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Interaction Design for Data Visualizations

Interaction Design for Data Visualizations | Behavior Research Technology | Scoop.it
Interactive data visualizations are an exciting way to engage and inform large audiences. They enable users to focus on interesting parts and details, to customize the content and even the graphical form, and to explore large amounts of data. At their best, they facilitate a playful experience that is way more engaging than static infographics or videos.

Several ideas and concepts of interaction design for data visualizations are presented in this post, using 11 examples from the web. The overall concepts featured include:

The Basics: Highlighting and Details on Demand Making More Data Accessible: User-driven Content Selection Showing Data in Different Ways: Multiple Coordinated Visualizations Showing Data in Different Ways: User-driven Visual Mapping Changes Integrating Users’ Viewpoints and Opinions

Visit the complete article for numerous links, useful visuals and specific details on how to understand, implement and evaluate interactive design elements used in data visualization design.


Via Lauren Moss
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Hannes's comment, October 2, 2012 2:09 AM
Great article, I really like the idea of interactive information with details on demand. As an interaction designer I always try to balance content management and usability. Here are some interesting examples that made me consider a complete information surface vs a deep level on demand architecture.
JongWon Kim's comment, October 9, 2012 7:39 PM
really beautiful!!
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On Twitter, It’s Beer Before Liquor* » Sociological Images

On Twitter, It’s Beer Before Liquor* » Sociological Images | Behavior Research Technology | Scoop.it
Friday research methods fun. http://t.co/15eHSpAl
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Analysis of Twitter data may provide insight into actual behavior

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The Best Health And Fitness Apps And Gadgets For Your New Year’s Needs | TechCrunch

The Best Health And Fitness Apps And Gadgets For Your New Year’s Needs | TechCrunch | Behavior Research Technology | Scoop.it
The holidays wreak havoc on our bodies, with their mandatory over-indulgence in food as well as family and reminiscences.
ilumivu's insight:

Wearable Tech to Watch in 2013:

 

1. Jawbone Up: The device comes with about a week’s worth of battery life in a single charge, is sleek and relatively unobtrusive, insulated in rubber and is waterproof. It includes a silent alarm that will wake you in the morning at the right time and a buzzer to remind you when it’s time to get up and get moving during the day.


2. Fitbit: It works like a charm, tracking the number of steps one takes each day, the amount of sleep one gets each night (though this is still a bit buggy), is sensitive to movement and offers a look into the number of calories burned each day.


3. Nike + FuelBand: up to this point, it hasn’t been accurate enough to be used in real training and workouts, putting it more in the casual use category as a motivator for workouts and just getting off your butt.


4. Basis: The device is loaded with sensors, which beyond using the accelerometer to measure sleep patterns, include an optical scanner to track blood flow (i.e. heart rate), a perspiration monitor, as well as skin and ambient temperature monitors to measure workout intensity, heat dissipation and so on. On top of that, the company offers a dashboard complete with a host of metrics, which include stuff like calories burned, steps taken, resting heart rate and hours slept and allows users to track their progress and create small, achievable goals to begin establishing healthy habits.


5. Lark: The app and wristband combo now offer one-tap diet tracking, which allows users to tap a button to indicate they’re eating, tracking dietary info, stress and productivity data to help users make more informed decisions about their health.


6. Shine: another elegant-looking activity tracker that isn’t yet available but looks promising.

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The Future of Flu Forecasting

The Future of Flu Forecasting | Behavior Research Technology | Scoop.it
In a few years, your weather forecast may also include a flu warning
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Tapping into Google's data on search terms stongly correlated with the actual spread of the influenza virus and apply statistical modeling to these data researchers at the CDC and Columbia are hoping to provide acurate flu forcasts. 

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New software promises early diagnosis of Alzheimer`s - Zee News

New software promises early diagnosis of Alzheimer`s - Zee News | Behavior Research Technology | Scoop.it
Zee News
New software promises early diagnosis of Alzheimer`s
Zee News
The support system and imaging methods were developed by VTT Technical Research Centre in Finland and Imperial College London, `Gizmag` reported.
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How The CDC Is Using Big Data To Save You From The Flu

How The CDC Is Using Big Data To Save You From The Flu | Behavior Research Technology | Scoop.it
Here's how they know the flu shot will protect you.
ilumivu's insight:

How are you saving the world from the flu using technology?

