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Could Bots and Spam Smother the Twitter?

Could Bots and Spam Smother the Twitter? | Bits 'n Pieces on Big Data R&D | Scoop.it
A University of Texas professor says Twitter still doesn't have a handle on spam, which damages its value to advertisers
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Bits 'n Pieces on Big Data R&D
Information and insight into Big Data R&D
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Massive Data Flow: Understanding the Complex Dynamics of the Web

The Web is perhaps the most complex system that we know. Its massive scale, complex dynamism, open richness, and social character mean that it may be more profitable to study it using tools and concepts appropriate for understanding nervous systems, organisms, ecosystems and society, rather than approaches more traditionally employed to engineer technology. Simultaneously, the scientists trying to understand this wide array of complex natural systems may have much to gain by considering the emergingstudy of the Web.

 

Massive Data Flow: Understanding the Complex Dynamics of the Web
Workshop at the ACM Web Science Conference 2014 (http://www.websci14.org )
10:00 - 18:00, June 23rd, 2014
Indiana University, Bloomington

http://sacral.c.u-tokyo.ac.jp/event/MDF_WebSci/ ;


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Eight (No, Nine!) Problems With Big Data

Eight (No, Nine!) Problems With Big Data | Bits 'n Pieces on Big Data R&D | Scoop.it

It’s a valuable tool for analysis, but don’t believe all the hype.

onur savas's insight:

Opinions and insights on Big Data by Gary Marcus and Ernest Davis. Gary Marcus is a professor of psychology at New York University and an editor of the forthcoming book “The Future of the Brain.” Ernest Davis is a professor of computer science at New York University.

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How Your Tweets Reveal Your Home Location | MIT Technology Review

How Your Tweets Reveal Your Home Location | MIT Technology Review | Bits 'n Pieces on Big Data R&D | Scoop.it
IBM researchers have developed an algorithm that predicts your home location using your last 200 tweets.
onur savas's insight:

The paper: http://arxiv.org/ftp/arxiv/papers/1403/1403.2345.pdf

 

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Yelp Dataset Challenge | Yelp

Yelp Dataset Challenge | Yelp | Bits 'n Pieces on Big Data R&D | Scoop.it

How well can you guess a review's rating from its text alone? Can you take all of the reviews of a business and predict when it will be the most busy, or when the business is open? Can you predict if a business is good for kids? Has Wi-Fi? Has Parking? What makes a review useful, funny, or cool? Can you figure out which business a user is likely to review next? How much of a business's success is really just location, location, location? What businesses deserve their own subcategory (i.e., Szechuan or Hunan versus just "Chinese restaurants"), and can you learn this from the review text? What makes a tip useful? There is a myriad of deep, machine learning questions to tackle with this rich dataset.

onur savas's insight:

Targeted for academic research though. The deadline is Thursday, July 31, 2014.

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Data Mining Reveals How Conspiracy Theories Emerge on Facebook | MIT Technology Review

Data Mining Reveals How Conspiracy Theories Emerge on Facebook | MIT Technology Review | Bits 'n Pieces on Big Data R&D | Scoop.it
Some people are more susceptible to conspiracy theories than others, say computational social scientists who have studied how false ideas jump the “credulity barrier” on Facebook.
onur savas's insight:

The paper "Collective attention in the age of (mis)information" is at http://arxiv.org/abs/1403.3344. A group of scientists from NEU, INRIA and IMT (Italy).

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Facebook Creates Software That Matches Faces Almost as Well as You Do | MIT Technology Review

Facebook Creates Software That Matches Faces Almost as Well as You Do | MIT Technology Review | Bits 'n Pieces on Big Data R&D | Scoop.it
Facebook’s new AI research group reports a major improvement in face-processing software.
onur savas's insight:

Using deep learning. It looks like Google is not the only one investing in deep learning.

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Massive Visualizations at CeBIT Depict The Scale of “Big Data”

Massive Visualizations at CeBIT Depict The Scale of “Big Data” | Bits 'n Pieces on Big Data R&D | Scoop.it

At this year’s CeBIT computer trade fair in Hannover, Germany, the world’s most impressive and eccentric new technology has been on display. But between the pole-dancing droids and the robot moon monkeys, the massive data visualizations on display at the fair’s CODE_n exhibition in Hall 16 have turned heads with their artistry, execution and scale

