Facebook of the Planet Science

David Kramer, MSU Hannah Distinguished Professor in Photosynthesis and Bioenergetics, has created the Facebook of plant science. Courtesy of MSU

By building PhotosynQ – a handheld device with sensors and an online data-sharing and analysis platform – a team of Michigan State University researchers is creating the plant-science equivalent of Facebook.

Following the trail blazed by successful social media networks, the team is giving away patentable devices at a nominal fee, building an active global community of plant science enthusiasts and sharing all data collected from around the world.

The goal is to allow even citizen scientists to make research-quality measurements, said David Kramer, MSU Hannah Distinguished Professor in Photosynthesis and Bioenergetics.

“We’ve built a platform that everyone can access through their cell phones,” he said. “We want to create a community that sees a 12-year-old student in China ask a question about a drought-resistant plant. Then we hope that hundreds of people answer, and not only the student in China is able to grow sustainable crops, but also a farmer in Africa could benefit from those insights.”

One component of PhotosynQ is a handheld device that costs about $100, scans plants and collects a handful of key data points. Via a smartphone running Android, the data is transferred from the device to the researcher’s project page on the PhotosynQ platform.

Currently, there are about 20 research projects on the burgeoning network. As new data is collected, community members can observe the projects’ progression.

Projects range from one measuring the robustness and productivity of beans, to another monitoring the efficiency of photosynthesis. Collecting data on how well plants convert sunlight to energy can be derived from satellite images in a very limited way. To improve the data, it’s best to get on-the-ground observations as well. The more handheld devices used in the field to gather the data, the better.

PhotosynQ will enable local scientists, plant breeders and citizens to improve the productivity and security of crops in communities around the world. This low-cost approach of collecting samples from global sites could change how science has traditionally been conducted, said Greg Austic, who is leading the development in the Kramer lab.

“It’s critical that PhotosynQ stays open source,” he said. “We’re changing the model of moving new technology from academia to the world. We’re maximizing the data and building a community rather than maximizing profits.”

If only two people use the network, it’s worthless. If 2 million people join in, it’s priceless. It will be a snapshot of what’s happening in the plant world at this very moment. Successful breeding efforts, rapidly spreading diseases and other trends can be identified quicker, he added.

This nontraditional approach is indicative of Kramer’s unique lab. Soldering irons and circuit boards outnumber plants and petri dishes. Shelves are lined with electronic prototypes. The buzzing hive of nearly 40 students is a blend of biologists, programmers and engineers.

“Many times one of our biology students will come up with an idea and bounces it off some of the other students,” Kramer said. “The computer specialists write a program, and the electronics students build a prototype and a new technique is developed and used – sometimes in a single day.”

His lab is a microcosm of what he hopes he can create on a global scale; empower people with data and easy-to-use scientific instruments, and people will look at their world differently, he said.

Kramer is a professor in the College of Natural Science and the MSU-DOE Plant Research Laboratory. His research is funded in part by MSU AgBioResearch.

Source: MSU

Use Social Media in Study of E-Cigarettes

Five-year grant from the National Institutes of Health will support project that is as much about data-gathering methods as it is about public health. Credit: UA

When Facebook announced in September that it would use all that personal data it collects to roll out a new ad platform to rival Google, privacy advocates groaned and marketers grinned.

But what if all that intelligence could be used to crack open one of today’s most pressing — yet least understood — public health issues?

That’s precisely the vision of the University of Arizona’s Daniel Zeng, MIS professor at the Eller College of Management, and Scott Leischow, adjunct faculty in the UA College of Medicine and professor of health services research at Arizona’s Mayo Clinic.

Fusing cutting-edge informatics and public health, their plan to scrape social media to create the world’s best data on e-cigarette usage and marketing recently won a five-year, $2.7 million grant from the National Institutes of Health.

The project will tackle four distinct goals. It will:

Create a massive, real-time and continuously growing data set of what consumers and marketers say about e-cigarettes on sites such as Facebook and Twitter, as well as social media forums focused on e-cigarettes and "vaping."

Mine that content for insights into why people use e-cigarettes, how they believe they affect their health and whether they help them quit smoking.

Document the marketing landscape — all the ways brands and vendors use these channels to promote their products and how consumers respond.

Integrate all of that information in the world’s first one-stop resource for wide-ranging data on e-cigarettes as revealed through social media as a tool for other researchers, health care professionals and more.

While e-cigarettes are relatively new in the U.S. — they were introduced in 2007 — sales are doubling annually and were expected to reach $1 billion last year. Even so, any time public dollars fund research, two questions naturally arise: Why study this? And why study it this way?

"There’s so much we don’t know about e-cigarettes," Leischow says. "The scientific community has found mixed data on whether they’re helpful for smoking cessation. We have questions about how different flavorings impact use, particularly among minors. And many health professionals worry that e-cigarettes may ultimately lead to more young people taking up smoking. All of these blind spots around a product that is still totally unregulated make this a top-priority area for the FDA."

As for why it makes sense to study e-cigarettes in this way, Zeng’s MIS expertise holds the key.  By mining social media in real time, as Zeng and Leischow have proposed, there are a number of strategic advantages:

Data comes from people interacting naturally in their day-to-day lives, thus removing “presentation bias” problems intrinsic in surveys.

The data collection is automated, which means sample size is not constrained by how much money or how many eyeball hours researchers can muster.

