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Forecasting The Onset And Course Of Mental Illness With Twitter Data, Andrew G. Reece, Andrew J. Reagan, Katharina L.M. Lix, Peter Sheridan Dodds, Christopher M. Danforth, Ellen J. Langer
Forecasting The Onset And Course Of Mental Illness With Twitter Data, Andrew G. Reece, Andrew J. Reagan, Katharina L.M. Lix, Peter Sheridan Dodds, Christopher M. Danforth, Ellen J. Langer
College of Engineering and Mathematical Sciences Faculty Publications
We developed computational models to predict the emergence of depression and Post-Traumatic Stress Disorder in Twitter users. Twitter data and details of depression history were collected from 204 individuals (105 depressed, 99 healthy). We extracted predictive features measuring affect, linguistic style, and context from participant tweets (N = 279,951) and built models using these features with supervised learning algorithms. Resulting models successfully discriminated between depressed and healthy content, and compared favorably to general practitioners' average success rates in diagnosing depression, albeit in a separate population. Results held even when the analysis was restricted to content posted before first depression diagnosis. …
Erratum To: Instagram Photos Reveal Predictive Markers Of Depression (Epj Data Science, (2017), 6, 1, (15), 10.1140/Epjds/S13688-017-0110-Z), Andrew G. Reece, Christopher M. Danforth
Erratum To: Instagram Photos Reveal Predictive Markers Of Depression (Epj Data Science, (2017), 6, 1, (15), 10.1140/Epjds/S13688-017-0110-Z), Andrew G. Reece, Christopher M. Danforth
College of Engineering and Mathematical Sciences Faculty Publications
Upon publication of the original article [1], it was noticed that Figure 2 contained an error. The horizontal bars for the likes row were incorrectly shown as blue. The horizontal bars for the ‘likes’ row should be orange. This has now been acknowledged and corrected in this erratum. The correct Figure 2 is shown below. In the section Method, subsection Improving data quality, the sentence ‘We also excluded participants with CES-D scores of 22 or higher. should read as We also excluded participants with CES-D scores of 21 or lower. This has now been acknowledged and corrected in this erratum. …
Instagram Photos Reveal Predictive Markers Of Depression, Andrew G. Reece, Christopher M. Danforth
Instagram Photos Reveal Predictive Markers Of Depression, Andrew G. Reece, Christopher M. Danforth
College of Engineering and Mathematical Sciences Faculty Publications
Using Instagram data from 166 individuals, we applied machine learning tools to successfully identify markers of depression. Statistical features were computationally extracted from 43,950 participant Instagram photos, using color analysis, metadata components, and algorithmic face detection. Resulting models outperformed general practitioners’ average unassisted diagnostic success rate for depression. These results held even when the analysis was restricted to posts made before depressed individuals were first diagnosed. Human ratings of photo attributes (happy, sad, etc.) were weaker predictors of depression, and were uncorrelated with computationally-generated features. These results suggest new avenues for early screening and detection of mental illness.
