Social Foraging
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Social Foraging
Dynamics of Social Interaction
Curated by Ashish Umre
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Is the singularity near, or is it already history?

Is the singularity near, or is it already history? | Social Foraging | Scoop.it

In Silicon Valley, there’s no overstating the redemptive potential of technology. Tech can make us happier, wealthier, healthier and luckier. It’s almost like a religion. It should come as no surprise, then, that this religion has its own rapture: the rapture of the geeks known as the singularity. According to this belief system, faster and better machines (a central tenet is Moore’s law) will beget faster, better machines at an exponential rate, and eventually, the machines will become so powerful that they rival human intelligence. Although there are variations, most people who subscribe to the notion of the singularity believe that when it comes, we will upload our consciousness into a computer and live forever. It will be the death of death.

 

The chief evangelist of this vision is futurist Ray Kurzweil. Kurzweil has serious credentials. He invented the text-to-speech synthesiser, among many other devices. The White House selected him to receive a National Medal of Technology, the highest technology honour in the US. He is in the US Patent Office’s National Inventors Hall of Fame.

 

He is also famous for consuming up to 150 vitamin pills a day to slow his body’s ageing, so that he will be around to witness the singularity.

 

The Singularity is Near is a hybrid of documentary and drama, co-directed by Kurzweil, that tries to explain the why and how of its title. Kurzweil’s alter ego, an animated character called Ramona, illustrates the evolutionary arc of thinking machines. She starts out as a primitive, choppy animation but gradually acquires consciousness.

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Using Data to Predict Your Future Health

Have you ever gone on a trip and unexpectedly found yourself in need of medical care? What if your condition could have been predicted? Better yet, what if you already had the medicine needed to treat that condition in your luggage?

 

The Hierarchical Association Rule Model (HARM), which I co-developed with Tyler McCormick of the University of Washington and David Madigan of Columbia University, can help patients be better prepared by warning them (and their doctors) about the conditions they may likely experience next. The predictive modeling tool checks data about an individual patient against other patients in the database with similar situations to help determine future conditions. It also alerts patients about any higher risks they may have for certain types of conditions.

 

For example, a patient or doctor would input the patient's medical history into HARM's interface and HARM would then combine that information with other information in the database to rank likely future medical conditions. It would say something like: patients like you who have experienced X and Y tend to experience Z next. HARM is not just a black box -- it can explain its predictions in simple easy-to-understand terms.

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Processing Rat Brain Neuronal Signals Using A Hadoop Computing Cluster – Part I

In this three-part series of posts, we will share our experiences tackling a scientific computing challenge that may serve as a useful practical example for those readers considering Hadoop and Hive as an option to meet their growing technical and scientific computing needs. This first part describes some of the background behind our application and the advantages of Hadoop that make it an attractive framework in which to implement our solution. Part II dives into the technical details of the data we aimed to analyze and of our solution. Finally, we wrap up this series in Part III with a description of some of our main results, and most importantly perhaps, a list of things we learned along the way, as well as future possibilities for improvements.

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Writing scalable recommender system with Hadoop

Lets say we want to implement a very simple "people you might know" recommender algorithm. Obviously, the speed and scalability of such an algorithm is as important as the actual logic behind the algorithm because such algorithms generally run over a "huge" graph and implementing these normally would probably take a lot of time for recommending friends even for just one user. I will show how to implement a very naive recommender algorithm efficiently. The basic idea of the algorithm is that if person A and person B do not know each other but they have a lot of mutual friends, then the system should recommend that they connect with each other. We will do this is hadoop which is an open source software for highly reliable, scalable distributed computing. The main idea behind it is map and reduce jobs.

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SODEXO: A System Framework for Deployment and Exploitation of Deceptive Honeybots in Social Networks

As social networking sites such as Facebook and Twitter are becoming increasingly popular, a growing number of malicious attacks, such as phishing and malware, are exploiting them. Among these attacks, social botnets have sophisticated infrastructure that leverages compromised users accounts, known as bots, to automate the creation of new social networking accounts for spamming and malware propagation. Traditional defense mechanisms are often passive and reactive to non-zero-day attacks. In this paper, we adopt a proactive approach for enhancing security in social networks by infiltrating botnets with honeybots. We propose an integrated system named SODEXO which can be interfaced with social networking sites for creating deceptive honeybots and leveraging them for gaining information from botnets. We establish a Stackelberg game framework to capture strategic interactions between honeybots and botnets, and use quantitative methods to understand the tradeoffs of honeybots for their deployment and exploitation in social networks. We design a protection and alert system that integrates both microscopic and macroscopic models of honeybots and optimally determines the security strategies for honeybots. We corroborate the proposed mechanism with extensive simulations and comparisons with passive defenses.

