相关论文: Predicting Economic Development using Geolocated W…

Local news has become increasingly important in the news industry due to its various benefits. It offers local audiences information that helps them participate in their communities and interests. It also serves as a reliable source of…

Poverty prediction models are used to address missing data issues in a variety of contexts such as poverty profiling, targeting with proxy-means tests, cross-survey imputations such as poverty mapping, top and bottom incomes studies, or…

Wikipedia is edited by volunteer editors around the world. Considering the large amount of existing content (e.g. over 5M articles in English Wikipedia), deciding what to edit next can be difficult, both for experienced users that usually…

Wikipedia articles aim to be definitive sources of encyclopedic content. Yet, only 0.6% of Wikipedia articles have high quality according to its quality scale due to insufficient number of Wikipedia editors and enormous number of articles.…

Stance detection infers a text author's attitude towards a target. This is challenging when the model lacks background knowledge about the target. Here, we show how background knowledge from Wikipedia can help enhance the performance on…

In this work, we are interested in the inner-cultural background shaping broad people's preferences. Our interest is also to track this human footprint, as it has the tendency to disappear due to the nowadays globalization. Given that…

The socioeconomic background of people and how they use standard forms of language are not independent, as demonstrated in various sociolinguistic studies. However, the extent to which these correlations may be influenced by the mixing of…

From 2000 to 2015, the UN's Millennium Development Goals guided global priorities. The subsequent Sustainable Development Goals (SDGs) adopted a more dynamic approach, with annual indicator updates. As 2030 nears and progress lags,…

The usage of non-authoritative data for disaster management presents the opportunity of accessing timely information that might not be available through other means, as well as the challenge of dealing with several layers of biases.…

Sustainable Development Goals (SDGs) bring together the diverse development community and provide a clear set of development targets for 2030. Given a large number of actors and initiatives related to these goals, there is a need to have a…

The communities that we live in affect our health in ways that are complex and hard to define. Moreover, our understanding of the place-based processes affecting health and inequalities is limited. This undermines the development of robust…

Signed network analysis has attracted increasing attention in recent years. This is in part because research on signed network analysis suggests that negative links have added value in the analytical process. A major impediment in their…

Accurate local-level poverty measurement is an essential task for governments and humanitarian organizations to track the progress towards improving livelihoods and distribute scarce resources. Recent computer vision advances in using…

Sustainable development is an imperative worldwide but metrics and data on poverty and quality of life have remained too coarse and abstract to characterize challenges adequately and guide practical progress. Nowhere is this challenge…

In many regions of the world, sparse data on key economic outcomes inhibits the development, targeting, and evaluation of public policy. We demonstrate how advancements in satellite imagery and machine learning can help ameliorate these…

Social media (SM) data provides a vast record of humanity's everyday thoughts, feelings, and actions at a resolution previously unimaginable. Because user behavior on SM is a reflection of events in the real world, researchers have realized…

Urban agglomerations are constantly and rapidly evolving ecosystems, with globalization and increasing urbanization posing new challenges in sustainable urban development well summarized in the United Nations' Sustainable Development Goals…

Predicting the occurrence of links is a fundamental problem in networks. In the link prediction problem we are given a snapshot of a network and would like to infer which interactions among existing members are likely to occur in the near…

This paper reviews the state of the art in satellite and machine learning based poverty estimates and finds some interesting results. The most important factors correlated to the predictive power of welfare in the reviewed studies are the…

Geo-localization is the task of identifying the location of an image using visual cues alone. It has beneficial applications, such as improving disaster response, enhancing navigation, and geography education. Recently, Vision-Language…