 

The data I use is the data contained in FluView. None of it comes from Google. There are basically eight different sources of data that go into FluView every week. It includes about 3,000 primary care providers across the country who report every week how many patients they saw that had Influenza-like illness. That gives us information on the proportion of people going to the doctor with flu-like illness.


How many entries a week do you get?

LB: More than 700,000 patient encounters per week. But then you pair that up with other data sources, like our ViralLogic Lab data. That's the U.S. World Health Organization collaborating lab system. It's about 85 labs.

[Doctors] can take samples from a subset of their patients, send them off to their state public health lab who will do testing for flu. All the results from the state public health lab come to the ViralLogic Lab.

The majority of labs are reporting to us electronically. When the test results are final, it goes to a folder on their system and then it transfers it over here to the CDC. It's very timely. It's a fabulous reporting system. We then report out on a weekly basis. We could analyze that and report daily, but weekly is really fine.


What types of things do you learn with all of this data?

LB: We learn where flu is and in what relative proportion [to the general population], what age groups are getting flu. We do what's called "antigenic characterization" [of flu strains that made people sick] to see how close they look to the strains used in the vaccine. We do anti-viral resistance testing to make sure the strains are still sensitive to the drugs for flu and we do genetic sequencing on some of them.

We get rates of hospitalizations from lab-confirmed flu to see how much severe disease there is. We have another system that tracks pneumonia and influenza deaths so we can see on the whole population if flu activity is causing more deaths than you would expect for this time of year.

We try and cover the spectrum of where people would come into the healthcare system from flu. We can't cover people not going to the doctor.

Things like Google Flu trends is where you get that type of data.

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The Social Business of Fighting Disease

The Social Business of Fighting Disease | Behavior Research Technology | Scoop.it

Whilst social media tools have primarily been used for commercial ends, there is a growing stream of evidence showing that it has scientific and social benefits as well. Nowhere is this more so than in the tracking and prevention of diseases.

 

For instance Google Flu Trends tracks search queries and applies its trending algorithm to gain an understanding of where flu outbreaks are occuring. A 21 month study by John Hopkins University found that the app was exceptionally good at predicting when hospitals would start to see people coming in with flu symptoms.

 

Primary investigator of the study, Dr. Richard Rothman, said that the results were promising for “eventually developing a standard regional or national early warning system for frontline health care workers.”

 

Social media context

 

It could be argued however that social media is a better method of tracking the spread of infection because it provides you with better context. Back in January the American Journal of Tropical Medicine and Hygiene reported that tweets and other public ‘status updates’ were a better way of determining the spread of cholera in post-earthquake Haiti than official channels. The research was conducted by scientists at Children’s Hospital Boston and Harvard Medical School and with over 6,000 people having died from the disease in Haiti, it has serious implications in terms of disaster prevention.

 

“When we analyzed news and Twitter feeds from the early days of the epidemic in 2010, we found they could be mined for valuable information on the cholera outbreak that was available up to two weeks ahead of surveillance reports issued by the government health ministry,” said Rumi Chunara, PhD, of the Informatics Program at Children’s Hospital Boston, Research Fellow at Harvard Medical School, and the lead author of the study. “The techniques we employed eventually could be used around the world as an affordable and efficient way to quickly detect the onset of an epidemic and then intervene with such things as vaccines and antibiotics.”


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Luca M. Sergio's curator insight, December 20, 2012 7:26 AM
so much potential from the social space to identify disease trends and act at an early stage ....
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Can an app improve asthma control ?

Can an app improve asthma control ? | Behavior Research Technology | Scoop.it

The prevalence of asthma is on the rise in nearly every demographic category. The CDC estimates that in the United States, 8% of the population and 10% of children are currently suffering from asthma at an expense of nearly 60 billion dollars annually.

 

Smartphone based technology has emerged as a promising tool for providing such education as well as facilitating behavioral change and promoting healthy choices. CHESS (Comprehensive Health Enhancement Support System) applications are extensively investigated eHealth systems designed to provide information, support, and decision making tools for individuals.

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Using social networking technologies for mixed methods HIV prevention research

Using social networking technologies for mixed methods HIV prevention research | Behavior Research Technology | Scoop.it

Background: Rapid growth in social networking usage, especially among at-risk populations, enables these technologies to be used as tools for mixed (qualitative and quantitative) methods HIV prevention research. We seek to analyze quantitative and qualitative data from a study-recruited social networking group to determine 1) participants willingness to use social networking technologies for HIV prevention research, 2) the topics and content discussed on social networking groups, and 3) the relationship between online discussions about HIV-related behaviors and actual HIV behavior change, among men who have sex with men (MSM).

