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Text mining and
Analyze the most used words in your reviews, capture concepts, analyze hidden trends and detect unspoken emotions in the texts.
Text mining processes are capable of analyzing any type of text, extracting meanings and emotions, and categorizing brand perceptions. The texts are granulated by identifying adjectives and generic phrases that commonly have a positive or negative connotation (for example: «Wonderful (adjective), «I would repeat without a doubt (generic phrase))».
Text mining analyzes are especially useful when combined with Image Recognition, OCR and Speech Recognition processes. Thus creating a circular intelligence of textual interpretation.
Automating text mining processes allows you to establish alert systems and have control of your audience (or that of your competition) in real time.
- Consumer analysis
- Process automation
- Competition analysis
- Billing Increase
- Reactive strategies
Easy to process outputs
Study the evolution of your brand perception, predict emotional trends, and automate processes based on the texts entered by the client.
Our text mining models are not yet ready to interpret texts written in certain languages such as Arabic, Korean or Vietnamese (among others). Ask for more information.
The global network structure of the SoU, 1790–2014. A community detection algorithm reveals cohesive clusters or discursive categories from the semantic network built from the 1,000 × 1,000 terms matrix over the SoU’s history. Some terms lie between clusters and serve as bridges connecting otherwise disjointed discourses. Two clusters contain only a few linked terms: one indexes the set of concepts associated with immigration, the other those associated with crime. Click for larger image. Source: sciencenode.org
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