Schedule and Program

Keynote Addresses

Brian Smith, Executive Director NIBR Biostatistics, Novartis Pharmaceutical Corporation

Alfredo Morales, Principal Research Scientist, Redzone Production Systems

Frank Hu, Chair, Department of Nutrition, Harvard T.H. Chan School of Public Health

Panel Descriptions & Panelists

Career Panel for Industry Minded Professionals

Data Analytics for Mitigating Health Disparities

Description
This panel will discuss health disparities affecting racial minority groups, and how the emergence and application of big data can help mitigate such disparities through analysis of differences in disease rates, exposures and risk, socioeconomic status, health coverage and insurance. This talk will discuss why disparities might arise, giving students a better understanding of the problems faced by different racial demographics, and big data's potential for attenuating those disparities.

Moderators
Kimberly Dong, Tufts School of Medicine
Seblewongel Yigletu, Tufts University

Panelists
Adam Pittman is a data Scientist at Folia Health, a startup company dedicated to helping patient and caregiver observations make their way into clinical practice. Currently, he works on integrating real world evidence and patient reported outcomes into existing healthcare data structures. Previously he worked with a Colorado syringe access program to help drive new legislation for individual and population safety in the opioid usage space. Adam holds a ScM in Biostatistics from Johns Hopkins Bloomberg School of Public Health.

Dr. Anna Orlova, a Senior Faculty, Health Informatics and Analytics Program, Tufts School of Medicine. She is also a Visiting Associate Professor in informatics at Johns Hopkins School of Medicine. Dr. Orlova’s informatics interests are in the areas of the Electronic Health Records, telehealth and digital health; health data and systems standardization and interoperability; and data trust. Dr. Orlova joined the Tufts University in 2018 to launch the Health Informatics and Analytics program at Tufts. Her online teaching experience includes teaching various informatics and health IT standardization courses at Johns Hopkins, University of Massachusetts, Amherst, and Tufts.

Dr. Carlota Dao is a Scientist III in the Energy Metabolism Laboratory at the Human Nutrition Research Center on Aging. Her research interests include obesity, weight management, food culture and eating behavior, gut microbiota, and health disparities. Specifically, her projects span three interrelated areas within obesity research: 1) Studying how cultural, environmental and biological factors determine eating behavior and weight status. 2) Developing culturally relevant lifestyle interventions for weight loss, including an ongoing community-based pilot intervention in older Hispanic adults. And 3) Understanding the role that the gut microbiota plays in chronic disease risk. Her previous experience includes establishing novel data integration approaches to analyze ‘big data’ and gain new insights on the interaction between host biology, gut microbiota, and environmental factors.

Glory Song has been working as an Epidemiologist for the Department of Public Health since 2011. She supports surveillance and evaluation work for a number of chronic disease prevention programs within the Bureau of Community Health and Prevention, including the Massachusetts Tobacco Cessation & Prevention Program (MTCP) and Mass in Motion. She has background and interest in quasi-experimental study designs, survey instrument development, and community-level policy evaluation. Glory received her MPH from Boston University School of Public Health.

Trade Tradeoffs: Efficiency, Resilience, and Sustainability

Description
Economic and trade theory guide our understanding of agricultural policy, international food prices, and foreign food aid programming and planning. Experts in this panel will discuss innovation and barriers to creating sustainable supply chains: from community-level logistics to international trade policies such as trade war tariff increases and the NAFTA renegotiation. They will also share how they are innovating sustainably, both in terms of environmental impacts, and in terms of social inclusion and equity.

Moderator
Will Masters is a Professor at Tufts University, in the Friedman School of Nutrition and the Department of Economics, working on the economics of agriculture, food and nutrition. From 2006 through 2011 he edited the journal Agricultural Economics. He is an elected Fellow of the Agricultural & Applied Economics Association (AAEA). Details online at http://sites.tufts.edu/willmasters.

Panelists
Christopher Mejía Argueta is a Research Scientist at the MIT Center for Transportation and Logistics (CTL). He develops applied research on retailing operations and food supply chains for multiple stakeholders in the Food and Retail Operations Lab (FaROL). His research focuses on improving the efficiency, flexibility of operations in multiple stakeholders, creating food access models to address the fragmented retail market and farmer’s side. His research focuses on reducing undesired socioeconomic and health problems related to income disparity, food malnutrition, food waste by proposing sustainable policies, business models to help vulnerable population segments. Dr. Mejía is also the Director of the MIT SCALE network for Latin America.

