Tobii Pro Lab: Eye Tracking Software for Behavior Research
Tobii Pro Lab is a comprehensive eye tracking software designed for behavioral research, offering a complete solution for researchers to conduct experiments from test design to data analysis.
Detaillierte Einführung
Tobii Pro Lab is the world-leading experimental software for eye tracking studies. It provides a visual user interface and dedicated software features that guide and support researchers through all phases of an eye tracking experiment. The software is designed to be powerful yet user-friendly, making it easy to get started with eye tracking research. It offers a large degree of flexibility to run advanced experiments for in-depth insights into attention and cognitive processes. Tobii Pro Lab is ideal for academic researchers and consumer researchers alike, providing valuable insights into human behavior and experience.
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APA PsycInfo: Behavioral and Social Sciences Database
APA PsycInfo is the premier abstracting and indexing database covering the behavioral and social sciences. It provides over 5,000,000 peer-reviewed records, 144 million cited references, and spans 600 years of content. The database is updated twice-weekly and includes research in 30 languages from 50 countries.
Mental Health in Tech Survey
This dataset contains survey responses from individuals in the tech industry about their mental health, including questions about treatment, workplace resources, and attitudes towards discussing mental health in the workplace. By analyzing this dataset, we can better understand how prevalent mental health issues are among those who work in the tech sector—and what kinds of resources they rely upon to find help—so that more can be done to create a healthier working environment for all.
Depression: Twitter Dataset + Feature Extraction
This dataset contains 20,000 labelled English tweets of depressed and non-depressed users. The data is collected using the Twitter API and includes feature extraction techniques such as topic modelling and emoji sentiment analysis. It is designed for mental health classification at the tweet level.