Detecting Inspiring Content on Social Media
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Abstract (arXiv)
Inspiration moves a person to see new possibilities and transforms the way they perceive their own potential. Inspiration has received little attention in psychology, and has not been researched before in the NLP community. To the best of our knowledge, this work is the first to study inspiration through machine learning methods. We aim to automatically detect inspiring content from social media data. To this end, we analyze social media posts to tease out what makes a post inspiring and what topics are inspiring. We release a dataset of 5,800 inspiring and 5,800 non-inspiring English-language public post unique ids collected from a dump of Reddit public posts made available by a third party and use linguistic heuristics to automatically detect which social media English-language posts are inspiring.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 16 of its 59 references that are in the map. First posted on arXiv 6 Sep 2021.
Builds on
16 of 59 references.
References · 16
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4 more
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Citing papers per year: 2022: 1; 2023: 0; 2024: 1.
2 papers.