Detecting Inspiring Content on Social Media
Ignat, Oana, Boureau, Y-Lan, Yu, Jane A., Halevy, Alon
–arXiv.org Artificial Intelligence
Our work aims to facilitate by Thrash and Elliot as possessing three core such encounters by providing tools for automatic identification characteristics: evocation (i.e., it is triggered rather than of text content likely to be judged inspiring. We focus on willed), transcendence (i.e., it orients towards things outside inspiration in everyday content as judged by lay people, similar of and greater than the self), and approach motivation (i.e., it in spirit to early work by Hart who attempted to capture the energizes approach rather than avoidance [1]-[3]). Inspiration experience of inspiration in ordinary life [5], rather than "as if has two distinct stages: one an activation state that is more akin it were reserved for the gifted artist, the breakthrough scientist, to feeling and emotion, the second an urge to act.
arXiv.org Artificial Intelligence
May-29-2023
- Country:
- North America > United States (0.46)
- Genre:
- Research Report (1.00)
- Industry:
- Health & Medicine > Therapeutic Area (0.68)
- Information Technology > Services (0.46)
- Media > News (0.47)
- Technology:
- Information Technology
- Artificial Intelligence
- Machine Learning > Statistical Learning (0.93)
- Natural Language (1.00)
- Communications > Social Media (1.00)
- Data Science (0.93)
- Artificial Intelligence
- Information Technology