Tales of a City: Sentiment Analysis of Urban Green Space in Dublin

TL;DR

This paper presents a novel AI-based sentiment analysis approach applied to social media reviews to assess urban green space quality in Dublin, aiding stakeholders in urban planning decisions.

Contribution

It introduces a unified topic modeling method for analyzing social media opinions on urban green spaces, a novel application in this context.

Findings

Identifies key characteristics of green spaces through sentiment analysis.

Supports urban planning with data-driven insights.

Demonstrates effectiveness of tailored sentiment models.

Abstract

Social media services such as TripAdvisor and Foursquare can provide opportunities for users to exchange their opinions about urban green space (UGS). Visitors can exchange their experiences with parks, woods, and wetlands in social communities via social networks. In this work, we implement a unified topic modeling approach to reveal UGS characteristics. Leveraging Artificial Intelligence techniques for opinion mining using the mentioned platforms (e.g., TripAdvisor and Foursquare) reviews is a novel application to UGS quality assessments. We show how specific characteristics of different green spaces can be explored by using a tailor-optimized sentiment analysis model. Such an application can support local authorities and stakeholders in understanding--and justification for--future urban green space investments.