 

Methods: Participants, primarily African American and Latino, were invited to join a “secret” Facebook group where participation was voluntary. Peer leaders, trained in HIV prevention, posted HIV-related content. Participant public group conversations were qualitatively and thematically analyzed. Multivariate quantitative methods tested associations between qualitative data, participants’ demographic information, and likelihood of requesting a home-based HIV testing kit.

 

Results: Latino and African-American participants (N=57) voluntarily used Facebook to discuss the following HIV-related topics (N=485 conversations): Prevention and Testing; Stigma; Knowledge; and Advocacy. Older participants more frequently discussed Prevention and Testing, Stigma, and Advocacy, and younger participants more frequently engaged in HIV Knowledge-related discussions. The proportion of messages related to Prevention and Testing and HIV Stigma increased during the course of the study. Results showed that participants posting about HIV Prevention and Testing (compared to those who did not) were significantly more likely to request an HIV testing kit (OR 11.14, p = 0.001).

 

Conclusions: Social networking technologies are engaging platforms that can be used for increasing HIV prevention-related conversations behaviors. Data from these technologies can be analyzed used both qualitative and quantitative methods.

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Facebook Is making you miserable, scientists find

Facebook Is making you miserable, scientists find | Behavior Research Technology | Scoop.it
wo separate studies have emerged pointing to the conclusion that for all its popularity, Facebook is actually making people unhappy.

 

The first study, conducted by researchers from New Zealand's University of Canterbury, sought to determine how people felt about the various activities that they spent time on during the day. Researcher Carsten Grimm used a technique known as "experience sampling," sending text messages to people to ask what they were doing and how they ranked the activity in terms of pleasure, engagement, meaningfulness and happiness.

 

Spending time on Facebook ranked among the 10 worst activities in terms of unpleasantness and lack of engagement. It was ranked as the least meaningful activity and the one that made people the second-most unhappy, surpassed only by recovering from illness.

Texting, e-mailing and computer tasks also scored poorly in terms of pleasure and happiness.

 

Although the study did not determine why people felt the way they did about Facebook, prior studies have indicated that many Facebook users become depressed because they view their friends' lives as happier than their own. This may be a side effect of the fact that Facebook users are more likely to post about their happy experiences than their unhappy ones.

 

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Early studies show mobiles can encourage exercise | mobihealthnews

Early studies show mobiles can encourage exercise | mobihealthnews | Behavior Research Technology | Scoop.it

A new meta-analysis of 11 studies shows that mobile device-enabled interventions can help increase people’s physical activity. The study, published in the Journal of Medical Internet Research, is the first meta-analysis of its kind, according to the authors.

 

A total of 1,351 individuals participated in the 11 studies. Three studies reported no effect, but the others all showed a positive effect. It was difficult to pull together aggregate data, Fanning said, because the studies used different metrics for success when it came to increasing physical activity: different studies used self-reported activity, pedometer data, accelerometer data, and metabolic equivalents.

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Increasing Physical Activity With Mobile Devices: A Meta-Analysis

Increasing Physical Activity With Mobile Devices: A Meta-Analysis | Behavior Research Technology | Scoop.it

Background: Regular physical activity has established physical and mental health benefits; however, merely one quarter of the U.S. adult population meets national physical activity recommendations. In an effort to engage individuals who do not meet these guidelines, researchers have utilized popular emerging technologies, including mobile devices (ie, personal digital assistants [PDAs], mobile phones). This study is the first to synthesize current research focused on the use of mobile devices for increasing physical activity.

 

Objective: To conduct a meta-analysis of research utilizing mobile devices to influence physical activity behavior. The aims of this review were to: (1) examine the efficacy of mobile devices in the physical activity setting, (2) explore and discuss implementation of device features across studies, and (3) make recommendations for future intervention development.

 

Methods: We searched electronic databases (PubMed, PsychINFO, SCOPUS) and identified publications through reference lists and requests to experts in the field of mobile health. Studies were included that provided original data and aimed to influence physical activity through dissemination or collection of intervention materials with a mobile device. Data were extracted to calculate effect sizes for individual studies, as were study descriptives. A random effects meta-analysis was conducted using the Comprehensive Meta-Analysis software suite. Study quality was assessed using the quality of execution portion of the Guide to Community Preventative Services data extraction form.

