Artificial Intelligence (AI) is generating new horizons in one of the biggest challenges in the
world's society—poverty. Our goal is to investigate utilities of AI in poverty prediction via …

Energy poverty affects billions worldwide, including people in developed and developing
countries. Identifying those living in energy poverty and implementing successful solutions …

Conventional measurements of urban poverty mainly rely on census data or aggregated
statistics. However, these data are produced with a relatively long cycle, and they hardly …

In this study, an interpretable machine learning algorithm is proposed for the issues of
intelligent decision through predicting the firms' efficiency of innovation. Based on the …

Poverty statistics are conventionally compiled using data from socioeconomic surveys. This
study examines an alternative approach to estimating poverty by investigating whether …

There are now more violent conflicts globally than at any time in the past three decades,
resulting in the largest forced displacement crisis ever recorded. Understanding at a …

We study how two groups, those inside vs those outside echo chambers, react to a political
event when we vary social media status (Twitter). Our treatments mimic two strategies often …

The poverty rate in Malaysia is determined through financial or income indices and
measurements. As such, periodic measurements are conducted through Household …

Poverty is a severe problem faced by all nations. Eradicating poverty tops first in the
Sustainable Development Goals. The elimination of poverty requires an understanding of …

Poverty reduction in low‐and middle‐income countries is increasingly an urban challenge,
and a challenge that continues to be constrained by lack of data, including data on the …