare form of machine learning that can spot hackers who have already broken in This revealed a remarkable regularity. Zipf found that the frequency of a word is inversely proportional to its place in the rankings. So a word that is second in the ranking appears half as often as the most common word. The third-ranked word appears one-third as often and so on.

Indeed, about words account for half of all word appearances. So a few words appear often, while most hardly ever appear. There is a problem, though. Linguists do not all agree that the statistical distribution of word frequency is the result of cognitive processes. Instead, some say the distribution is the result of statistical errors associated with low-frequency words, which can produce similar distributions.

Such a large-scale study would be more statistically powerful and so able to tease these possibilities apart. Today, we get just such a study thanks to the work of Shuiyuan Yu and colleagues at the Communication University of China in Beijing. Yu and co say the word frequencies in these languages share a common structure that differs from the one that statistical errors would produce.

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