 

Results: Four studies were of “good” quality and seven of “fair” quality. In total, 1351 individuals participated in 11 unique studies from which 18 effects were extracted and synthesized, yielding an overall weight mean effect size of g = 0.54 (95% CI = 0.17 to 0.91, P = .01).

 

Conclusions: Research utilizing mobile devices is gaining in popularity, and this study suggests that this platform is an effective means for influencing physical activity behavior. Our focus must be on the best possible use of these tools to measure and understand behavior. Therefore, theoretically grounded behavior change interventions that recognize and act on the potential of smartphone technology could provide investigators with an effective tool for increasing physical activity.

 

(J Med Internet Res 2012;14(6):e161)
doi:10.2196/jmir.2171

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Pedometers play up every step you take

Pedometers play up every step you take | Behavior Research Technology | Scoop.it

NEW YORK (Reuters) - Pedometers have ticked off many miles since Leonardo da Vinci sketched his version, essentially a pendulum for walkers, in the 15th century.

 

 A summary of 26 different studies showed that pedometer users walked at least 2,000 more steps each day than nonusers, according to the Harvard Health Letter, produced by experts at Harvard Medical School. Also, using a pedometer helped them increase overall physical activity levels by 27 percent.

 

Simply engaging in the self-quantification of the behavior helps encourgae it. 

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Patient-Centered Outcomes Research Institute Issues Call for Applications to Fund Up to $12 Million in Projects to Improve Research Methods | Patient-Centered Outcomes Research Institute

Patient-Centered Outcomes Research Institute Issues Call for Applications to Fund Up to $12 Million in Projects to Improve Research Methods | Patient-Centered Outcomes Research Institute | Behavior Research Technology | Scoop.it

WASHINGTON, D.C. (November 16, 2012) – The Patient-Centered Outcomes Research Institute (PCORI) today released a funding announcement to support research that addresses methodological gaps in patient-centered outcomes research (PCOR).

 

PCORI plans to award $12 million under this funding announcement for up to 14 contracts for studies that will address knowledge gaps and advance the field of comparative clinical effectiveness research.

 

“The nation’s capacity to conduct patient-centered comparative effectiveness research quickly and efficiently remains extremely limited,” said PCORI Executive Director Joe Selby, MD, MPH. “Our goal is to improve this field of research by building data infrastructure, improving analytic methods, and training researchers, patients and other stakeholders to participate in the conduct of research.”

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Sensing as a Service and Big Data

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Internet of Things (IoT) will comprise billions of devices that can sense, communicate, compute and potentially actuate. Data streams coming from these devices will challenge the traditional approaches to data management and contribute to the emerging paradigm of big data. This paper discusses emerging Internet of Things (IoT) architecture, large scale sensor network applications, federating sensor networks, sensor data and related context capturing techniques, challenges in cloud-based management, storing, archiving and processing of sensor data. 

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Bizarre texts could be sign of stroke or other health problems - The Boston Globe

Bizarre texts could be sign of stroke or other health problems - The Boston Globe | Behavior Research Technology | Scoop.it
Speaking gibberish has long been known to be a telltale sign of a stroke, but how about sending nonsensical text messages?
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A Hackathon for Happiness

A Hackathon for Happiness | Behavior Research Technology | Scoop.it
The H(app)athon Project, an initiative to create digital tools to drive global contentment, can help us find ways to improve overall wellness by using the daily information we c...
ilumivu's insight:

"Tools to measure our actions have matured to the point where we can essentially analyze the heartbeat of the planet," Havens said. "But we don't have a common cultural or ethical framework around these technologies, and I see things getting pretty messy and scary if we don't agree on a way to look at things."

 

Havens put together a detailed description of how the H(app)athon Project could create this framework. Then he gathered a committee of approximately 30 experts from various places, including the United Nations, World Economic Forum, MIT, Cambridge University, Microsoft and PEW Internet, to guide the project from there.

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How Eye Tracking Could Revolutionize Interaction Design

How Eye Tracking Could Revolutionize Interaction Design | Behavior Research Technology | Scoop.it
What if you could move a cursor on your TV with just your eyes? Or turn the page of an ebook without using your hands? These are the promises of PredictGaze, what’s basically (and somewhat allegedly) a series of ingenious algorithms by a team of garage engineers. PredictGaze can work with the lousy webcam in your smartphone, tablet, or laptop, and even in low-light conditions, track your eyes and identify your face to enable all sorts of futuristic controls.