Andrew Feierman is a Data Scientist working on the Trase project. Before joining SEI, he worked on global environmental policy for Dr. Angel Hsu in the Data-Driven Environmental Solutions Lab, jointly based out of Yale University and Yale-NUS in Singapore. He also has experience working with large private companies on reducing energy consumption in buildings through the Institute for Market Transformation in Washington, DC, and holds a degree from American University’s School of International Service.

Ravdeep Jaidka is the Sourcing Manager at the fresh produce division of Equal Exchange, managing the banana and avocado programs sourced directly from small farmer cooperatives in Ecuador, Peru and Mexico. Ravdeep started at Equal Exchange in 2015, after receiving her Master's degree in the Agriculture, Food and Environment Program at the Friedman School.

Understanding Big Data Implications for Food Policy

Description
There is no commonly accepted definition of the term big data, yet this ambiguity has not stopped policy makers from taking an interest in its collection, management and use. But how is big data relevant to nutrition and food policy? Increasingly, participants in the agricultural supply chain are collecting data from the farm gate to the plate, while questions of ownership of and access remain unanswered. Evidence-based research produces vast amounts of data about critical policy issues, which informs and justifies the actions of public, private and not-for-profit organizations, yet questions of appropriate data analysis remain. This panel will pursue the question, how does this growing body of highly detailed information – often referred to as “big data” - influence research, funding and implementation of food and nutrition policy, and what are the strengths and challenges of this approach?

Moderator
Katrina Sarson is an Emmy Award winning television producer who is currently a Masters student at the Friedman School of Nutrition Science and Policy at Tufts University. Previously, she earned a Masters in Education at the Harvard Graduate School of Education with an emphasis on Technology in Education. Her interests are nutrition education, communication, and the ways that corporations and government agencies interact to shape food and nutrition policies. During her time at Friedman, she has worked on the Public Impact Initiative, and co-founded Friedman’s Potluck Club, and Tufts Food Week. She is passionate about food, nutrition, bread baking, and engaging conversations.

Panelists
Laura Benavidez, MBA has been the executive director of food and nutrition services of Boston Public Schools since August 2016. Laura was formerly with the Los Angeles Unified School District (LAUSD), where she was the interim co-director. She oversaw the operations and logistics for LAUSD, the second largest school district in the country with more than 560,000 students, 700 schools, 1,100 meal programs, and over 4,000 foodservices employees. Laura earned her bachelor of science in food science and technology, and master of business administration. She is currently pursuing a doctorate degree.Since starting at BPS' Food and Nutrition Services department, her focus has been to be fiscally sustainable, decrease waste, increase technology, and build the culture of the program. (Dorchester, MA)

Alana Davidson is the SNAP interagency specialist at the Massachusetts Department of Transitional Assistance. She manages the Department’s SNAP projects with external agencies to address food insecurity in a more holistic way and improve SNAP access. This includes policy alignment, following legislation and regulations, research and assisting with writing the Department’s publicly submitted comments for federal rule making. Prior, Davidson worked at anti-hunger nonprofit organizations on child nutrition advocacy and outreach. She holds a Master’s of Science in Food Policy and Applied Nutrition from Tufts University and a Bachelors of Science in nutrition, dietetics from the University of New Hampshire.

Eileen Kennedy is a former dean of the Friedman School. Currently a professor at the School, Kennedy's research interests include assessing the health, nutrition, diet and food security impacts of policies and programs; nutrient density and diet diversity; and agriculture nutrition linkages. She is a member of the High Level Panel of Experts on Food Security and Nutrition of the UN Committee on World Food Security. Formerly a member of the UN SCN Advisory Group on Nutrition. She founded and was the first Executive Director of the USDA Center for Nutrition Policy and Promotion. She created the Healthy Eating Index which is used as a single summary measure of diet quality. She is currently a member of the World Economic Forum's Global Council on Food Security and Nutrition.

