CLEVER: Social Market Module

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This CLEVER module is designed to analyse and visualise the impact of a company and its products on social media using natural-language-processing tools. Its purpose is to capture, process and interpret mentions, opinions and digital conversations in order to provide information on brand perception, product acceptance, trends and potential reputational issues.
The solution applied NLP techniques to extract relevant indicators from social content. It is currently inactive because it was designed mainly to work with Twitter and, since 2023, the cost of using its APIs has made operational use unviable.

Social-media perception analysis
The main application was to provide a social-media intelligence layer showing how the company and its products were perceived across digital channels. Using NLP techniques, the module could analyse mentions, comments and posts to identify sentiment, recurring topics, the evolution of conversations and early signals of opportunity or risk. This information was useful to marketing, communications, product and customer-service teams, linking social activity to business decisions and reputation monitoring.

Reputation intelligence and early detection
The main benefit was transforming unstructured social-media information into useful decision-making indicators. Automated conversation analysis could detect changes in brand perception, identify product-related problems, anticipate reputational crises and assess market response to campaigns or launches. Although the module is currently inactive because Twitter API costs have made it economically unviable since 2023, its approach remains applicable to other accessible social sources or digital channels.

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