Sentiment Analysis Methods For Understanding Large-Scale Texts: A Case For Using Continuum-Scored Words And Word Shift Graphs, Andrew J. Reagan, Christopher M. Danforth, Brian Tivnan, Jake Ryland Williams, Peter Sheridan Dodds
Sentiment Analysis Methods For Understanding Large-Scale Texts: A Case For Using Continuum-Scored Words And Word Shift Graphs, Andrew J. Reagan, Christopher M. Danforth, Brian Tivnan, Jake Ryland Williams, Peter Sheridan Dodds
College of Engineering and Mathematical Sciences Faculty Publications
The emergence and global adoption of social media has rendered possible the real-time estimation of population-scale sentiment, an extraordinary capacity which has profound implications for our understanding of human behavior. Given the growing assortment of sentiment-measuring instruments, it is imperative to understand which aspects of sentiment dictionaries contribute to both their classification accuracy and their ability to provide richer understanding of texts. Here, we perform detailed, quantitative tests and qualitative assessments of 6 dictionary-based methods applied to 4 different corpora, and briefly examine a further 20 methods. We show that while inappropriate for sentences, dictionary-based methods are generally robust in …
Upstream Watershed Condition Predicts Rural Children's Health Across 35 Developing Countries, Diego Herrera, Alicia Ellis, Brendan Fisher, Christopher D. Golden, Kiersten Johnson, Mark Mulligan, Alexander Pfaff, Timothy Treuer, Taylor H. Ricketts
Upstream Watershed Condition Predicts Rural Children's Health Across 35 Developing Countries, Diego Herrera, Alicia Ellis, Brendan Fisher, Christopher D. Golden, Kiersten Johnson, Mark Mulligan, Alexander Pfaff, Timothy Treuer, Taylor H. Ricketts
Rubenstein School of Environment and Natural Resources Faculty Publications
Diarrheal disease (DD) due to contaminated water is a major cause of child mortality globally. Forests and wetlands can provide ecosystem services that help maintain water quality. To understand the connections between land cover and childhood DD, we compiled a database of 293,362 children in 35 countries with information on health, socioeconomic factors, climate, and watershed condition. Using hierarchical models, here we find that higher upstream tree cover is associated with lower probability of DD downstream. This effect is significant for rural households but not for urban households, suggesting differing dependence on watershed conditions. In rural areas, the effect of …
A Multi-Country Assessment Of Factors Related To Smallholder Food Security In Varying Rainfall Conditions, Meredith T. Niles, Molly E. Brown
A Multi-Country Assessment Of Factors Related To Smallholder Food Security In Varying Rainfall Conditions, Meredith T. Niles, Molly E. Brown
College of Agriculture and Life Sciences Faculty Publications
Given that smallholder farmers are frequently food insecure and rely significantly on rain-fed agriculture, it is critical to examine climate variability and food insecurity. We utilize data from smallholder farmer surveys from 12 countries with 30 years of rainfall data to examine how rainfall variability and household resources are correlated with food security. We find that on average, households that experienced a drier than average year are 3.81 months food insecure, while households within a normal range of rainfall were 3.67 months food insecure, and wetter than average households were 2.86 months food insecure. Reduced odds of food insecurity is …
Adults And Children In Low-Income Households That Participate In Cost-Offset Community Supported Agriculture Have High Fruit And Vegetable Consumption, Karla L. Hanson, Jane Kolodinsky, Weiwei Wang, Emily H. Morgan, Stephanie B. Jilcott Pitts, Alice S. Ammerman, Marilyn Sitaker, Rebecca A. Seguin
Adults And Children In Low-Income Households That Participate In Cost-Offset Community Supported Agriculture Have High Fruit And Vegetable Consumption, Karla L. Hanson, Jane Kolodinsky, Weiwei Wang, Emily H. Morgan, Stephanie B. Jilcott Pitts, Alice S. Ammerman, Marilyn Sitaker, Rebecca A. Seguin
College of Agriculture and Life Sciences Faculty Publications
Licensee MDPI, Basel, Switzerland. This paper examines fruit and vegetable intake (FVI) in low-income households that participated in a cost-offset (CO), or 50% subsidized, community-supported agriculture (CSA) program. CSA customers paid farms upfront for a share of the harvest, and received produce weekly throughout the growing season. A cohort of adults and children 2-12 y in a summer CO-CSA were surveyed online twice: August 2015 (n = 41) and February 2016 (n = 23). FVI was measured by the National Cancer Institute’s (NCI) Fruit and Vegetable Screener (FVS) and an inventory of locally grown fruits and vegetables. FVI relative to …
