Text Summerisation of Nigeria Economic Discourse from Social Media Platform
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Text SummarizationProject Title: Sentiment Analysis of Public Opinion on the Nigerian Economy Data Labelling Task Performed: Text Classification (Topic Labelling) for Sentiment Analysis preparation. Each collected text was manually reviewed and labelled with a relevant economic topic/category (e.g., Fuel Price, Naira Exchange Rate, Food Prices, Unemployment, etc.). This topic labelling served as the primary data labelling task to organize the dataset before performing sentiment analysis using Microsoft Fondary. Project Size: Total texts collected and labelled: 68 short texts Sources: Twitter/X posts and Nigerian news websites (Vanguard and Punch) more from Twitter/X Time period: Texts collected between April 20– April 22, 2026 Quantity Measures Adhered To: Collected 68 texts, which falls within the required range of 50–80 short texts as specified in the project brief. Each text entry was properly labelled with a topic label. Texts were organized in a structured Excel sheet with columns for: Original Text, Source, Topic Label, and later enriched with Azure AI Sentiment results (Positive, Negative, Neutral, and Opinion Targets). This labelled dataset was used to conduct sentiment analysis, identify opinion targets, and derive insights into current public sentiment regarding key economic issues in Nigeria.