- Neticle Knowledge Base
- Text Analysis API
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What is Neticle Media Intelligence?
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NMI Basic Methodology
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Getting Started with NMI
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Zurvey.io Platform
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Zurvey.io Text Analysis Methodology
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Zurvey.io Home & Dataset
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Zurvey.io Inputs
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Zurvey.io Settings
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Zurvey.io Outputs
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Zurvey.io Survey Module
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Zurvey.io Audience
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Privacy & Legal
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Conversation Analysis
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Text Analysis API
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Data API
How does Neticle's automated labeling work?
Labels are defined by the sets of synonyms.
Besides sentiment lexicons, Neticle also has a lexicon for labels, where the available labels have their corresponding sets of synonyms. The label is recognized in a verbatim only if any of its synonyms can be found in the text, either by matching the beginning of a phrase, or by an exact match (depending on the settings of each label). Some labels can have excluded phrases as well: this prevents the label recognition in texts where the excluded phrase is present.
For example, the English label “import” has one synonym: import. It matches if the beginning of a phrase contains the string import, so the following phrases will be a hit: import, importing, imported, importer, etc. However, it also has two excluded phrases: important, importance. This means that even if a phrase begins with import (a synonym), it will not be a hit if it also begins with any of the excluded phrases.