Simon's Fundamental Rich-Get-Richer Model Entails A Dominant First-Mover Advantage, Peter Sheridan Dodds, David Rushing Dewhurst, Fletcher F. Hazlehurst, Colin M. Van Oort, Lewis Mitchell, Andrew J. Reagan, Jake Ryland Williams, Christopher M. Danforth
Simon's Fundamental Rich-Get-Richer Model Entails A Dominant First-Mover Advantage, Peter Sheridan Dodds, David Rushing Dewhurst, Fletcher F. Hazlehurst, Colin M. Van Oort, Lewis Mitchell, Andrew J. Reagan, Jake Ryland Williams, Christopher M. Danforth
College of Engineering and Mathematical Sciences Faculty Publications
Herbert Simon's classic rich-get-richer model is one of the simplest empirically supported mechanisms capable of generating heavy-tail size distributions for complex systems. Simon argued analytically that a population of flavored elements growing by either adding a novel element or randomly replicating an existing one would afford a distribution of group sizes with a power-law tail. Here, we show that, in fact, Simon's model does not produce a simple power-law size distribution as the initial element has a dominant first-mover advantage, and will be overrepresented by a factor proportional to the inverse of the innovation probability. The first group's size discrepancy …
Farm Fresh Foods For Healthy Kids (F3hk): An Innovative Community Supported Agriculture Intervention To Prevent Childhood Obesity In Low-Income Families And Strengthen Local Agricultural Economies, Rebecca A. Seguin, Emily H. Morgan, Karla L. Hanson, Alice S. Ammerman, Stephanie B. Jilcott Pitts, Jane Kolodinsky, Marilyn Sitaker, Florence A. Becot, Leah M. Connor, Jennifer A. Garner, Jared T. Mcguirt
Farm Fresh Foods For Healthy Kids (F3hk): An Innovative Community Supported Agriculture Intervention To Prevent Childhood Obesity In Low-Income Families And Strengthen Local Agricultural Economies, Rebecca A. Seguin, Emily H. Morgan, Karla L. Hanson, Alice S. Ammerman, Stephanie B. Jilcott Pitts, Jane Kolodinsky, Marilyn Sitaker, Florence A. Becot, Leah M. Connor, Jennifer A. Garner, Jared T. Mcguirt
College of Agriculture and Life Sciences Faculty Publications
Background: Childhood obesity persists in the United States and is associated with serious health problems. Higher rates of obesity among children from disadvantaged households may be, in part, attributable to disparities in access to healthy foods such as fruits and vegetables. Community supported agriculture can improve access to and consumption of fresh produce, but the upfront payment structure, logistical barriers, and unfamiliarity with produce items may inhibit participation by low-income families. The aim of this project is to assess the impact of subsidized, or "cost-offset," community supported agriculture participation coupled with tailored nutrition education for low-income families with children. Methods/design: …
Connecting Every Bit Of Knowledge: The Structure Of Wikipedia's First Link Network, Mark Ibrahim, Christopher M. Danforth, Peter Sheridan Dodds
Connecting Every Bit Of Knowledge: The Structure Of Wikipedia's First Link Network, Mark Ibrahim, Christopher M. Danforth, Peter Sheridan Dodds
College of Engineering and Mathematical Sciences Faculty Publications
Apples, porcupines, and the most obscure Bob Dylan song—is every topic a few clicks from Philosophy? Within Wikipedia, the surprising answer is yes: nearly all paths lead to Philosophy. Wikipedia is the largest, most meticulously indexed collection of human knowledge ever amassed. More than information about a topic, Wikipedia is a web of naturally emerging relationships. By following the first link in each article, we algorithmically construct a directed network of all 4.7 million articles: Wikipedia's First Link Network. Here, we study the English edition of Wikipedia's First Link Network for insight into how the many articles on inventions, places, …
The Lexicocalorimeter: Gauging Public Health Through Caloric Input And Output On Social Media, Sharon E. Alajajian, Jake Ryland Williams, Andrew J. Reagan, Stephen C. Alajajian, Morgan R. Frank, Lewis Mitchell, Jacob Lahne, Christopher M. Danforth, Peter Sheridan Dodds
The Lexicocalorimeter: Gauging Public Health Through Caloric Input And Output On Social Media, Sharon E. Alajajian, Jake Ryland Williams, Andrew J. Reagan, Stephen C. Alajajian, Morgan R. Frank, Lewis Mitchell, Jacob Lahne, Christopher M. Danforth, Peter Sheridan Dodds
