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Morgan R Frank

Datos Biográficos

ID1753764
NOMBREMorgan R Frank
NOMBRESMorgan R
APELLIDOFrank
FIRMAFRANK M R
AFILIACIONESUniversity of Pittsburgh
ORCID0000-0001-9487-9359
VERIFICADOSí
TOTAL DE OBRAS7
TOTAL DE CITAS3
OBRAS COMO AUTOR7
OBRAS COMO EDITOR0
PRIMER AÑO DE PUBLICACIÓN2013
AÑO MÁS RECIENTE DE PUBLICACIÓN2026
ÍNDICE H1
  • Stakeholder Satisfaction Interdependencies in 10-K Reports

    Open Access•Yishan Luo, Morgan R Frank et al.•ARTICLE•Journal of Business Ethics•2026

  • Behaviour-based dependency networks between places shape urban economic resilience

    Open Access•Takahiro Yabe, Bernardo García Bulle Bueno et al.•ARTICLE•Nature Human Behaviour•2024•Citada por: 3•Referencias: 39

    Disruptions, such as closures of businesses during pandemics, not only affect businesses and amenities directly but also influence how people move, spreading the impact to other businesses and increasing the overall economic shock. However, it is unclear how much businesses depend on each other during disruptions. Leveraging human mobility data and same-day visits in five US cities, we quantify dependencies between points of interest encompassing…

  • Art and the science of generative AI

    Open Access•Ziv Epstein, Sudi Nurtini et al.•ARTICLE•Science•2023

    Understanding shifts in creative work will help guide AI’s impact on the media ecosystem

  • Developing China’s workforce skill taxonomy reveals extent of labor market polarization

    Open Access•Weipan Xu, Xiaozhen Qin et al.•ARTICLE•Humanities and Social Sciences…•2021

    China, the world’s second largest economy, is transitioning into an advanced, knowledge-based economy after four decades of rapid economic development. However, China still lacks a detailed understanding of the skills that underly the Chinese labor force, and the development and spatial distribution of these skills. Similar data has proven essential in other contexts; for example, the US standardized skill taxonomy, Occupational Information Netwo…

  • Toward understanding the impact of artificial intelligence on labor

    Open Access•Morgan R Frank, David Autor et al.•ARTICLE•Proceedings of the National…•2019

    Rapid advances in artificial intelligence (AI) and automation technologies have the potential to significantly disrupt labor markets. While AI and automation can augment the productivity of some workers, they can replace the work done by others and will likely transform almost all occupations at least to some degree. Rising automation is happening in a period of growing economic inequality, raising fears of mass technological unemployment and a r…

  • Human language reveals a universal positivity bias

    Open Access•Peter Sheridan Dodds, Eric M Clark et al.•ARTICLE•Proceedings of the National…•2015

    Significance The most commonly used words of 24 corpora across 10 diverse human languages exhibit a clear positive bias, a big data confirmation of the Pollyanna hypothesis. The study’s findings are based on 5 million individual human scores and pave the way for the development of powerful language-based tools for measuring emotion.

  • The Geography of Happiness

    Open Access•Lewis Mitchell, Morgan R Frank et al.•ARTICLE•PLoS ONE•2013

    We conduct a detailed investigation of correlations between real-time expressions of individuals made across the United States and a wide range of emotional, geographic, demographic, and health characteristics. We do so by combining (1) a massive, geo-tagged data set comprising over 80 million words generated in 2011 on the social network service Twitter and (2) annually-surveyed characteristics of all 50 states and close to 400 urban populations…

  • Behaviour-based dependency networks between places shape urban economic resilience

    Open Access•Takahiro Yabe, Bernardo García Bulle Bueno et al.•ARTICLE•Nature Human Behaviour•2024•Citada por: 3•Referencias: 39

    Disruptions, such as closures of businesses during pandemics, not only affect businesses and amenities directly but also influence how people move, spreading the impact to other businesses and increasing the overall economic shock. However, it is unclear how much businesses depend on each other during disruptions. Leveraging human mobility data and same-day visits in five US cities, we quantify dependencies between points of interest encompassing…

  • The Geography of Happiness

    Open Access•Lewis Mitchell, Morgan R Frank et al.•ARTICLE•PLoS ONE•2013

    We conduct a detailed investigation of correlations between real-time expressions of individuals made across the United States and a wide range of emotional, geographic, demographic, and health characteristics. We do so by combining (1) a massive, geo-tagged data set comprising over 80 million words generated in 2011 on the social network service Twitter and (2) annually-surveyed characteristics of all 50 states and close to 400 urban populations…

  • Human language reveals a universal positivity bias

    Open Access•Peter Sheridan Dodds, Eric M Clark et al.•ARTICLE•Proceedings of the National…•2015

    Significance The most commonly used words of 24 corpora across 10 diverse human languages exhibit a clear positive bias, a big data confirmation of the Pollyanna hypothesis. The study’s findings are based on 5 million individual human scores and pave the way for the development of powerful language-based tools for measuring emotion.

  • Toward understanding the impact of artificial intelligence on labor

    Open Access•Morgan R Frank, David Autor et al.•ARTICLE•Proceedings of the National…•2019

    Rapid advances in artificial intelligence (AI) and automation technologies have the potential to significantly disrupt labor markets. While AI and automation can augment the productivity of some workers, they can replace the work done by others and will likely transform almost all occupations at least to some degree. Rising automation is happening in a period of growing economic inequality, raising fears of mass technological unemployment and a r…

  • Developing China’s workforce skill taxonomy reveals extent of labor market polarization

    Open Access•Weipan Xu, Xiaozhen Qin et al.•ARTICLE•Humanities and Social Sciences…•2021

    China, the world’s second largest economy, is transitioning into an advanced, knowledge-based economy after four decades of rapid economic development. However, China still lacks a detailed understanding of the skills that underly the Chinese labor force, and the development and spatial distribution of these skills. Similar data has proven essential in other contexts; for example, the US standardized skill taxonomy, Occupational Information Netwo…

  • Art and the science of generative AI

    Open Access•Ziv Epstein, Sudi Nurtini et al.•ARTICLE•Science•2023

    Understanding shifts in creative work will help guide AI’s impact on the media ecosystem

  • Behaviour-based dependency networks between places shape urban economic resilience

    Open Access•Takahiro Yabe, Bernardo García Bulle Bueno et al.•ARTICLE•Nature Human Behaviour•2024•Citada por: 3•Referencias: 39

    Disruptions, such as closures of businesses during pandemics, not only affect businesses and amenities directly but also influence how people move, spreading the impact to other businesses and increasing the overall economic shock. However, it is unclear how much businesses depend on each other during disruptions. Leveraging human mobility data and same-day visits in five US cities, we quantify dependencies between points of interest encompassing…

  • Stakeholder Satisfaction Interdependencies in 10-K Reports

    Open Access•Yishan Luo, Morgan R Frank et al.•ARTICLE•Journal of Business Ethics•2026

Computer Science (5 obras) · Psychology (4 obras) · Business (3 obras) · Economics (3 obras) · Regional Economics and Spatial Analysis (3 obras) · Sociology (3 obras) · Artificial Intelligence (2 obras) · Demography (2 obras) · Economic growth (2 obras) · Human Mobility and Location-Based Analysis (2 obras)

Ethnos_APP • Proyecto Open Source • Licencia MIT • Frontend v2.0.0 • Privacidad y Cookies • Documentación de la API: api.ethnos.app/docs • Código de la API: GitHub • DOI: 10.5281/zenodo.17049435 • Código del Frontend: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae