A Dataset for Psychological Human Needs Detection From Social Networks

A real-time awareness of an individual’s affective state is the goal of the affect-aware city. Being aware of different affective states can be useful to enhance a citizen’s quality of life and their experiences. In this paper, we aim to provide new insight to the affect-aware city and analyze individual experiences in regards to basic human needs. We propose a theoretical based multi-layer framework for a psychological needs analysis that is guided by research in the field of motivational psychology. The framework’s layers are constructed to identify the psychological needs, measure their satisfaction level, and assess the individual’s surrounding environment in different aspects of life. We created a psychological needs corpus: a collection of Twitter posts annotated based on three universal needs proposed by the self-determination theory framework. Several techniques were employed to encourage high-quality annotations. We provide descriptive statistics of the annotated corpus. This corpus can be used in the development of automatic detection systems and predication models to detect individual needs and measure their satisfaction. It can also be used to better interpret and understand the individual’s surrounding social contexts.