College of Engineering and Mathematical Sciences Faculty Publications
We propose and develop a Lexicocalorimeter: an online, interactive instrument for measuring the "caloric content" of social media and other large-scale texts. We do so by constructing extensive yet improvable tables of food and activity related phrases, and respectively assigning them with sourced estimates of caloric intake and expenditure. We show that for Twitter, our naive measures of "caloric input", "caloric output", and the ratio of these measures are all strong correlates with health and well-being measures for the contiguous United States. Our caloric balance measure in many cases outperforms both its constituent quantities; is tunable to specific health and …
Integrating Fisheries And Agricultural Programs For Food Security, Brendan Fisher, Robin Naidoo, John Guernier, Kiersten Johnson, Daniel Mullins, Dorcas Robinson, Edward H. Allison
Integrating Fisheries And Agricultural Programs For Food Security, Brendan Fisher, Robin Naidoo, John Guernier, Kiersten Johnson, Daniel Mullins, Dorcas Robinson, Edward H. Allison
Rubenstein School of Environment and Natural Resources Faculty Publications
Background: Despite the connections between terrestrial and marine/freshwater livelihood strategies that we see in coastal regions across the world, the contribution of wild fisheries and fish farming is seldom considered in analyses of the global food system and is consequently underrepresented in major food security and nutrition policy initiatives. Understanding the degree to which farmers also consume fish, and how fishers also grow crops, would help to inform more resilient food security interventions. Results: By compiling a dataset for 123,730 households across 6781 sampling clusters in 12 highly food-insecure countries, we find that between 10 and 45% of the population …
Reducing Greenhouse Gas Emissions In Agriculture Without Compromising Food Security?, Stefan Frank, Petr Havlík, Jean François Soussana, Antoine Levesque, Hugo Valin, Eva Wollenberg, Ulrich Kleinwechter, Oliver Fricko, Mykola Gusti, Mario Herrero, Pete Smith, Tomoko Hasegawa, Florian Kraxner, Michael Obersteiner
Reducing Greenhouse Gas Emissions In Agriculture Without Compromising Food Security?, Stefan Frank, Petr Havlík, Jean François Soussana, Antoine Levesque, Hugo Valin, Eva Wollenberg, Ulrich Kleinwechter, Oliver Fricko, Mykola Gusti, Mario Herrero, Pete Smith, Tomoko Hasegawa, Florian Kraxner, Michael Obersteiner
Rubenstein School of Environment and Natural Resources Faculty Publications
To keep global warming possibly below 1.5◦C and mitigate adverse effects of climate change, agriculture, like all other sectors, will have to contribute to efforts in achieving net negative emissions by the end of the century. Cost-efficient distribution of mitigation across regions and economic sectors is typically calculated using a global uniform carbon price in climate stabilization scenarios. However, in reality such a carbon price would substantially affect food availability. Here, we assess the implications of climate change mitigation in the land use sector for agricultural production and food security using an integrated partial equilibrium modelling framework and explore ways …
When, Where, And How Nature Matters For Ecosystem Services: Challenges For The Next Generation Of Ecosystem Service Models, Jesse T. Rieb, Rebecca Chaplin-Kramer, Gretchen C. Daily, Paul R. Armsworth, Katrin Böhning-Gaese, Aletta Bonn, Graeme S. Cumming, Felix Eigenbrod, Volker Grimm
When, Where, And How Nature Matters For Ecosystem Services: Challenges For The Next Generation Of Ecosystem Service Models, Jesse T. Rieb, Rebecca Chaplin-Kramer, Gretchen C. Daily, Paul R. Armsworth, Katrin Böhning-Gaese, Aletta Bonn, Graeme S. Cumming, Felix Eigenbrod, Volker Grimm
Rubenstein School of Environment and Natural Resources Faculty Publications
Many decision-makers are looking to science to clarify how nature supports human well-being. Scientists' responses have typically focused on empirical models of the provision of ecosystem services (ES) and resulting decision-support tools. Although such tools have captured some of the complexities of ES, they can be difficult to adapt to new situations. Globally useful tools that predict the provision of multiple ES under different decision scenarios have proven challenging to develop. Questions from decision-makers and limitations of existing decision-support tools indicate three crucial research frontiers for incorporating cutting-edge ES science into decision-support tools: (1) understanding the complex dynamics of ES …