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DOMINIK S. MEIER



I’m currently a postdoc at the Center for Philanthropy Studies (CEPS) and a
visiting researcher at the Gradel Institute of Charity (Oxford).

I use big data, machine learning and natural language processign to study
individual and institutional philanthropy.

I am also interested in the Sustainable Development Goals (SDGs), especially in
how philanthropy can contribute to achieving the SDGs. As part of this interest,
I helped co-develop and validate a machine learning algorithm that detects SDGs
in text.


SELECTED PUBLICATIONS

 1. text2sdg: An R package to Monitor Sustainable Development Goals from Text
    Dominik S. Meier, Rui Mata, and Dirk U Wulff
    R Journal (in press), 2021
    
    Abs PDF
    
    Monitoring progress on the United Nations Sustainable Development Goals
    (SDGs) is important for both academic and non-academic organizations.
    Existing approaches to monitoring SDGs have focused on specific data types;
    namely, publications listed in proprietary research databases. We present
    the text2sdg package for the R language, a user-friendly, open-source
    package that detects SDGs in any kind of text data using different existing
    or custom-made query systems. The text2sdg package thereby facilitates the
    monitoring of SDGs for a wide array of text sources and provides a
    much-needed basis for validating and improving extant methods to detect SDGs
    from text.

 2. Using novel data and ensemble models to improve automated labeling of
    Sustainable Development Goals
    Dirk U Wulff, Dominik S. Meier, and Rui Mata
    Sustainability Science (in press), 2023
    
    Abs PDF
    
    A number of labeling systems based on text have been proposed to help
    monitor work on the United Nations (UN) Sustainable Development Goals
    (SDGs). Here, we present a systematic comparison of systems using a va-
    riety of text sources and show that systems differ con- siderably in their
    specificity (i.e., true-positive rate) and sensitivity (i.e., true-negative
    rate), have systematic bi- ases (e.g., are more sensitive to specific SDGs
    relative to others), and are susceptible to the type and amount of text
    analyzed. We then show that an ensemble model that pools labeling systems
    alleviates some of these lim- itations, exceeding the labeling performance
    of all cur- rently available systems. We conclude that researchers and
    policymakers should care about the choice of label- ing system and that
    ensemble methods should be favored when drawing conclusions about the
    absolute and rela- tive prevalence of work on the SDGs based on automated
    methods.

 3. The evolution of SDG-related third sector and public administration
    literature: an analysis and call for more SDG-related research
    Dominik S. Meier
    Sustainability: Science, Practice and Policy, 2023
    
    Abs HTML PDF
    
    The seventeen Sustainable Development Goals (SDGs) were adopted in 2015 and
    achieving them by 2030 is crucial for human development. However, progress
    on the goals currently remains short of the requirements. As the third and
    public sectors play a crucial role in achieving the goals, this study
    analyzes how the SDG-related third sector and public administration
    literature has evolved over the last thirty years. I use a state-of-the-art
    method to map articles to the SDGs. In contrast to previous studies that
    have found an increase in publications that directly mention the SDGs, I
    find a decline in the proportion of articles that relate to the SDGs without
    necessarily mentioning them directly. I also analyze how the SDG-relatedness
    of an article corresponds to its citation count. While I find mixed results
    across SDGs and data sources, the relationship between SDG-relatedness and
    citation count is significantly more positive for work published after the
    adoption of the SDGs. While the association between SDG-relatedness and
    citation count is now positive for the third sector literature published
    after 2015, it is still negative for the public administration literature.

 4. Risking Your Health to Help Others: The Effect of Pandemic Severity on
    Volunteering
    Dominik S. Meier, Amadeus Petrig, and Georg von Schnurbein
    Nonprofit and Voluntary Sector Quarterly, 2023
    
    Abs HTML PDF
    
    The COVID-19 pandemic affected the provision of voluntary work across the
    globe. We study informal volunteers who buy and deliver groceries for people
    in a high-risk group or in quarantine. Using data from a volunteering
    grocery delivering app in Switzerland that coordinated these volunteers, we
    are able to track volunteering during the pandemic. Combined with public
    health data on cases and deaths, we test how the severity of the pandemic
    affects the provision of voluntary work in the form of neighborhood grocery
    deliveries. We find a positive effect of the number of deaths on voluntary
    deliveries. However, in contrast to the literature studying the effect of
    the severity of the pandemic on giving, this effect is concave. We suggest
    that this concave effect is due to the signal of risk of infection implied
    by rising death rates, which is at odds with the signal of need to help
    others.

 5. Compassion for all: Real-world online donations contradict compassion fade
    Dominik S. Meier
    2023
    
    Abs PDF
    
    People tend to donate more to help a single rather than a group of victims.
    However, recent studies were able to reverse this compassion fade effect by
    presenting people with multiple donation appeals with different victim group
    sizes (joint evaluation) instead of just one donation appeal (separate
    evaluation). Because practitioners often use the compassion fade effect to
    boost giving, the reversal of this effect in joint evaluation settings has
    important implications for fundraising. This study tests whether the
    reversed compassion fade effect can be replicated in the field by using data
    from the crowdfunding platform GoFundMe. When browsing projects on GoFundMe,
    people see multiple projects displayed at once, placing them in a joint
    evaluation context. I found a concave effect of the perceived victim group
    size on the amount of funds raised, the number of donations received, and
    the size of the average donation received by a project.

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