Detecting Inspiring Content on Social Media

TL;DR

This paper introduces the first machine learning approach to automatically detect inspiring social media content, analyzing linguistic features and topics to distinguish inspiring posts from non-inspiring ones, based on a new dataset from Reddit.

Contribution

It presents a novel dataset and methodology for identifying inspiring content in social media using NLP techniques, addressing an unexplored area in psychology and NLP.

Findings

Successful automatic detection of inspiring posts

Identification of linguistic features associated with inspiration

Creation of a publicly available dataset for future research

Abstract

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.