AI-powered API

Product Review Sentiment Checker

Analyzes customer reviews and returns the sentiment score.

The Product Review Sentiment Analysis API parses the customer's product review and provides its sentiment (POSITIVE/NEGATIVE/NEUTRAL) with a score between 0-100%.

This API is perfect for generating sentiment reports for any online store, offering valuable insights into customer feedback.

Developers can use this API to enhance e-commerce platforms, customer feedback systems, or sentiment analysis tools. It automates the analysis process, helping businesses understand customer opinions and improve their offerings. Use cases include creating sentiment reports, enhancing customer service strategies, and refining product descriptions based on customer feedback.

NEUTRAL sentiment will always have score equals to 0.

AI jobs involve two key steps:

Submitting the AI job: Initiating the process by sending the job request.
Monitoring and receiving results: Continuously checking the job status and obtaining the final output upon successful completion.

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Step 1. Submit the AI Job request

Endpoint: POST - /v1/ecommerce/review_sentiment

Attribute	Type	Mandatory	Description
content	String	Yes	Provide review text to analyze the sentiment.

REQUEST EXAMPLE:

{
  "content": "I got a variant of this laptop 4090 with miniLED and surprise, it does not work in SDR and if you enable HDR to make the miniLED work it causes so much back light bleed you can see light follow the mouse and around the the text. I found out Razer has two variants of the panel one called BOE and one called AUO. The BOE i got is whats broken, and they have the audacity to sell an inferior version of the laptop (early 2023) with a huge faulty screen.refer to my images to see how bad the MiniLED looks when HDR is enable, and without HDR well, the miniLED simply does not work. Great job Razer, will be returning this as I have no way of telling if I get the BOE or AUO variant of the screen. Do some research on this if you going for the MiniLED version.Other than the screen which is one of main reasons you likely buying this, the performance is amazing and temps are great."
}

RESPONSE EXAMPLE:

{
  "status_url": "https://sharpapi.com/api/v1/content/translate/job/status/5de4887a-0dfd-49b6-8edb-9280e468c210",
  "job_id": "5de4887a-0dfd-49b6-8edb-9280e468c210"
}

Step 2. Monitor & Fetch AI Job Results

Endpoint: GET - /v1/ecommerce/review_sentiment/job/status/:uuid

An endpoint is used to check on the progress of the requested API job.

Result Example:

{
    "data": {
        "type": "api_job_result",
        "id": "f245cf5a-26da-4c02-91d7-01606a1a8759",
        "attributes": {
            "status": "success",
            "type": "ecommerce_review_sentiment",
            "result": {
                "opinion": "NEGATIVE",
                "score": 75,
                "emotion": "frustration",
                "urgency": "moderate",
                "topics": [
                    {
                        "topic": "screen_quality",
                        "sentiment": "negative",
                        "mention_count": 3
                    },
                    {
                        "topic": "performance",
                        "sentiment": "positive",
                        "mention_count": 1
                    },
                    {
                        "topic": "backlight_bleed",
                        "sentiment": "negative",
                        "mention_count": 2
                    }
                ],
                "loyalty_signal": "detractor",
                "recommended_action": "investigate_issue",
                "language": "en",
                "review_quality": "detailed"
            }
        }
    }
}

Related Keywords:
Sentiment
Reviews
Feedback
E-commerce