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Early Warning Signals for Critical Transitions: A Generalized Modeling Approach

Early Warning Signals for Critical Transitions: A Generalized Modeling Approach | Social Foraging | Scoop.it

Critical transitions are sudden, often irreversible, changes that can occur in a large variety of complex systems; signals that warn of critical transitions are therefore highly desirable. We propose a new method for early warning signals that integrates multiple sources of information and data about the system through the framework of a generalized model. We demonstrate our proposed approach through several examples, including a previously published fisheries model. We regard our method as complementary to existing early warning signals, taking an approach of intermediate complexity between model-free approaches and fully parameterized simulations. One potential advantage of our approach is that, under appropriate conditions, it may reduce the amount of time series data required for a robust early warning signal.

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New computational technique relieves logjam from massive amounts of data

It's relatively easy to collect massive amounts of data on microbes. But the files are so large that it takes days to simply transmit them to other researchers and months to analyze once they are received.

 

Researchers at Michigan State University have developed a new computational technique, featured in the current issue of the Proceedings of the National Academy of Sciences, that relieves the logjam that these "big data" issues create.

 

Microbial communities living in soil or the ocean are quite complicated. Their genomic data is easy enough to collect, but their data sets are so big that they actually overwhelm today's computers. C. Titus Brown, MSU assistant professor in bioinformatics, demonstrates a general technique that can be applied on most microbial communities.

 

The interesting twist is that the team created a solution using small computers, a novel approach considering most bioinformatics research focuses on supercomputers, Brown said.

 

"To thoroughly examine a gram of soil, we need to generate about 50 terabases of genomic sequence -- about 1,000 times more data than generated for the initial human genome project," said Brown, who co-authored on the paper with Jim Tiedje, University Distinguished professor of microbiology and molecular genetics. "That would take about 50 laptops to store that much data. Our paper shows the way to make it work on a much smaller scale."

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Liberal Brains Bigger in Areas of Complexity; Conservative Brains Bigger in Areas of Fear

Liberal Brains Bigger in Areas of Complexity; Conservative Brains Bigger in Areas of Fear | Social Foraging | Scoop.it

This is going to sound sort of obvious, but here we go: A study from University College London published this week in Current Biology has discovered that there are actually differences in the brains of liberals and conservatives. Specifically, liberals' brains tend to be bigger in the area that deals with processing complex ideas and situations, while conservatives' brains are bigger in the area that processes fear.

 

According to the report: "We found that greater liberalism was associated with increased gray matter volume in the anterior cingulate cortex, whereas greater conservatism was associated with increased volume of the right amygdala."

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Artificial Beginnings: Understanding the Origin of Life by Recreating It

Artificial Beginnings: Understanding the Origin of Life by Recreating It | Social Foraging | Scoop.it

The Origin of Life on Earth was certainly, in retrospect, and from the human vantage point, the most fateful event in the history of the Universe. On a young, tepid Earth chemistry sprung into biology and set course on a four billion year journey that would eventually lead to us. However, all traces of the first, primitive organisms have vanished. They were outcompeted and devoured by their evolutionary descendents, leaving nothing to form fossils. Though we will never be able to set eyes on the first Earthlings, the first pioneers, we can understand what they must have been like through more subtle, indirect approaches. Comparative biochemistry across the whole of life takes us back quite a ways, though not to the first cells. The most recent common ancestor shared by all living organisms—bacteria, plants, animals, fungi, archaea, and unicellular eukaryotes like amoebae—was born long after the first cell ceased to exist. The only way we can truly understand what life must have been like in its earliest days is to create it ourselves.