The lack of constraint also makes anecdotal information scientifically relevant: One personal story is just that, but 10,000 or 100,000 personal stories over time equal robust statistical data.

Because content is processed by algorithms, not people, data is available in near real time, not months or even years after countless hours of labor-intensive review.

The world of e-cigarettes, like that of any niche product or interest, has its own specialized vocabulary of acronyms and slang, so the research team will first need to construct a base lexical dataset for “training” the computers that will collect and process content.

It’s also one thing to scrape words but a much more complex challenge to automate the process of extracting meaning, so that a computer can spot when someone cites a reason for using e-cigarettes or mentions how the products affect his or her health (both of which first require a computer to detect who is or isn’t a user) or correctly catalog the marketing strategy used in an advertisement.

"We basically will be creating a suite of novel technologies for this study using both established building blocks of informatics and methods that have yet to be developed," Zeng says, "including analysis and visualization tools that were developed here at the U of A. 
Beyond that, we’re relying on proven tools for pattern mining, group behavior prediction, social network analysis and a lot more, but in ways that have never been combined for this level of research and in this topic area."

For Leischow, the knowledge those tools will produce is invaluable.

"There are all kinds of messages out there, from how effective e-cigarettes can be to help smokers quit tobacco to how they’re totally harmless or taste like candy," he says. "It may be that e-cigarettes prove beneficial to public health, or they may be shown to do more harm than good. In either case, it often takes many years for experts to fully recognize how products are being used and how they impact well-being, and even longer for regulation to catch up.

"This time, it’s going to be different. This time, we’re getting out ahead."

Source: UA

A Facebook application knows if you are having a bad day and tells your teacher

Spanish scientists create algorithms to measure sentiment on social networks Computer languages and systems researchers at the Autonomous University of Madrid have developed an application called SentBuk, which is capable of deducing the emotional states of Facebook users by analysing their messages using algorithms. The authors believe that this tool could be useful to online educators, as it would furnish them with similar information to that obtained by in-person teachers when they look at their students’ faces.

Computer languages and systems researchers at the Autonomous University of Madrid have developed an application called SentBuk, which is capable of deducing the emotional states of Facebook users by analysing their messages using algorithms. The authors believe that this tool could be useful to online educators, as it would furnish them with similar information to that obtained by in-person teachers when they look at their students' faces.

Information from social networks is becoming a goldmine for marketing and advertising companies. Now, a team of computer languages and systems researchers at the Autonomous University of Madrid (UAM) has also spotted great potential for analysing the emotions transmitted by users in the most popular of these networks: Facebook.

As Álvaro Ortigosa, Director of the UAM's National Centre of Excellence in Cybersecurity, explains, he and his team have developed an application called SentBuk, which is capable of automatically deducing the emotional states of Facebook users by analysing their messages on the social network using algorithms. The results of the study have been published in the journal Computers in Human Behavior.

"SentBuk is an application external to Facebook which, with the user's permission, analyses the messages he/she publishes and calculates his/her emotional state. The tool is based on two algorithms: the first calculates the emotional load of each message and classifies it as positive, negative or neutral. The second deduces emotional state by comparing it with the emotional load of recent messages."

The tool -Ortigosa continues- "utilises a natural language analysis technique to recognise significant words with emotional load. It also uses an automatic, machine-learning-type classification system. Based on a large bank of sentences classified by humans, the application has been trained to learn to reproduce human judgment. The emotional load assigned to each sentence arises from a combination of both calculations."

Adaptive e-learning

The UAM scientists believe that this application could be used in adaptive online education, i.e. education that attempts to suggest tasks to the student at the most appropriate time.

"The information obtained via SentBuk, with the approval of the user," Ortigosa insists, "will be able to be used to avoid recommending especially complex pieces of work at times when it detects that the student is in a negative state of mind or one that is less positive than usual."

In these situations, by contrast, "activities with less pedagogical content but designed to motivate students could be assigned."

In his opinion, analysing the general trend of a group of students during internet courses "may afford the teacher similar feedback to that obtained by looking at students' faces in an in-person class -- information it is not normally possible to get online."

Field tests

Ortigosa and the study's co-authors have performed tests with SentBuk and have included the information on students' emotional states in an e-learning system.

According to the expert, in its most basic form, the application alerts professors when it detects that a significant number of students are in a negative frame of mind. "These messages are analysed in context. Although there may be many reasons for the emotional state, the hypothesis is that these negative emotions should be uniformly distributed across time."

On the other hand, he adds, the students of an online course have little to no relation to each other, beyond being classmates in that particular course. For this reason, "if at any given moment a negative emotional peak is detected in a representative sample of the students, it is highly probable that such emotional variation is due to some situation relating to the course, and thus the tool will send a warning message to the teacher."

Other applications

Álvaro Ortigosa says that it is a non-intrusive technique that "enables teachers to have an emotional state thermometer for Facebook users." Once all the necessary permissions for the application have been given, it deduces their emotional state by observing the behaviour in their interaction -- presumably normal and spontaneous -- with the social network.

This information could be used in several contexts. "For example, to complement remote monitoring of those who are ill or to measure user satisfaction. In this area, companies could use the information to alter products or services offered to potential consumers.

The UAM team's research is part of a broader project seeking to infer general characteristics, such as personality and emotional load, of those who use social networking sites like Facebook and Twitter.

Source: Plataforma SINC