Cross-cultural Inspiration Detection and Analysis in Real and LLM-generated Social Media Data
Authors: Oana Ignat, Gayathri G L, Rada Mihalcea


Reviewer paper summaries: This paper investigates the concept of inspiration across different cultures using machine learning techniques. It addresses the scarcity of research focused specifically on inspiring content, distinct from merely positive or engaging material. A notable gap identified is the lack of cross-cultural studies on inspiration, with previous works predominantly centered around Western contexts. To tackle these issues, the authors present the INSPIRED dataset, which includes 2,000 real inspiring posts, 2,000 real non-inspiring posts, and 2,000 AI-generated inspiring posts, equally distributed between India and the UK. The real posts are sourced from Reddit, while the AI-generated ones are produced using the GPT-4 model. Through extensive computational linguistic analysis, the study aims to compare inspiring content across cultures, assess the quality of AI-generated inspiring posts relative to real ones, and evaluate the accuracy of models in distinguishing inspiring content across cultures and data sources.
Summary of strengths: The creation of the INSPIRED dataset fills a research gap by providing a resource for studying cross-cultural differences in inspiration and the capability of AI to generate inspiring content.

The study's focus on comparing inspiration across Indian and UK cultures gives insights into the universality and specificity of inspirational content, contributing to a more global understanding of inspiration.
Summary of weaknesses: While the paper acknowledges the need for cross-cultural research, its focus on only two countries (India and the UK) may not adequately represent global diversity. Additional cultures could provide a broader perspective on inspiration.

I do not see much significance regarding the analysis on differentiating between GPT-generated inspiring content and human-written inspiring content. The focus should be exploring various user reaction to different inspiring content. The analysis is not deep enough. There seems to be no significant/interesting findings for cross-culture inspiring content, which is claimed to be one of the main contributions.
Comments, suggestions and typos: N/A
Overall assessment scores: 2.5