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JAMA Network | Archives of Internal Medicine | Integrating Technology Into Standard Weight Loss TreatmentA Randomized Controlled TrialIntegrating Technology Into Obesity Treatment

JAMA Network | Archives of Internal Medicine | Integrating Technology Into Standard Weight Loss TreatmentA Randomized Controlled TrialIntegrating Technology Into Obesity Treatment | Behavior Research Technology | Scoop.it
ilumivu's insight:

Background  A challenge in intensive obesity treatment is making care scalable. Little is known about whether the outcome of physician-directed weight loss treatment can be improved by adding mobile technology.


Methods  We conducted a 2-arm, 12-month study (October 1, 2007, through September 31, 2010). Seventy adults (body mass index >25 and ≤40 [calculated as weight in kilograms divided by height in meters squared]) were randomly assigned either to standard-of-care group treatment alone (standard group) or to the standard and connective mobile technology system (+mobile group). Participants attended biweekly weight loss groups held by the Veterans Affairs outpatient clinic. The +mobile group was provided personal digital assistants to self-monitor diet and physical activity; they also received biweekly coaching calls for 6 months. Weight was measured at baseline and at 3-, 6-, 9-, and 12-month follow-up.


Results  Sixty-nine adults received intervention (mean age, 57.7 years; 85.5% were men). A longitudinal intent-to-treat analysis indicated that the +mobile group lost a mean of 3.9 kg more (representing 3.1% more weight loss relative to the control group; 95% CI, 2.2-5.5 kg) than the standard group at each postbaseline time point. Compared with the standard group, the +mobile group had significantly greater odds of having lost 5% or more of their baseline weight at each postbaseline time point (odds ratio, 6.5; 95% CI, 2.5-18.6).


Conclusions  The addition of a personal digital assistant and telephone coaching can enhance short-term weight loss in combination with an existing system of care. Mobile connective technology holds promise as a scalable mechanism for augmenting the effect of physician-directed weight loss treatment.

 
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Study: text4baby effectively helps new moms with behavior change - FierceMobileHealthcare

Study: text4baby effectively helps new moms with behavior change - FierceMobileHealthcare | Behavior Research Technology | Scoop.it
In the first randomized evaluation of the text4baby mHealth program, a pilot study has found it to be a "promising program" in which "exposure to the text messages was associated with changes in specific beliefs targeted by the messages," according to an article in BMC Public Health. Text4baby is a free mobile information service for pregnant women and new moms designed to promote maternal and child health by sending text messages each week on pregnancy and baby care.

 

In the pilot evaluation study, all participants were pregnant women first presenting for care at the Fairfax County, Virginia Health Department. Randomized participants were enrolled in text4baby and received usual healthcare (intervention), or continued simply to receive usual care (control).

 

For those who had a high school education or greater, the study observed a significantly higher overall agreement to attitudes against alcohol consumption during pregnancy, and also observed a significant improvement of attitudes toward alcohol consumption from baseline to follow-up.

 

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Smartphones might soon develop emotional intelligence

Smartphones might soon develop emotional intelligence | Behavior Research Technology | Scoop.it
New research by a team of engineers at the University of Rochester may soon make that possible.

 

The research has already been used to develop a prototype of an app. The app displays either a happy or sad face after it records and analyzes the user's voice. It was built by one of Heinzelman's graduate students, Na Yang, during a summer internship at Microsoft Research. "The research is still in its early days," Heinzelman added, "but it is easy to envision a more complex app that could use this technology for everything from adjusting the colors displayed on your mobile to playing music fitting to how you're feeling after recording your voice."

 

Previous research has shown that emotion classification systems are highly speaker dependent; they work much better if the system is trained by the same voice it will analyze. "This is not ideal for a situation where you want to be able to just run an experiment on a group of people talking and interacting, like the parents and teenagers we work with," Sturge-Apple explained.


Their new results also confirm this finding. If the speech-based emotion classification is used on a voice different from the one that trained the system, the accuracy dropped from 81 percent to about 30 percent. The researchers are now looking at ways of minimizing this effect, for example, by training the system with a voice in the same age group and of the same gender. As Heinzelman said, "there are still challenges to be resolved if we want to use this system in an environment resembling a real-life situation, but we do know that the algorithm we developed is more effective than previous attempts."

