Analysis Method
Let us introduce you to how Neticle Text Analysis works.
We have developed our own search and analysis methods to find out any text's meaning without having to read it.
in my experience, this is a bad car
Web Opinion Index:-2
Recognized labels:car
"keyword_stats": {
"total_keyword_hit_number":1,
"total_synonym_hit_numbers": [
{
"car":1
}
]
}
The system is keyword based which means you can add keywords and their synonyms. It will find every text that contains the given word and analyse it based on the keyword's context.
The system analyses the hits automatically and rates them between -3 and +3 based on the strength of the keyword's polarity. We call this the opinion index.
The scores of the keywords are added up, so you can see the overall opinion and reputation of them.
We can manage negations and double negations and we can also recognize irony.
We can customize the algorithm if needed (e.g. if the field or industry of a given keyword requires the recognition of specific expressions in the content).
"recognized_negative_phrases": [
{
"related_pos_phrases": [
],
"phrase":"a bad",
"mention_number":1,
"related_entities": [
],
"mentions": [
" this is a bad car"
],
"related_neg_phrases": [
]
}
],
This is how we have created our market leading algorithm which is able to analyse texts with near human-level precision.
If two people manually score thousands of texts based on their sentiment, their opinion match at the maximum of 82% because of human subjectivity. Neticle's algorithm generally performs above that.
Besides sentiment, we also recognize what the hits are about. Our algorithm automatically recognizes places, topics, persons and brands.