Parke Wilde (PhD, Cornell) is a food economist and professor at the Friedman School of Nutrition Science and Policy at Tufts University. Previously, he worked for USDA’s Economic Research Service. At Tufts, Parke teaches graduate-level courses in statistics and U.S. food policy. His research addresses the economics of federal nutrition assistance programs. He was Director of Design for the SNAP Healthy Incentives Pilot (HIP) evaluation in Hampden County, Massachusetts. He has been a member of the Institute of Medicine’s Food Forum and is on the scientific and technical advisory committee for Menus of Change, an initiative to advance the health and sustainability of the restaurant industry. He directs the USDA-funded Tufts/UConn Research Innovation and Development Grants in Economics (RIDGE) program. In March, 2018, Routledge/Earthscan released the second edition of his book, Food Policy in the United States: An Introduction.

Perspectives on Environmental and Economic Costs to Food Security

Description
How innovative analytic methods for understanding food security and food access in the context of environmental and economic stressors are yielding nuanced understanding of barriers to food security. This session evaluates the role data sciences can play in integrating interdisciplinary knowledge and data to understand the marriage of environmental and economic factors on topics of food security.

Moderator
Dr. Meg Hartwick completed her Ph.D. work in Molecular and Evolutionary Systems Biology developing predictive models for emerging food and waterborne pathogens and received her MSc through the Tufts Cummings School of Veterinary Medicine in Conservation Medicine. She has worked as Data Scientist examining the intersection of food production and human and wildlife disease with the University of New Hampshire, Woods Hole Oceanographic Institute and Tufts University. She is currently a Data Scientist with InForMID.

Panelists
Yan Bai is a doctoral student at Tufts’ Friedman School of Nutrition. His work is focused on index studies on the cost of nutritious diets around the world. Before that, Yan earned the Master of International Business (MIB) at the Fletcher School. Besides advancing his knowledge of international finance and global health there, he also developed quantitative skills at Harvard Chan School. Prior to his graduate education, Yan worked as an investment analyst in the finance industry, where he obtained industry experiences in health and agriculture sectors in China, Southeast Asia, and Africa. Yan also holds a master’s degree in Economics from Tufts and bachelor’s degrees in Chemistry and Economics from Peking University in China.

Nicole Tichenor Blackstone is an Assistant Professor in the Division of Agriculture, Food, and Environment at the Friedman School of Nutrition Science and Policy at Tufts University. Dr. Blackstone’s research focuses on developing and evaluating strategies to improve food system sustainability. Her work fuses industrial ecology, nutrition, and social science methods. To date, her research has explored the environmental and social implications of livestock agriculture, human diets, food waste management, and regional food systems. She teaches graduate courses on U.S. agriculture, environmental life cycle assessment, and corporate social responsibility in the food industry. Dr. Blackstone holds a Ph.D. and M.S. in Nutrition from Tufts University and a B.A. in Philosophy and Religious Studies from the University of Kansas.

Sean B. Cash is the Bergstrom Foundation Professor in Global Nutrition and an Associate Professor at the Friedman School of Nutrition Science and Policy at Tufts University. As an agricultural and food economist, his research focuses on how food, nutrition, and environmental interventions and policies affect both producers and consumers. He has conducted research in the areas of environmental impacts in food production, including projects on climate change and coffee and tea production, and invasive species management. Other work includes assessing the efficacy of food label and price interventions as public health and environmental tools; children’s food choices in commercial and school environments; and consumer interest in food labeling of ethical attributes of food production.

Dr. Bea Rogers is Professor of Economics and Food Policy and Director of the Food Policy and Applied Nutrition Program at the Friedman School of Nutrition Science and Policy, where she has been on the faculty since 1982. Prof. Rogers has over 30 years of experience promoting evidence-based policy and programs related to food security, food consumption, and nutrition in the developing world. She has been responsible for the design and implementation of national household income, expenditure, and consumption surveys in several countries, and has conducted many smaller scale surveys of household economic and consumption behaviors. Her current work looks at effectiveness of alternative food aid products used in nutrition programs and on the sustainability of food aid program impacts in the face of insecurity and civil unrest. She is also working on a project to improve dietary data collection methods and promote the use of such data in policy-making.

Jennifer Coates, Tufts Friedman School of Nutrition Science and Policy

Data Analytics in Nutrition and Health Business: A Data Analytics Career Panel

Description
Nutrition and food related business and entrepreneurship requires constant product iteration, innovation, and creativity. The application of advanced technological programs can further improve the quantity, quality, and complexity of data and information available for this research and development. This panel will invite local business experts and entrepreneurs to discuss applications of data in product development and business planning for establishing healthier lifestyles and promoting more nutritious products.

