Artificial Intelligence
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why we are using textmining content analysis for assessing indicators related to infrastructure in sdg 11.


1. Large Volume of Unstructured Data: Text mining allows us to analyze a large volume of unstructured data, such as social media posts, news articles, and reports related to infrastructure. This helps us to get a comprehensive understanding of the current situation and challenges related to infrastructure in SDG 11. 2. Identification of Key Themes: Content analysis through text mining helps in identifying key themes and topics that are frequently mentioned in relation to infrastructure. This can help us to prioritize the most critical areas for improvement in infrastructure under SDG 11. 3. Extraction of Relevant Information: Text mining techniques can extract relevant information from unstructured data sources and categorize them into different indicators, such as access to basic services, public transport, and sustainable urbanization. This can help in assessing the progress made towards specific targets of SDG 11. 4. Comparison Across Time and Geography: Text mining allows for easy comparison of data across different time periods and geographical regions. This can be useful in identifying trends and patterns related to infrastructure development and determine the effectiveness of policies and initiatives. 5. Identification of Public Perceptions: Text mining can also be used to analyze public perceptions and sentiments related to infrastructure in SDG 11. This can help in understanding the impact of infrastructure on the quality of life of people and identify areas that need improvement. 6. Integrating Different Data Sources: Text mining can integrate data from various sources, such as social media, news articles, and reports, to provide a holistic view of the infrastructure situation. This can help in developing more comprehensive and evidence-based policies. 7. Real-time Monitoring: Text mining is a useful tool for real-time monitoring of progress towards SDG 11. By continuously analyzing data from different sources, we can identify emerging issues and take timely actions accordingly. 8. Cost and Time-effective: Text mining is a cost-effective and time-efficient method for analyzing a large volume of data. It eliminates the need for manual reading and analysis, which can be time-consuming and resource-intensive.