Tweet Sentiment Analysis API

API ID 739

This API will allow you to recognize the sentiment of a given Tweet URL.

100% uptime 479 ms avg response

API Documentation

Endpoints

Request

Given a tweet URL, this API will run an NLP analysis and it will deliver its detected sentiment with a confidence score. 

Endpoint ID: 452
POST https://docs.zylalabs.com/api/739/tweet+sentiment+analysis+api/452/tweet+analysis
INPUT PARAMETERS

Tweet Analysis — Endpoint Features

Object Description
Request Body Required Json

Free test requests remaining: 3 of 3.


INPUT PARAMETERS

API EXAMPLE RESPONSE
JSON
{"Sentiment":"positive","Value":0.32089,"Tweet":"As curator of the Bitcoin Cash City, I am extremally proud of every business and customer that uses Bitcoin Cash.\n\nThat said we are a city of 200,000 people with 200 merchants that accept BCH.\n\n#BitcoinWhitePaperDay #BitcoinCash "}
Tweet Analysis — CODE SNIPPETS

curl --location --request POST 'https://zylalabs.com/api/739/tweet+sentiment+analysis+api/452/tweet+analysis' --header 'Authorization: Bearer YOUR_API_KEY' 

--data-raw '{
    "tweetUrl": "https://twitter.com/TheBitcoinJason/status/1588176762319474688"
}'

    

API Access Key & Authentication

After signing up, every developer is assigned a personal API access key, a unique combination of letters and digits provided to access to our API endpoint. To authenticate with the Tweet Sentiment Analysis API simply include your bearer token in the Authorization header.

Headers
Header Description
Authorization Required Should be Bearer access_key. See "Your API Access Key" above when you are subscribed.

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Overview

About the API:

This API uses NLP to detect the sentiment that a given text could have. This API in particular will allow you to check this from a given tweet of your choice. 

 

What your API receives and what your API provides (input/output)?

 

Just pass the tweet URL that you want to check its sentiment from, and receive the output. Positive, negative, or neutral? You will be able to know with this API. 

 

What are the most common uses cases of this API?

This kind of API is ideal to have a better understanding of what the users are saying about a certain topic. 

You will be able to check what is the average tweet sentiment of a selected topic. 

Also, you will be able to detect what is the sentiment about a given product or keyword present on those tweets, so you may have more information if the users are happy or not about that specific matter. 

 

Are there any limitations to your plans?

The only limitation is the number of API calls you can make per month. And, also, you can only create 1 API calls per second. 
Also, free plan has a limitation of 33 calls per day. 

Tweet Sentiment Analysis API FAQs

The API returns sentiment analysis results for a given tweet URL, including the detected sentiment (positive, negative, or neutral) and a confidence score indicating the reliability of the sentiment assessment.

The response data includes three key fields: "Sentiment" (the sentiment classification), "Value" (the confidence score), and "Tweet" (the original tweet text being analyzed).

The response data is structured in JSON format, with key-value pairs for easy parsing. For example, a typical response might look like: `{"Sentiment":"positive","Value":0.32089,"Tweet":"...original tweet text..."}`.

The API provides sentiment analysis for tweets, allowing users to understand public opinion on specific topics, products, or keywords based on the sentiment expressed in the tweets.

Users can customize their requests by providing different tweet URLs to analyze. Each URL will yield a unique sentiment analysis based on the content of the tweet.

The data is sourced from publicly available tweets on Twitter. The API utilizes Natural Language Processing (NLP) techniques to analyze the text and determine sentiment.

Typical use cases include monitoring brand sentiment, analyzing public opinion on current events, and assessing customer feedback on products or services through tweet sentiment.

Users can leverage the sentiment and confidence score to gauge public sentiment trends, inform marketing strategies, or enhance customer engagement by addressing concerns highlighted in negative tweets.

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