Moderator
Christine Kressirer is the Site Director of Tufts Launchpad BioLabs, a premier co-working facility for life science startups in Boston. Christine spent 7 years at the Forsyth Institute most recently as the Director of Core and Laboratory Services and 5 years at Arizona State University in research and laboratory coordination. She received her Ph.D. in Pharmaceutical Biology form Ludwig-Maximilians University in Munich, Germany and was a Postdoctoral Research Fellow at the Forsyth Institute and the Harvard School of Dental Medicine.

Panelists
Benjamin Batorsky is the Associate Director of Data Science at MIT Sloan, where he leads data science projects for the Food Supply Chain and Analytics group. Previously he worked on the data science team at ThriveHive, where he scoped and built data products by leveraging multi-modal datasets on small businesses and their customers. In his work, he is often posed difficult business questions and is able to develop and execute a strategy for answering them with either one-off analytic products or production-ready prototypes. He earned his PhD in Policy Analysis from the RAND Corporation, working on analytics projects in the areas of health, policy and infrastructure.

Erin Baumgartner is a local food nerd and entrepreneur. She is the CEO and founder of Family Dinner a local farmer's market delivery service. Family Dinner seeks to use data to improve the local food supply chain and eliminate waste in the system while highlighting the importance of local food through data visualization. Erin spent 11 years at MIT, most recently as the Assistant Director of the MIT Senseable City Lab, an Urban Science Lab within the Department of Urban Studies and Planning. She is also the former Director of the MIT-France Program, organizing scientific exchanges between MIT students, faculty and researchers and the French Scientific Community. Erin spent many years living and working in France and currently lives on Boxford, MA with her husband and co-founder Tim, and their toothless dog, Frank.

Dr. Svetlana Vinogradova is a Lead Data Scientist at InsideTracker, working with the Data Science team to integrate blood biomarkers and DNA data with physiological data from activity trackers to improve lifestyle recommendations and discover new patterns and optimal zones in sleep, heart rate, and blood biomarkers. Prior to Inside Tracker, Svetlana got her PhD in Bioinformatics and Mathematical Biology from Lomonosov Moscow State University and then completed a Postdoctoral training at Harvard Medical School and Dana-Farber Cancer Institute, where she worked as a bioinformatician developing statistical methods to study epigenetic mechanisms affecting gene expression. In addition to being a researcher and data scientist, Svetlana is an aspiring marathon runner and Boston marathon qualifier.

Marcia Hooper is a principal of Branch Venture Group, LLC, an angel investing group, focused on food startups, targeting food products, food technology, business services for food-related companies, ag-tech, and sustainability. She currently serves as a Senior Advisor to Bowside Capital, a private equity firm focusing in the small capitalization market. She has over 30 years of private equity and venture capital investing experience. She has served as a Director of over 30 private and publicly listed companies. She began her career at IBM in marketing. Ms. Hooper earned an MBA from the Harvard Graduate School of Business, a MA from Columbia University and an Sc.B. from Brown University.

Alfredo Morales works in understanding the complex behavior of social systems by analyzing big data with artificial intelligence algorithms, networks and complexity science. He explains large scale, societal behaviors, such as social segregation and polarization, by retrieving unstructured patterns of information from large datasets resulting from human activity on Internet, mobile phones and shopping data. In 2018 he was included in the list of 35 Innovators Under 35 by MIT Technology Review and in 2017 he was included in the list of Latinos of the Future by the journal El Planeta in Boston.

Workshop Descriptions

An Intro to GIS using QGIS: Exploring Access to Healthy Foods in Cambridge, Ma

Teaching Data Analytics to Non-Analytics Students

Comparisons Across Statistical Software

Identifying Your Audience to Capture: Effective Communication of Data-Driven Research

What's In The Recipe: Model Development and Diagnostics

Speaking Results Without Words: Data Visualization

Breaking Down Silos: Managing and Analyzing Data As A Team

Network Sciences and Complex Systems in Nutrition-Related Research

Oral Presentations

Group A: Nasir et al. Substance Use Disorder Outcome Predictions for Decision Support: A Holistic Data Approach

Group A: Wang et al. Sleeping Disorders and Alzheimer's Disease: Evidence for Heterogeneity

Group B: Stark. What a “Batman Graph” shows about US income: A cautionary tale of correlation, principal components, and nonlinear regression

Group B: Nasir et al. Synthetic Average Neighborhood Sampling Algorithm (SANSA): A Neighborhood Informed Synthetic Sample Placement Approach to Improve Learning from Imbalanced Data