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Lab41/Dendrite

Lab41/Dendrite | Bits 'n Pieces on Big Data R&D | Scoop.it

It turns out that much of the world, both physical and virtual, can be represented as a graph. Graphs describe things that are linked together such as web pages and human societies. Like many other topics, Web technologies can make these types of powerful mathematical concepts more accessible to everyday users. Dendrite is a Lab41 exploration of ways to analyze, manipulate, version, and share extremely large graphs:

The Web frontend leverages AngularJS to provide a responsive data-driven experience.The UI interacts with a backend instance of the Titan Distributed Graph Database.The backend uses GraphLab, Faunus, and Jung for graph analytics.
onur savas's insight:

For Lab41: https://www.lab41.org/

 

Director Bob Gleichof's talk in DG'13: http://www.youtube.com/watch?v=L4FiVuUckJc

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onur savas's curator insight, March 16, 1:19 PM

Director Bob Gleichof's talk on DG'13: http://www.youtube.com/watch?v=L4FiVuUckJc

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Strata 2014: Joe Hellerstein and Tutti Taygerly, "Big Data Moonshots and Ground Control"

http://strataconf.com/strata2014/public/schedule/detail/33714 f Big Data is the grand challenge of our time, most analytic effort is like ground control: the...
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Streamtools: A Graphical Tool for Working with Streams of Data

Streamtools: A Graphical Tool for Working with Streams of Data | Bits 'n Pieces on Big Data R&D | Scoop.it

We see a moment coming when the collection of endless streams of data is commonplace. As this transition accelerates it is becoming increasingly apparent that our existing toolset for dealing with streams of data is lacking. Over the last 20 years we have invested heavily in tools that deal with tabulated data, from Excel, MySQL, and MATLAB to Hadoop, R, and Python+Numpy. These tools, when faced with a stream of never-ending data, fall short and diminish our creative potential.

In response to this shortfall we have created streamtools—a new, open source project by the New York Times R&D Lab which provides a general purpose, graphical tool for dealing with streams of data. It offers a vocabulary of operations that can be connected together to create live data processing systems without the need for programming or complicated infrastructure. These systems are assembled using a visual interface that affords both immediate understanding and live manipulation of the system

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Why Big Data Isn’t Necessarily Better Data | Observations, Scientific American Blog Network

Why Big Data Isn’t Necessarily Better Data | Observations, Scientific American Blog Network | Bits 'n Pieces on Big Data R&D | Scoop.it
Tech companies—Facebook, Google and IBM, to name a few—are quick to tout the world-changing powers of “big data” gleaned from mobile devices, Web searches, citizen science ...
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Presentations - 2014 NIST Data Science Symposium

Presentations - 2014 NIST Data Science Symposium | Bits 'n Pieces on Big Data R&D | Scoop.it
Presentations for the NIST Data Science Symposium that took place on March 4-5 2014
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The Parable of Google Flu: Traps in Big Data Analysis

The Parable of Google Flu: Traps in Big Data Analysis | Bits 'n Pieces on Big Data R&D | Scoop.it
onur savas's insight:

The paper in PDF is at http://gking.harvard.edu/files/gking/files/0314policyforumff.pdf.

 

 

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The Data Mining Techniques That Reveal Our Planet's Cultural Links and Boundaries | MIT Technology Review

The Data Mining Techniques That Reveal Our Planet's Cultural Links and Boundaries | MIT Technology Review | Bits 'n Pieces on Big Data R&D | Scoop.it
Studying cultural variation around the world has always been expensive, time-consuming work. Which is why the newfound ability to mine the data from location-based social networks is revolutionizing this science.
onur savas's insight:

The paper is available at  http://arxiv.org/abs/1404.1009: You Are What You Eat (and Drink): Identifying Cultural Boundaries By Analyzing Food & Drink Habits In Foursquare

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Scientific method: Statistical errors

Scientific method: Statistical errors | Bits 'n Pieces on Big Data R&D | Scoop.it
P values, the 'gold standard' of statistical validity, are not as reliable as many scientists assume.
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Data Analytics Handbook

Data Analytics Handbook | Bits 'n Pieces on Big Data R&D | Scoop.it

On-the-job experiences in the Big Data Industry with employees from LinkedIn, Facebook, Yelp, Cloudera, and more.

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The Last 20 Inches: Data’s Treacherous Journey from the Screen to the Mind | MIT Technology Review

The Last 20 Inches: Data’s Treacherous Journey from the Screen to the Mind | MIT Technology Review | Bits 'n Pieces on Big Data R&D | Scoop.it
Data is crucial to our lives, but it can be hard to make sense of. That’s what makes these visualization tools potentially transformative.
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DIMACS Workshop 2014

DIMACS Workshop  2014 | Bits 'n Pieces on Big Data R&D | Scoop.it
DIMACS Workshop on Building Communities for Transforming Social Media Research Through New Approaches for Collecting, Analyzing, and Exploring Social Media DataApril 10 - 11, 2014 
DIMACS Center, CoRE Building, Rutgers University
onur savas's insight:

Many interesting papers. For example: Matthew J. Salganik, "Wiki Surveys: Open and Quantifiable Social Data Collection."