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Evolutionary shift dynamics on a cycle

Evolutionary shift dynamics on a cycle | Social Foraging | Scoop.it

We present a new model of evolutionary dynamics in one-dimensional space. Individuals are arranged on a cycle. When a new offspring is born, another individual dies and the rest shift around the cycle to make room. This rule, which is inspired by spatial evolution in somatic tissue and microbial colonies, has the remarkable property that, in the limit of large population size, evolution acts to maximize the payoff of the whole population. Therefore, social dilemmas, in which some individuals benefit at the expense of others, are resolved. We demonstrate this principle for both discrete and continuous games. We also discuss extensions of our model to other one-dimensional spatial configurations. We conclude that shift dynamics in one dimension is an unusually strong promoter of cooperative behavior.

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8th International Workshop on Uncertainty Reasoning for the Semantic Web (2012 URSW Workshop)

8th International Workshop on Uncertainty Reasoning for the Semantic Web (2012 URSW Workshop) | Social Foraging | Scoop.it

Deadlines:

31 Jul 2012 Paper submissions
21 Aug 2012 Paper acceptance
10 Sep 2012 Camera-ready papers

 

ISWC is a major international forum for presenting visionary research on all aspects of the Semantic Web. The Uncertainty Reasoning Workshop is an exciting opportunity for collaboration and cross-fertilization between the uncertainty reasoning community and the Semantic Web community.

 

Effective methods for reasoning under uncertainty are vital for realizing many aspects of the Semantic Web vision, but the ability of current-generation web technology to handle uncertainty is extremely limited. Recently, there has been a groundswell of demand for uncertainty reasoning technology among Semantic Web researchers and developers.

 

This surge of interest creates a unique opening to bring together two communities with a clear commonality of interest but little history of interaction. By capitalizing on this opportunity, URSW could spark dramatic progress toward realizing the Semantic Web vision.

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Older worker termites become exploding, toxic defenders

Older worker termites become exploding, toxic defenders | Social Foraging | Scoop.it

Many social insects, like ants and termites, do most of their work with their mouths. After enough time spent cutting through foliage and shoring it around, the mouth parts on older animals tend to wear down and lose their sharpness, making them less able to contribute to their nest. Now, researchers have found the way that some older termites can remain useful to their peers: they become suicidal chemical weapons specialists.

 

The authors were working with a species that was already known to have a penchant for a suicidal form of defense. When confronted by a competing species of termites, the animals tend to burst, releasing a sticky substance from their backs. However, the authors noticed that a subset of animals had blue stripes across their backs, and were far more prone to bursting with just a bit of minor prodding from an enemy termite.

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What biological clock? Ovaries continue to produce eggs during adulthood?

What biological clock? Ovaries continue to produce eggs during adulthood? | Social Foraging | Scoop.it

A compelling new genetic study tracing the origins of immature egg cells, or 'oocytes', from the embryonic period throughout adulthood adds new information to a growing controversy. The notion of a "biological clock" in women arises from the fact that oocytes progressively decline in number as females get older, along with a decades-old dogmatic view that oocytes cannot be renewed in mammals after birth.

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Strangers on a bus: Study reveals lengths commuters go to avoid each other

Strangers on a bus: Study reveals lengths commuters go to avoid each other | Social Foraging | Scoop.it

You're on the bus, and one of the only free seats is next to you. How, and why, do you stop another passenger sitting there? New research reveals the tactics commuters use to avoid each other, a practice the paper published in Symbolic Interaction describes as 'nonsocial transient behavior.'

 

The study was carried out by Esther Kim, from Yale University, who chalked up thousands of miles of bus travel to examine the unspoken rules and behaviors of commuters.

 

Over three years Kim took coach trips across the United States. Kim's first trip, between Connecticut and New Mexico, took two days and 17 hours, and this was followed by further adventures from California to Illinois, Colorado to New York, and Texas to Nevada.

"We live in a world of strangers, where life in public spaces feels increasingly anonymous," said Kim. "However, avoiding other people actually requires quite a lot of effort and this is especially true in confined spaces like public transport."

 

Kim found that the greatest unspoken rule of bus travel is that if other seats are available you shouldn't sit next to someone else. As the passengers claimed, "It makes you look weird." When all the rows are filled and more passengers are getting aboard the seated passengers initiate a performance to strategically avoid anyone sitting next to them.

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Writing graphics software gets much easier with Halide

Writing graphics software gets much easier with Halide | Social Foraging | Scoop.it
A new programming language for image-processing algorithms yields code that’s much shorter and clearer — but also faster.

 

Image-processing software is a hot commodity: Just look at Instagram, a company built around image processing that Facebook is trying to buy for a billion dollars. Image processing is also going mobile, as more and more people are sending cellphone photos directly to the Web, without transferring them to a computer first.