Group C: Ericson. Minds in Motion: Using positional data to study human behavior and cognition

Group C: Abhilash et al. Building a Predictive Framework for Analyzing Opioid Patient Toxicology Data to Improve Medication-Assisted Therapy Adherence and Relapse

In the United States, over 2 million people are diagnosed with OUD, resulting in costs exceeding $500 billion each year. Pharmacological intervention by medication-assisted treatment (MAT) is most effective, based on minimizing withdrawal severity, reducing relapse, and improving retention in treatment. Despite demonstrated MAT effectiveness, there are differences in individual responses due to high dropout, non-adherence, and relapse. We have analyzed data from clinical toxicology tests over 18 months from 71 providers listing suboxone as the MAT on order for approximately 1,500 patients. For these patients, analysis of clinical toxicology results (over 512,000 tests) enabled determination of frequency of testing relative to MAT positives and unexpected positives of common drugs of abuse (including non-MAT opiates, amphetamine/methamphetamine, and benzodiazepines). Descriptive statistics demonstrate that testing frequency is related to adherence (measured by consistent appearance of MAT) and relapse (measured by unexpected positives). The analysis also found that more frequent testing showed decreased adherence and higher indicators of relapse with all drugs except benzodiazepines. In addition, significant associations between testing frequency, unexpected positives, and simulated adherence (i.e. dropping a drug directly into the urine) were observed among patients in a 6-month sample of the dataset. Finally, we identified geographically-distributed patterns of drugs showing unexpected positives that were consistent with public health data on drug use. Our ongoing work includes predictive analytics to identify patients at risk for adverse adherence and relapse outcomes based on testing history, drug metabolism, and analysis of unexpected positive rates—in addition to using data to distinguish between metabolism and drug impurities and determine the parent drug that was ingested. We propose that this predictive method can improve adherence and retention of MAT patients by aiding evidence-based treatment determination.

Group D: Bai & Wallbaum. Dual-dynamic Retirement Income Strategy for Better Retirement Outcomes

Group D: Mentzer et al. The Role of Gender and Party on the Twitter Conversation in the 2018 U.S. Senate Elections

Group E: McGuirk. Business Ethics at the Core of Successful and Sustainable Analytics Practices

The International Institute for Analytics has included 'ethics of analytics' as a top five business imperative in both their 2019 and 2020 Analytics Predictions and Priorities list. Interestingly, this heightened need to focus on ethical practices coincides with a separate industry and business priority to ramp up efforts to identify new ways to collect consumer data and apply analytics and data science techniques on this data to gain a competitive advantage. In fact, in a recent study completed by Forrester Research, they found that over 50% of the companies surveyed are planning to launch initiatives to expand their ability to source external data and that many of these firms will appoint 'data hunters' to lead these initiatives. In this session we will dive into this critical moment in time for the analytics and data science communities. A time when an increased reliance on these practices will intensify the need to incorporate sound judgement and ethical business practices across all facets of analytics operations. Unfortunately, there have been too many recent cases of companies committing transgressions that quickly erode consumer trust in their ability to properly manage data and deploy ethical analytics practices. In 2018, Facebook enabled Cambridge Analytica to use millions of members’ personal data without their consent for targeted political advertising and in 2019 Goldman Sachs has been under fire for allowing blatant gender bias in algorithms used to establish credit limits for Apple Card customers.. This session will explore the important role educational institutions can play helping to inspire and empower students to use ethical and socially responsible data collection and analytic practices. It will also explore how industry can utilize cross-functional data governance teams to ensure diverse and empathetic perspectives are considered when deciding what data should be collected, analyzed, and used to support insight-driven decision-making.

Poster Presentations

Hsu et al. Differences in nutrient intake between individuals with and without familial longevity

