Related Experiment Video
Updated: Aug 23, 2025
13:44
Project-Based Learning Guidelines for Health Sciences Students: An Analysis with Data Mining and Qualitative Techniques
Published on: December 9, 2022
3.6K
Researcher reasoning meets computational capacity: Machine learning for social science.
Ian Lundberg1, Jennie E Brand2, Nanum Jeon2
1Department of Information Science, Cornell University, USA.
Social Science Research
|November 5, 2022
Summary
Machine learning (ML) enhances social science research by automating data analysis and targeting researcher attention. These accessible ML tools offer new ways to discover insights from big data in the social world.
Area of Science:
- Social Sciences
- Computational Social Science
- Data Science
Background:
- Big data and computational power offer new avenues for social world exploration.
- Synergy between human attention and algorithmic automation is key for social scientists.
- Machine learning (ML) presents opportunities to advance social science research methods.
Conclusions:
- Machine learning tools are increasingly accessible and valuable for social research.
- ML offers significant potential for generating new discoveries in the social sciences.
- Social scientists should consider adopting ML tools to enhance their research capabilities.
Related Concept Videos
01:22Statistical Package for the Social Sciences (SPSS)
486
The Statistical Package for the Social Sciences, or SPSS, is a data management and analysis software suite. Developed by SPSS Inc. in 1968 and acquired by IBM in 2009, this tool was initially designed for social science data analysis, evolving to serve a wider range of disciplines. It was later renamed to Statistical Product and Service Solutions.
SPSS streamlines the process from data preparation to analysis and reporting. It is characterized by its user-friendly interface, which conceals...
SPSS streamlines the process from data preparation to analysis and reporting. It is characterized by its user-friendly interface, which conceals...
486
01:12Statistical Software for Data Analysis and Clinical Trials
739
Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
739
01:23Mechanistic Models: Compartment Models in Individual and Population Analysis
79
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
79
01:29Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
98
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
98
02:16Stereotype Content Model
14.8K
The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence...
14.8K
01:11Statistical Analysis: Overview
7.0K
When we take repeated measurements on the same or replicated samples, we will observe inconsistencies in the magnitude. These inconsistencies are called errors. To categorize and characterize these results and their errors, the researcher can use statistical analysis to determine the quality of the measurements and/or suitability of the methods.
One of the most commonly used statistical quantifiers is the mean, which is the ratio between the sum of the numerical values of all results and the...
One of the most commonly used statistical quantifiers is the mean, which is the ratio between the sum of the numerical values of all results and the...
7.0K