 

At the same time, digital-photo files are getting so big that, without a lot of clever software engineering, processing them would take a painfully long time on a desktop computer, let alone a cellphone. Unfortunately, the tricks that engineers use to speed up their image-processing algorithms make their code almost unreadable, and rarely reusable. Adding a new function to an image-processing program, or modifying it to run on a different device, often requires rethinking and revising it from top to bottom.

 

Researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) aim to change that, with a new programming language called Halide. Not only are Halide programs easier to read, write and revise than image-processing programs written in a conventional language, but because Halide automates code-optimization procedures that would ordinarily take hours to perform by hand, they’re also significantly faster.

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Hadoop-MapReduce Market Forecast 2013-2018

Hadoop-MapReduce Market Forecast 2013-2018 | Social Foraging | Scoop.it

Hadoop-MapReduce is taking the Big Data market by storm. It would not be exaggeration to say that today Hadoop-MapReduce is the only cost-sensible and scalable Big Data management alternative to commercially available packages dominating the market. It also becomes an integral part of almost any commercially available Big Data solution and de-facto industry standard for business intelligence (BI). The Hadoop-MapReduce market is forecast to grow at a compound annual growth rate (CAGR) 58% reaching $2.2 billion in 2018.

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Optimizing MapReduce for Highly Distributed Environments

MapReduce, the popular programming paradigm for large-scale data processing, has traditionally been deployed over tightly-coupled clusters where the data is already locally available. The assumption that the data and compute resources are available in a single central location, however, no longer holds for many emerging applications in commercial, scientific and social networking domains, where the data is generated in a geographically distributed manner. Further, the computational resources needed for carrying out the data analysis may be distributed across multiple data centers or community resources such as Grids. In this paper, we develop a modeling framework to capture MapReduce execution in a highly distributed environment comprising distributed data sources and distributed computational resources. This framework is flexible enough to capture several design choices and performance optimizations for MapReduce execution. We propose a model-driven optimization that has two key features: (i) it is end-to-end as opposed to myopic optimizations that may only make locally optimal but globally suboptimal decisions, and (ii) it can control multiple MapReduce phases to achieve low runtime, as opposed to single-phase optimizations that may control only individual phases. Our model results show that our optimization can provide nearly 82% and 64% reduction in execution time over myopic and single-phase optimizations, respectively. We have modified Hadoop to implement our model outputs, and using three different MapReduce applications over an 8-node emulated PlanetLab testbed, we show that our optimized Hadoop execution plan achieves 31-41% reduction in runtime over a vanilla Hadoop execution. Our model-driven optimization also provides several insights into the choice of techniques and execution parameters based on application and platform characteristics.

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Predicting system crashes in nature and society

The world can deliver sudden and nasty shocks. Economies can crash, fisheries can collapse, and climates can pass tipping points. Providing early warning of such changes currently requires the collection of enormous and often prohibitive amounts of data. A new method developed by Steven Lade from the Max-Planck-Institute for the Physics of Complex Systems in Germany and Thilo Gross from the University of Bristol in the UK could change this.

 

In a paper published in the open-access journal PLoS Computational Biology on February 2, the researchers present a mathematical methodology that uses easily obtainable information to greater effect and can therefore reduce the amount of additional data that needs to be collected.

 

The proposed method adds a new twist to an old idea. Predicting the behavior of simple systems is easy. However, systems at risk of severe transitions, such as fisheries and economies, are complex and intricate. To warn of critical transitions, scientists mostly use approaches that require close and continuous monitoring of the system under consideration. The present situation thus presents a fundamental dilemma: predicting transitions without a credible mathematical model requires large amounts of data, but building such a model entails gathering even larger amounts of information.

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Scaling metagenome sequence assembly with probabilistic de Bruijn graphs

Deep sequencing has enabled the investigation of a wide range of environmental microbial ecosystems, but the high memory requirements for de novo assembly of short-read shotgun sequencing data from these complex populations are an increasingly large practical barrier. Here we introduce a memory-efficient graph representation with which we can analyze the k-mer connectivity of metagenomic samples. The graph representation is based on a probabilistic data structure, a Bloom filter, that allows us to efficiently store assembly graphs in as little as 4 bits per k-mer, albeit inexactly. We show that this data structure accurately represents DNA assembly graphs in low memory. We apply this data structure to the problem of partitioning assembly graphs into components as a prelude to assembly, and show that this reduces the overall memory requirements for de novo assembly of metagenomes. On one soil metagenome assembly, this approach achieves a nearly 40-fold decrease in the maximum memory requirements for assembly. This probabilistic graph representation is a significant theoretical advance in storing assembly graphs and also yields immediate leverage on metagenomic assembly.