The contribution of diet upon the ability to reach extreme ages remains unclear, in part, because centenarians (people over the age of 100) may have markedly changed dietary patterns at the end of life. Studying centenarian offspring, who are predisposed to longer and healthier lives, allows for the investigation of diet earlier in the life course when it is more likely to have an effect on longevity. The primary objective of the study was to assess the difference in nutrient intake between centenarian offspring and a referent cohort in the New England Centenarian Study. Semi-quantitative food frequency questionnaire data were collected on 280 centenarian offspring and 129 referent participants without familial longevity (mean age 72.6 years). The data were converted to 103 nutrient measurements. Wilcoxon rank sum test and generalized linear regression were used to evaluate the association between each nutrient measurement and cohort (offspring vs. referent). Principal component analysis identified eight components thus a corrected p-value of < 0.00625 was considered to be statistically significant. After adjustment of age, sex, and total caloric intake, centenarian offspring had higher intakes of dietary sources (i.e., not including supplements) of iron (p = 0.0060), niacin (p = 0.0016), riboflavin (p = 0.0016) and zinc (p = 0.0026) than referents. In conclusion, centenarian offspring have a higher reported intake of some vitamins and minerals, particularly those associated with energy metabolism and oxidant levels, in comparison with individuals without familial longevity. In addition to the genetic contributions to achieving extreme ages, intake of iron, niacin, riboflavin, and zinc may contribute to the longer life and health spans of offspring of centenarians. Future research should investigate how intake levels of these nutrients by centenarian offspring compare with nationally representative data and recommended daily allowances as well as metabolite measurements from blood.

Gregory & Byrd. Using Geographic Information Systems (GIS) to Determine Sites for SNAP-Ed

Mississippi State University Extension Office of Nutrition Education (ONE) is utilizing geographic information systems (GIS) technology to determine site location eligibility for Supplemental Nutrition Assistance Program Education (SNAP-Ed) programming among low-resource audiences.Methods to determine eligibility for SNAP-Ed include counties determined by the USDA to be StrikeForce, in persistent poverty, or child persistent poverty. Any county that meet one of these criteria received approval for programming at all locations within the county. Counties that do not meet any of the three criteria could use approved schools (public schools whose enrollment was 50% or more free/reduced lunch) and locations allowed by SNAP-Ed guidance (SNAP offices, WIC offices, food banks/pantries, county health departments, etc.) for programming.It was proposed to use GIS technology (GIS Online) to determine eligibility for sites that did not meet any of the above criteria. Shapefiles were created based on the following: areas within a one-mile radius of an approved school and areas within a one-mile radius of a census tract where 50% or more of the population’s income was below 185% of the federal poverty level. The two shapefiles were added to an existing map layer of Mississippi counties. Sites that intersect with either of these areas are considered eligible for SNAP-Ed programming.Site locations can be validated in two ways: using a search engine for a single site or uploading addresses to be geocoded for multiple sites. Using these additional criteria to determine eligibility has increased the number of sites where ONE employees can conduct SNAP-Ed.Using GIS technology can help ONE identify eligible sites that are not currently being served.Future plans include adding additional criteria for eligibility and creating an interactive mapping tool ONE employees can use to determine eligibility without having to submit requests to the state office.

Chow et al. Use of advanced statistical analysis in determining death manner: lessons from 330,000 national violent death data

Suicide is the tenth leading cause of death in the US, over 48,000 Americans died by suicide in the year 2018. The number might still be underreported, since identifying the intent of death is difficult in the absence of a suicide note. Identifying intent becomes problematic specifically for opioid overdose cases given the drug’s abilities to cause respiratory depression. The ability to accurately identify and report on the prevalence of suicide has important implications for policy development in suicide prevention. The NVDRS is a state-based surveillance system funded by the Centers for Disease Control and Prevention (CDC) to collect data on violent deaths from participating states. Currently CDC allows use of restricted access data to researchers for a preapproved analysis. In this study, we analyzed ~330,000 violent death data from 37 participating US states for 15 years (2003-2017). Using NVDRS data, we aim to identify and validate predictors of suicide in the opioid overdose cases through a combination of qualitative and quantitative analyses. The quantitative analysis begins with results from contingency tables examining the association between opiates and the manner of death coded by CDC staff. Next, we will perform a logit model predicting the probability of suicides and homicides resulting from opiates indicated as a causal factor controlling for socio-demographic factors. The qualitative method relies on the narratives generated from law enforcement and medical examiner reports. We identified a list of word/themes that might be distinctly present in suicide compared to homicide. This pattern/theme can later be used to develop a methodology for natural language processing and statistical text analysis to investigate the differential use of language (e.g., thematic content, syntax, sentiment, etc.) across death narratives and construct a measure of descriptive similarity between narratives within and across groups of decedents.

Hur et al. Combining unstructured social media data with structured scientific literature: a data merging problem

Deichmann et al. European Moods: Satisfaction levels from 2003 to 2016