Machine learning for social science: An agnostic approach
Social scientists are now in an era of data abundance, and machine learning tools are
increasingly used to extract meaning from data sets both massive and small. We explain …
increasingly used to extract meaning from data sets both massive and small. We explain …
Testing causal theories with learned proxies
Social scientists commonly use computational models to estimate proxies of unobserved
concepts, then incorporate these proxies into subsequent tests of their theories. The …
concepts, then incorporate these proxies into subsequent tests of their theories. The …
The CANDOR corpus: Insights from a large multimodal dataset of naturalistic conversation
People spend a substantial portion of their lives engaged in conversation, and yet, our
scientific understanding of conversation is still in its infancy. Here, we introduce a large …
scientific understanding of conversation is still in its infancy. Here, we introduce a large …
The role of hyperparameters in machine learning models and how to tune them
Hyperparameters critically influence how well machine learning models perform on unseen,
out-of-sample data. Systematically comparing the performance of different hyperparameter …
out-of-sample data. Systematically comparing the performance of different hyperparameter …
[BOOK][B] Text as data: A new framework for machine learning and the social sciences
A guide for using computational text analysis to learn about the social world From social
media posts and text messages to digital government documents and archives, researchers …
media posts and text messages to digital government documents and archives, researchers …
Keyword‐assisted topic models
In recent years, fully automated content analysis based on probabilistic topic models has
become popular among social scientists because of their scalability. However, researchers …
become popular among social scientists because of their scalability. However, researchers …
[BOOK][B] Computational analysis of communication
Provides clear guidance on leveraging computational techniques to answer social science
questions In disciplines such as political science, sociology, psychology, and media studies …
questions In disciplines such as political science, sociology, psychology, and media studies …
Multi-criteria decision analysis for health technology assessment: addressing methodological challenges to improve the state of the art
Background Multi-criteria decision analysis (MCDA) concepts, models and tools have been
used increasingly in health technology assessment (HTA), with several studies pointing out …
used increasingly in health technology assessment (HTA), with several studies pointing out …
How do you say it matters? A multimodal analytics framework for product return prediction in live streaming e-commerce
W Xu, X Zhang, R Chen, Z Yang - Decision Support Systems, 2023 - Elsevier
As a new shop** paradigm, live streaming e-commerce has undergone rapid
development in recent years. However, a higher return rate than that of traditional e …
development in recent years. However, a higher return rate than that of traditional e …
Researcher reasoning meets computational capacity: Machine learning for social science
Computational power and big data have created new opportunities to explore and
understand the social world. A special synergy is possible when social scientists combine …
understand the social world. A special synergy is possible when social scientists combine …