 

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Good Samaritan Index Identifies Web Users Who Help Others Most | MIT Technology Review

Good Samaritan Index Identifies Web Users Who Help Others Most | MIT Technology Review | Behavior Research Technology | Scoop.it
In online discussions, people provide vital emotional support for others. Now computer scientists have created an index that automatically identifies Good Samaritans.
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Earth’s Nervous System: Looking At Humanity Through Big Data

Earth’s Nervous System: Looking At Humanity Through Big Data | Behavior Research Technology | Scoop.it

• Every two days, mankind creates as much information as it did from the dawn of civilization until 2003.• The amount of information that an average person is exposed to in a day is the same as a person from the 15th century was exposed to in his in his lifetime.

 

In his latest book, The Human Face of Big Data, photographer and co-author Rick Smolan looks at what vast amounts of real time data says about us, how it makes our lives better, and scarier.

 

In The Human Face of Big Data, Rick Smolan, a former Time, Life, and National Geographic photographer famous for creating the Day in the Life book series, and author Jennifer Erwitt examine how today’s digital onslaught and emerging technologies can help us better understand and improve the human condition--ourselves, interactions with each other, and the planet.

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Course Videos: Analyzing Big Data with Twitter

Course Videos: Analyzing Big Data with Twitter | Behavior Research Technology | Scoop.it

COURSE VIDEOS: ANALYZING BIG DATA WITH TWITTER


Lecture 1 - Intro to course; Twitter basics

Lecture 2 - Growing a Human-Scale Service & the Twitter Ecosystem

Lecture 3 - Bill Graham: Intro to Hadoop; Hadoop at Twitter

Lecture 4 - Apache Pig at Twitter

Lecture 6 - Trend Detection In Twitter Social Data (Analyzing Big Data With Twitter)

Analyzing Big Data with Twitter: Lecture 7 - Brian Larson on Real Time Twitter Search

Lecture 8 - Analyzing Big Data with Twitter: Splunk for Ad Hoc Exploration of Twitter

Lecture 9 - Analyzing Big Data with Twitter: Twitter's Social Network by Aneesh Sharma

Lecture 10 - Analyzing Big Data with Twitter: GraphLab: Big Learning with Graphs by Joey Gonzalez

Lecture 12 -Analyzing Big Data with Twitter: Recommender Systems by Alpa Jain

Lecture 13 - Analyzing Big Data with Twitter: Kurt Thomas on Security at Twitter and Everywhere

Lecture 14 - Analyzing Big Data with Twitter: Stan Nicolov on Information Diffusion at Twitter

Lecture 15 - Analyzing Big Data with Twitter: Introduction to Scalding by @posco and @argyris

Lecture 16 - Analyzing Big Data with Twitter: Spark by Matei Zaharia

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How Twitter will revolutionise academic research and teaching

How Twitter will revolutionise academic research and teaching | Behavior Research Technology | Scoop.it
Social media is becoming increasingly important in teaching and research work but tutors must remember, it's a conversation not a lecture, says Ernesto Priego...

 

There is still considerable resistance to embracing social media tools for educational purposes, but if you are reading this article you are probably willing to consider their positive effects. New technologies have slow adoption cycles, and often the learning curve is steep.

 

"It's a conversation, not a lecture," is a well-known trope that is useful to remember in the scholarly web. This does not mean we should spend every waking hour chatting to strangers on social networks; it means that social media is not a uni-directional broadcasting tool. Those who "follow" us online are likely to be our students, colleagues, employers. They are not a passive audience.

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Geometrical Psychology: Benjamin Betts’s 19th-Century Mathematical Illustrations of Consciousness

Geometrical Psychology: Benjamin Betts’s 19th-Century Mathematical Illustrations of Consciousness | Behavior Research Technology | Scoop.it

“Imagination receives the stream of Consciousness, and holds apart and compares the different experiences.”

 

“What makes a mathematician is not technical skill or encyclopedic knowledge,” Paul Lockhard recently wrote, “but insatiable curiosity and a desire for simple beauty.” But what if this mathematical curiosity and desire for beauty were applied to questions that have perplexed scientists and philosophers for millennia — questions about consciousness, what it is, how it works, and how it shapes our lives?

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