Geo-visualization of Hotspots of Citizens Dissatisfaction on Social Services Using Media Print: A Case Study of Fuel and Cash Scarcity in Nigeria.
Keywords: Geosemantics, Geoparsing, Fuel and Cash Scarcity and Citizens Dissatisfaction.
Abstract: The recent public dissatisfaction in Nigeria due to cash and fuel scarcity underscores the critical role of these resources in the modern economy, impacting various aspects of society like transportation, commerce, and daily living expenses. Existing research on citizen dissatisfaction relied on surveys, but this study employs geosemantics techniques to extract locations of social service dissatisfaction from social media data for efficient resource allocation. The method involves crawling and classifying social media content into three categories (dissatisfied, satisfied, or neutral). Using deep learning and a rule-based geoparsing approach, the study identifies locations mentioned in dissatisfied text in real time. This real-time insight from unstructured text aids in comprehending the complex economic, social, and spatial effects of resource scarcity, facilitating the government in developing effective resource allocation strategies to improve citizens' quality of life.
Submission Category: Machine learning algorithms
Submission Number: 53
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