Presented under the auspices of the DIMACS Special Focus on Information Sharing and Dynamic Data Analysis.

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Zooniverse - Real Science Online

Zooniverse - Real Science Online | Bits 'n Pieces on Big Data R&D | Scoop.it

The Zooniverse is home to the internet's largest, most popular and most successful citizen science projects. Our current projects are here but plenty more are on the way. If you're new to the Zooniverse, we suggest picking a project and diving in - the same account will get you into all of our projects, and you can keep track of what you've contributed by watching 'My Zooniverse'.

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Making Sense of Data (Course)

Making Sense of Data (Course) | Bits 'n Pieces on Big Data R&D | Scoop.it

This self-paced, online course is intended for anyone who wants to learn more about how to structure, visualize, and manipulate data. This includes student, educators, researchers, journalists, and small business owners.

onur savas's insight:

A short one (March 18-April 4) though covers basics of data science. 

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Analyzing Tweets on Malaysia Flight #MH370

Analyzing Tweets on Malaysia Flight #MH370 | Bits 'n Pieces on Big Data R&D | Scoop.it
My QCRI colleague Dr. Imran is using our AIDR platform (Artificial Intelligence for Disaster Response) to collect & analyze tweets related to Malaysia Flight 370 that went missing several days ...
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The Languages of Twitter Users

The Languages of Twitter Users | Bits 'n Pieces on Big Data R&D | Scoop.it

Twitter styles itself as the “global town square” for public conversations — a place for fans to gossip about an actress falling at the Academy Awards and for critics of Tunisia’s government topublicly decry the death of an opposition leader.

To measure Twitter’s global impact, Gnip, a social data firm, studied the firehose of posts over the years. The above chart tracks tweets from users who selected a primary language in their profiles since the service went live in 2006. Last year, among people who told Twitter they had a preferred language, almost 49 percent of tweets were from users who chose Japanese, Spanish, Portuguese and other languages other than English.

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Who’s More Famous Than Jesus?

Who’s More Famous Than Jesus? | Bits 'n Pieces on Big Data R&D | Scoop.it
And more questions answered by a just-released interactive catalog of fame compiled by a team of researchers at M.I.T.
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Detecting Emotional Contagion in Massive Social Networks

Detecting Emotional Contagion in Massive Social Networks | Bits 'n Pieces on Big Data R&D | Scoop.it

Happiness and other emotions spread between people in direct contact, but it is unclear whether massive online social networks also contribute to this spread. Here, we elaborate a novel method for measuring the contagion of emotional expression. With data from millions of Facebook users, we show that rainfall directly influences the emotional content of their status messages, and it also affects the status messages of friends in other cities who are not experiencing rainfall. For every one person affected directly, rainfall alters the emotional expression of about one to two other people, suggesting that online social networks may magnify the intensity of global emotional synchrony.

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The Bursty Dynamics of the Twitter Information Network

In online social media systems users are not only posting, consuming, and resharing content, but also creating new and destroying existing connections in the underlying social network. While each of these two types of dynamics has individually been studied in the past, much less is known about the connection between the two. How does user information posting and seeking behavior interact with the evolution of the underlying social network structure?
Here, we study ways in which network structure reacts to users posting and sharing content. We examine the complete dynamics of the Twitter information network, where users post and reshare information while they also create and destroy connections. We find that the dynamics of network structure can be characterized by steady rates of change, interrupted by sudden bursts. Information diffusion in the form of cascades of post re-sharing often creates such sudden bursts of new connections, which significantly change users' local network structure. These bursts transform users' networks of followers to become structurally more cohesive as well as more homogenous in terms of follower interests. We also explore the effect of the information content on the dynamics of the network and find evidence that the appearance of new topics and real-world events can lead to significant changes in edge creations and deletions. Lastly, we develop a model that quantifies the dynamics of the network and the occurrence of these bursts as a function of the information spreading through the network. The model can successfully predict which information diffusion events will lead to bursts in network dynamics.

 

The Bursty Dynamics of the Twitter Information Network
Seth A. Myers, Jure Leskovec

http://arxiv.org/abs/1403.2732


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