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Emergent Hierarchical Structures in Multiadaptive Games

We investigate a game-theoretic model of a social system where both the rules of the game and the interaction structure are shaped by the behavior of the agents. We call this type of model, with several types of feedback couplings from the behavior of the agents to their environment, a multiadaptive game. Our model has a complex behavior with several regimes of different dynamic behavior accompanied by different network topological properties. Some of these regimes are characterized by heterogeneous, hierarchical interaction networks, where cooperation and network topology coemerge from the dynamics.

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Scheduling tweets: Does common sense trump algorithms?

Scheduling tweets: Does common sense trump algorithms? | Social Foraging | Scoop.it

Several services offer to schedule your social media updates at times people are most likely to see them. This intrigues many businesses who worry their followers are missing important content.I've tried several of these services. Some social media experts praise them often. Scheduling content for the following day has its benefits when you won't have time to post in real time. But can a website actually provide precise insight on the best times to tweet?

 

People study this like a science, and you can sign up for webinars to learn the secrets. However, many of the experts explaining the benefits of scheduling social media are in the social media industry. Don't they benefit by convincing businesses that social media is not an exercise in randomness?

One service recommended that I tweet at times that most people, if they had to guess, would select anyway. The times were when most people get to work, eat lunch, and start preparing to head home. My wife and business partner, Loren, tried the same service, which provided her times similar to mine. Do our followers behave so similarly?

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From Index Cards to Spatial Data Infrastructures

From Index Cards to Spatial Data Infrastructures | Social Foraging | Scoop.it

Spatial data management is of particular importance to projects related to natural resources, because of their interdisciplinary nature, the large and high amount of datasets and the need for data exchange. Since project members are often distributed between different locations, but their success depends on a consistent and easy exchange of data, central data repositories are often web-based. In this article, we describe the use of GeoNetwork OpenSource for building spatial data infrastructures and report on experiences from practical application.

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Think you're a comic genius? Maybe you're just overconfident

Knock, knock! Who's there? Cows go. Cows go who? No, cows go moo!

 

OK, OK. So it's not a side-slapper -- especially if the teller has zero sense of comic timing. But most likely the person sharing the joke over the water cooler thinks he or she is pretty funny.

 

No matter how badly the joke is told, it will sometimes elicit a few polite laughs.

Why?

 

Because social norms make us averse to providing negative feedback, says Joyce Ehrlinger, a Florida State University assistant professor of psychology whose latest laboratory research recreated everyday interactions in which people might feel pressured to withhold negative information.

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Measuring the Evolution of Contemporary Western Popular Music

Measuring the Evolution of Contemporary Western Popular Music | Social Foraging | Scoop.it

Popular music is a key cultural expression that has captured listeners' attention for ages. Many of the structural regularities underlying musical discourse are yet to be discovered and, accordingly, their historical evolution remains formally unknown. Here we unveil a number of patterns and metrics characterizing the generic usage of primary musical facets such as pitch, timbre, and loudness in contemporary western popular music. Many of these patterns and metrics have been consistently stable for a period of more than fifty years. However, we prove important changes or trends related to the restriction of pitch transitions, the homogenization of the timbral palette, and the growing loudness levels. This suggests that our perception of the new would be rooted on these changing characteristics. Hence, an old tune could perfectly sound novel and fashionable, provided that it consisted of common harmonic progressions, changed the instrumentation, and increased the average loudness.

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Decoding the secrets of balance

Decoding the secrets of balance | Social Foraging | Scoop.it

If you have ever looked over the edge of a cliff and felt dizzy, you understand the challenges faced by people who suffer from symptoms of vestibular dysfunction such as vertigo and dizziness. There are over 70 million of them in North America. For people with vestibular loss, performing basic daily living activities that we take for granted (e.g. dressing, eating, getting in and out of bed, getting around inside as well as outside the home) becomes difficult since even small head movements are accompanied by dizziness and the risk of falling.

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